SkyPilot is a platform that allows users to execute operations such as machine learning or data processing across many cloud services (such as Amazon Web Services, Google Cloud, or Microsoft Azure) without having to understand how each cloud works separately.

In simple terms, it does the following:

Cost Savings: It finds the cheapest cloud service and automatically runs your tasks there, saving you money.

Multi-Cloud Support>: You can execute your jobs across several clouds without having to change your code for each one.

Automation: SkyPilot handles technical setup for you, such as establishing and stopping cloud servers, so you don't have to do it yourself.

Spot Instances:It employs a unique form of cloud server that is less expensive (but may be interrupted), and if it is interrupted, SkyPilot instantly transfers your task to another server.

Getting Started with SkyPilot on AWS#

Prerequisites#

Before you start using SkyPilot, ensure you have the following:

1. AWS Account#

To create and manage resources, you need an active AWS account with the relevant permissions.

• EC2 Instances: Creating, modifying, and terminating EC2 instances.

• IAM Roles: Creating and managing IAM roles that SkyPilot will use to interact with AWS services.

• Security Groups: Setting up and modifying security groups to allow necessary network access.

You can attach policies to your IAM user or role using the AWS IAM console to view or change permissions.

2. Create IAM Policy for SkyPilot#

You should develop a custom IAM policy with the necessary rights so that your IAM user may utilize SkyPilot efficiently. Proceed as follows:

Create a Custom IAM Policy:

• Go to the AWS Management Console.
• Navigate to IAM (Identity and Access Management).
• Click on Policies in the left sidebar and then Create policy.
• Select the JSON tab and paste the following policy:

• Click Next: Tags and then Next: Review.
• Provide a name for the policy (e.g., SkyPilotPolicy) and a description.
• Click Create policy to save it.

Attach the Policy to Your IAM User:

• Navigate back to Users and select the IAM user you created earlier.
• Click on the Permissions tab.
• Click Add permissions, then Attach existing policies directly.
• Search for the policy you just created (e.g., SkyPilotPolicy) and select it.
• Click Next: Review and then Add permissions.

3. Python#

Make sure your local computer is running Python 3.7 or later. The official Python website. offers the most recent version for download.

Use the following command in your terminal or command prompt to confirm that Python is installed:

If Python is not installed, follow the instructions on the Python website to install it.

4. SkyPilot Installed#

You need to have SkyPilot installed on your local machine. SkyPilot supports the following operating systems:

• Linux
• macOS
• Windows (via Windows Subsystem for Linux (WSL))

To install SkyPilot, run the following command in your terminal:

After installation, you can verify if SkyPilot is correctly installed by running:

The installation of SkyPilot is successful if the command yields a version number.

5. AWS CLI Installed#

To control AWS services via the terminal, you must have the AWS Command Line Interface (CLI) installed on your computer.

To install the AWS CLI, run the following command:

After installation, verify the installation by running:

If the command returns a version number, the AWS CLI is installed correctly.

6. Setting Up AWS Access Keys#

To interact with your AWS account via the CLI, you'll need to configure your access keys. Here's how to set them up:

Create IAM User and Access Keys:

• Go to the AWS Management Console.
• Navigate to IAM (Identity and Access Management).
• Click on Users and then select user which you created before.
• Click on Security Credentials.
• Click on Create Access Key.
• In use case select Command Line Interface.
• Give the confirmation and click on next.
• Click on Create Access Key and download the Access key.

Configure AWS CLI with Access Keys:

• Run the following command in your terminal to configure the AWS CLI:

When prompted, enter your AWS access key ID, secret access key, default region name (e.g., us-east-1), and the default output format (e.g., json).

Example:

Once the AWS CLI is configured, you can verify the configuration by running:

This command will return details about your AWS account if everything is set up correctly.

Launching a Cluster with SkyPilot#

Once you have completed the prerequisites, you can launch a cluster with SkyPilot.

1. Create a Configuration File#

Create a file named sky-job.yaml with the following content:

Example:

2. Launch the Cluster#

In your terminal, navigate to the directory where your sky.yaml file is located and run the following command to launch the cluster:

This command will provision the resources specified in your sky.yaml file.

3. Monitor the Cluster Status#

To check the status of your cluster, run:

4. Terminate the Cluster#

If you want to terminate the cluster, you can use the following command:

This command will clean up the resources associated with the cluster.

5. Re-launching the Cluster#

If you need to launch the cluster again, you can simply run:

This command will recreate the cluster using the existing configuration.

Conclusion#

Now that you've completed the above steps, you should be able to install SkyPilot, launch an AWS cluster, and properly manage it. This guide will help you get started with SkyPilot by providing a complete introduction. Good luck with the clustering!

Useful Resources for SkyPilot on AWS#

Readers wishing to extend their expertise or explore other configuration possibilities, here are some valuable resources:

• SkyPilot Official Documentation
  Visit the SkyPilot Documentation for comprehensive guidance on setup, configuration, and usage across cloud platforms.

• AWS CLI Installation Guide
  Learn how to install the AWS CLI by visiting the official AWS CLI Documentation.

• Python Installation
  Ensure Python is correctly installed on your system by following the Python Installation Guide.

• Setting Up IAM Permissions for SkyPilot
  SkyPilot requires specific AWS IAM permissions. Learn how to configure these by checking out the IAM Policies Documentation.

• Running SkyPilot on AWS
  Discover the process of launching and managing clusters on AWS with the SkyPilot Getting Started Guide.

• Using Spot Instances with SkyPilot
  Learn more about cost-saving with Spot Instances in the SkyPilot Spot Instances Guide.

DynamoDB Streams and AWS Lambda can be integrated to create effective serverless apps that react to changes in your DynamoDB tables automatically. Developers frequently run into problems with this integration when the Lambda function is not called as intended. We'll go over how to troubleshoot and fix scenarios where your DynamoDB Stream isn't triggering your Lambda function in this blog article.

What Is DynamoDB Streams?#

Data changes in your DynamoDB table are captured by DynamoDB Streams, which enables you to react to them using a Lambda function. Every change (like INSERT, UPDATE, or REMOVE) starts the Lambda function, which can then analyze the stream records to carry out other functions like data indexing, alerts, or synchronization with other services. Nevertheless, DynamoDB streams occasionally neglect to call the Lambda function, which results in the modifications going unprocessed. Now let's explore the troubleshooting procedures for this problem.

1. Ensure DynamoDB Streams Are Enabled#

Making sure DynamoDB Streams are enabled for your table is the first step. The Lambda function won't get any events if streams aren't enabled. Open the Management Console for AWS. Go to Your Table > DynamoDB > Tables > Exports and Streams. Make sure DynamoDB Streams is enabled and configured to include NEW_IMAGE at the very least. Note: What data is recorded depends on the type of stream view. Make sure your view type is NEW_IMAGE or NEW_AND_OLD_IMAGES for a typical INSERT operation.

2. Check Lambda Trigger Configuration#

A common reason for Lambda functions not being invoked by DynamoDB is an improperly configured trigger. Open the AWS Lambda console. Select your Lambda function and navigate to Configuration > Triggers. Make sure your DynamoDB table's stream is listed as a trigger. If it's not listed, you'll need to add it manually: Click on Add Trigger, select DynamoDB, and then configure the stream from the dropdown. This associates your DynamoDB stream with your Lambda function, ensuring events are sent to the function when table items change.

3. Examine Lambda Function Permissions#

To read from the DynamoDB stream, your Lambda function needs certain permissions. It won't be able to use the records if it doesn't have the required IAM policies.

Ensure your Lambda function's IAM role includes these permissions:

Lambda can read and process records from the DynamoDB stream thanks to these actions.

4. Check for CloudWatch Logs#

Lambda logs detailed information about its invocations and errors in AWS CloudWatch. To check if the function is being invoked (even if it's failing):

1. Navigate to the CloudWatch console.
2. Go to Logs and search for your Lambda function's log group (usually named /aws/lambda/<function-name>).
3. Look for any logs related to your Lambda function to identify issues or verify that it's not being invoked at all.

Note: If the function is not being invoked, there might be an issue with the trigger or stream configuration.

5. Test with Manual Insertions#

Use the AWS console to manually add an item to your DynamoDB table to see if your setup is functioning: Click Explore table items under DynamoDB > Tables > Your Table. After filling out the required data, click Create item and then Save. Your Lambda function should be triggered by this. After that, verify that the function received the event by looking at your Lambda logs in CloudWatch.

6. Verify Event Structure#

Your Lambda function's handling of the incoming event data may be the problem if it is being called but failing. Make that the code in your Lambda function is handling the event appropriately. An example event payload that Lambda gets from a DynamoDB stream is as follows:

Make sure this structure is handled correctly by your Lambda function. Your function won't process the event as intended if the NewImage or Keys section is absent from your code or if the data format is off. Lambda code example Here is a basic illustration of how to use your Lambda function to handle a DynamoDB stream event:

7. Check AWS Region and Limits#

Make sure the Lambda function and your DynamoDB table are located in the same AWS region. The stream won't activate the Lambda function if they are in different geographical locations. Check the AWS service restrictions as well: Lambda concurrency: Make that the concurrency limit isn't being reached by your function. Throughput supplied by DynamoDB: Your Lambda triggers may be missed or delayed if your DynamoDB table has more read/write capacity than is allocated.

8. Retry Behavior#

There is an inherent retry mechanism in lambda functions that are triggered by DynamoDB Streams. AWS may eventually stop retrying if your Lambda function fails several times, depending on your configuration. To guarantee that no data is lost during processing, make sure your Lambda function retries correctly and handles mistakes graciously.

Conclusion#

A misconfiguration in the stream settings, IAM permissions, or event processing in the Lambda code may be the cause if DynamoDB streams are not triggering your Lambda function. You should be able to identify and resolve the issue by following these procedures and debugging the problem with CloudWatch Logs. The most important thing is to make sure your Lambda function has the required rights to read from the DynamoDB stream and handle the event data appropriately, as well as that the stream is enabled and connected to your Lambda function. Enjoy your troubleshooting!

You might eventually need to swap out an old Domain Controller (DC) for a new one when maintaining a network architecture. Decommissioning an outdated DC and installing a new one with DNS capability may be part of this procedure. The procedure is simple for those using AWS EC2 instances for this purpose, but it needs to be carefully planned and carried out. A high-level method to successfully managing this shift can be found below.

1. Install the New Domain Controller (DC) on a New EC2 Instance#

In order to host your new Domain Controller, you must first establish a new EC2 instance.

• EC2 Instance Setup: Begin by starting a fresh Windows Server-based EC2 instance. For ease of communication, make sure this instance is within the same VPC or subnet as your present DC and is the right size for your organization's needs.

• Install Active Directory Domain Services (AD DS): Use the Server Manager to install the AD DS role after starting the instance.

• Promote to Domain Controller: After the server has been promoted to a Domain Controller, the AD DS role must be installed. You will have the opportunity to install the DNS server as part of this promotion procedure. In order to manage the resolution of your domain name, this is essential.

2. Replicate Data from the Old DC to the New DC#

Making ensuring all of the data from the old DC is copied onto the new server is the next step once the new DC is promoted.

• Enable Replication: Active Directory will automatically replicate the directory objects, such as users, machines, and security policies, while the new Domain Controller is being set up. If DNS is set up on the old server, this will also include DNS records.

• Verify Replication: Ascertain whether replication was successful. Repadmin and dcdiag, two built-in Windows utilities, can be used to monitor and confirm that the data has been fully synchronized between both controllers.

3. Verify the Health of the New DC#

Before decommissioning the old Domain Controller, it is imperative to make sure the new one is completely functional.

• Use dcdiag: This utility examines the domain controller's condition. It will confirm that the DC is operating as it should.

• To make sure no data or DNS entries are missing, use the repadmin utility to verify Active Directory replication between the new and old DCs.

4. Update DNS Settings#

You must update the DNS settings throughout your network after making sure the new DC is stable and replicating correctly.

• Update VPC/DHCP DNS Settings: If you're using DHCP, make sure that the new DC's IP address is pointed to by updating the DNS settings in your AWS VPC or any other DHCP servers. This enables clients on your network to resolve domain names using the new DNS server.

• Update Manually Assigned DNS: Make sure that any computers or programs that have manually set up DNS are updated to resolve DNS using the new Domain Controller's IP address.

5. Decommission the Old Domain Controller#

It is safe to start decommissioning the old DC when the new Domain Controller has been validated and DNS settings have been changed.

• Demote the Old Domain Controller: To demote the old server, use the dcpromo command. With this command, the server no longer serves as a Domain Controller in the network and is removed from the domain.

• Verify Decommissioning: After demotion, examine the AD structure and replication status to make sure the previous server is no longer operating as a DC.

6. Clean Up and DNS Updates#

With the old DC decommissioned, there are some final cleanup tasks to ensure smooth operation.

• Tidy Up DNS and AD: Delete from both DNS and Active Directory any last traces of the previous Domain Controller. DNS entries and metadata are examples of this.

• Verify Client DNS Settings: Verify that every client computer is correctly referring to the updated DNS server.

Assigning IP Addresses to the New EC2 Instance#

You must make sure that your new DC has a stable IP address because your previous DC was probably linked to a particular one.

• Elastic IP Assignment: The new EC2 instance can be given an elastic IP address, which will guarantee that it stays the same IP throughout reboots and session restarts. By doing this, DNS resolution and domain service interruptions are prevented.

• Update Routing if Needed: Verify that the new Elastic IP is accessible and correctly routed both inside your VPC and on any other networks that communicate with your domain.

  Additional Considerations#

• Networking Configuration: Ascertain that your EC2 instances are correctly networked within the same VPC and that the security groups are set up to permit the traffic required for AD DS and DNS functions.

• DNS Propagation: The time it takes for DNS to propagate may vary depending on the size of your network. Maintain network monitoring and confirm that all DNS modifications have been properly distributed to clients and external dependencies.

Conclusion#

You can completely decommission your old Domain Controller located on an EC2 instance and install a new one with a DNS server by following these instructions. This procedure permits the replacement or enhancement of your underlying hardware and software infrastructure while guaranteeing little downtime and preserving the integrity of your Active Directory system. Your new EC2 instance can be given a static Elastic IP address, which will guarantee DNS resolution stability even when the server restarts.

For further reading and detailed guidance, explore these resources:

• Amazon EC2 Documentation
• AWS VPC Documentation
• Configuring DHCP Options in AWS
• Elastic IP Addresses in Amazon EC2
• Dcdiag Command Reference
• Networking and Security Groups in AWS

Cloud Computing and the Phases in Life of a Startup#

Innovation and startups are usually synonymous, and with it comes economic growth. A startup evolves through different phases to strive for success. Each phase requires crafted architecture, appropriate tools, and resources for good results.

So, if you have a startup looking for help, you are at the right place. In this guide, let's discuss a startup's key phases. Also, let's check out the structural considerations, tools, and resources required.

Phase 1: Idea Generation#

The first step in a startup's journey is where everything begins. It's when you come up with your business concept and plan. During this phase, you need a flexible and affordable setup.

Key components include:

Website and Landing Page Hosting:#

Host your website and landing page on cloud servers to save money and adapt to changes.

Servers like:

• Amazon Web Services
• Microsoft Azure
• Google Cloud Platforms are reliable servers.

Collaboration Tools:#

Use tools like Slack, Trello, and Google Workspace for smooth teamwork from anywhere.

These tools help with real-time communication, file sharing, and project management.

Development Tools:#

Cloud-based development helps speed the creation of prototypes and initial product versions. These platforms support version control, code collaboration, and continuous integration, reducing time-to-market. Platforms, for example, GitHub and GitLab.

Phase 2: Building#

During this phase, startups turn their ideas into reality. They do so by creating and launching their products or services.

The architecture in this phase should be scalable and reliable. Tools and resources include -

Scalable Hosting Infrastructure:#

Cloud computing services provide scalable infrastructure to handle increased traffic and growth.

Solutions you can go for:

• AWS Elastic Beanstalk
• Google App Engine
• Microsoft Azure App Service offers managed hosting environments.

Cloud-Based Databases:#

Secure, scalable, and cost-effective cloud-based databases are crucial for data storage and retrieval. Amazon RDS, Google Cloud SQL, and Azure SQL Database are popular startup choices.

Development Platforms:#

Cloud-based development platforms offer the tools needed to build and deploy applications. Platforms such as:

• AWS Lambda
• Google Cloud Functions
• Azure Functions

These allow startups to create server-less applications, reducing operational complexity.

Phase 3: Product Launch#

The launch phase marks the introduction of the startup's product or service to the market. It demands an architecture that can handle sudden spikes in user activity.

Key elements include:

Infrastructure Scaling:#

Cloud services allow startups to scale up to meet the demands of new customers. Auto-scaling features in AWS, Google Cloud, and Azure adjust resources based on traffic.

Load Balancers:#

Cloud-based load balancers distribute traffic across servers, ensuring high availability and performance. Some examples of balancers are:

• AWS Elastic Load Balancing
• Google Cloud Load Balancing
• Azure Load Balancer

Security Measures:#

For securing your startup against cyber threats during this phase, you can take the help of:

• Cloud-based firewalls
• Web application firewalls (WAFs)
• Security groups.

For common threats, you can use:

• AWS WAF
• Google Cloud Armor
• Azure Web Application Firewall

Phase 4: Expansion#

In the growth phase, startups experience rapid expansion and an increasing customer base. The architecture must accommodate this growth. Tools and resources include:

Continued Scaling:#

Cloud computing services allow startups to keep up with client's growing demands. Auto-scaling and server-less architectures allow startups to divide resources.

Adding New Features:#

Startups can scale and enhance their offerings using cloud resources and development tools. Tools like Docker and Kubernetes make it easier to roll out new functionalities.

Market Expansion:#

The global reach of cloud infrastructure allows startups to enter new markets. Content delivery networks (CDNs) like:

• AWS Cloud Front
• Google Cloud CDN
• Azure CDN

These ensure fast and reliable content delivery worldwide.

DevOps as a Service#

In the startup lifecycle, Extended DevOps Teams play an essential role. DevOps practices ensure smooth development, deployment, and operations. DevOps as a service provides startups with the following:

Speed:#

Immediate adoption of DevOps practices speeds up development and deployment cycles. Continuous integration and continuous delivery (CI/CD) pipelines automate software delivery.

Expertise:#

Access to experienced professionals who can put in place and manage IT infrastructure. Managed DevOps services and consulting firms offer guidance and support.

Cost-Effectiveness:#

Outsourcing DevOps is cost-effective to maintain an internal team. You can lower the operational cost With pay-as-you-go models and managed services. Companies can tap into the expertise of skilled DevOps professionals without any issues. This approach ensures flexibility and scalability, allowing businesses to adapt to changing needs. By outsourcing DevOps services, organizations can:

• Optimize their resources
• Focus on core competencies.
• Achieve a more streamlined and cost-efficient development and operations environment.

Cloud Management Platforms#

Cloud management platforms offer startups:

Visibility:#

Startups gain a centralized interface for overseeing all their cloud resources. Cloud management platforms offer visibility into resource usage, cost monitoring, and performance metrics.

Control:#

The ability to configure, manage, and optimize cloud resources to meet specific needs. Infrastructure as code (IaC) tools like:

• AWS Cloud Formation
• Google Cloud Deployment Manager
• Azure Resource Manager

These will allow startups to define and automate their infrastructure.

Security:#

Protection against cyber threats to secure the cloud environment and safeguard valuable assets. Cloud security services such as:

• AWS Identity and Access Management (IAM)
• Google Cloud Identity and Access Management (IAM)
• Azure Active Directory (AD)

These enhance identity and access management.

Nife's Application Lifecycle and Cloud Management Platform#

Nife is an application that serves as a life cycle management tool, offering worldwide support for software deployment and cloud management. Our state-of-the-art arrangements engage undertakings and engineers to consistently send off and scale applications inside the Nife Edge Matrix.

Improve on the intricacies of 5G, edge figuring, and cloud with our set-up of APIs and devices, guaranteeing security, protection, and cost productivity.

Conclusion#

The journey of a startup is akin to a dynamic and ever-evolving process, with each phase presenting unique challenges and opportunities.

To navigate this ever-shifting landscape effectively, a strategic approach that leverages cloud computing services and DevOps expertise is indispensable.

In the initial stages, startups often grapple with resource constraints and rapidly changing requirements. Cloud computing services provide scalability and flexibility, allowing them to adapt to evolving demands without massive upfront investments. This elasticity is critical for cost-effective growth.

As a startup matures and product or service offerings solidify, DevOps practices become essential. The synergy of development and operations accelerates the development cycle, leading to faster time-to-market and increased customer satisfaction.

It also facilitates continuous integration and delivery, enabling frequent updates and enhancements to meet market demands.

In conclusion, the startup journey is a multifaceted expedition, with each phase requiring specific tools and strategies.

Cloud computing and DevOps, hand in hand, provide the adaptability, efficiency, and innovation needed for startups to thrive and succeed in a constantly changing business landscape. Their synergy is the recipe for a prosperous and enduring entrepreneurial voyage.

Serverless Security and Security Computing#

Many cloud providers now offer secure cloud services using special security tools or structures. According to LogicMonitor, there might be a decrease of 10% to 27% in on-premises applications by 2020. However, cloud-based serverless applications like Microsoft Azure, AWS Lambda, and Google Cloud are expected to grow by 41%. The shift from in-house systems to serverless cloud computing has been a popular trend in technology.

Security risks will always exist no matter how well a program or online application is made. It doesn't matter how securely it stores crucial information. You're in the right place if you're using a serverless system or interested in learning how to keep serverless cloud computing safe.

What is Serverless Computing?#

The idea of serverless computing is about making things easier for application developers. Instead of managing servers, they can just focus on writing and deploying their code as functions. This kind of cloud computing called Function-as-a-Service (FaaS), removes the need for programmers to deal with the complicated server stuff. They can simply concentrate on their code without worrying about the technical details of building and deploying it.

In serverless architectures, the cloud provider handles setting up, taking care of, and adjusting the server infrastructure according to the code's needs. Once the applications are deployed, they can automatically grow or shrink depending on how much they're needed. Organizations can use special tools and techniques called DevOps automation to make delivering software faster, cheaper, and better. Many organizations also use tools like Docker and Kubernetes to automate their DevOps tasks. It's all about making things easier and smoother.

Software designed specifically for managing and coordinating containers and their contents is called container management software.

In serverless models, organizations can concentrate on what they're good at without considering the technical stuff in the background. But it's important to remember that some security things still need attention and care. Safety is always essential, even when things seem more straightforward. Here are some reasons why you need to protect your serverless architecture or model:

• In the serverless paradigm, detection system software (IDS tools) and firewalls are not used.
• The design does not feature any protection techniques or instrumentation agents, such as protocols for file transmission or critical authentication.

Even if serverless architecture is even more compact than microservices, organizations still need to take measures to protect their systems.

What Is Serverless Security?#

In the past, many applications had problems with security. Criminals could do things like to steal sensitive information or cause trouble with the code. To stop these problems, people used special tools like firewalls and intrusion prevention systems.

But with serverless architecture, those tools might work better. Instead, serverless uses different techniques to keep things safe, like protecting the code and giving permissions. Developers can add extra protection to their applications to ensure everything stays secure. It's all about following the proper rules to keep things safe.

This way, developers have more control and can prevent security problems. Using container management software can make serverless applications even more secure.

Best Practices for Serverless Security#

1. Use API Gateways as Security Buffers#

To keep serverless applications safe, you can use unique gateways that protect against data problems. These gateways act like a shield, keeping the applications secure when getting data from different places. Another way to make things even safer is using a unique reverse proxy tool. It adds extra protection and makes it harder for bad people to cause trouble.

As part of DevOps automation practices, it is essential to leverage the security benefits provided by HTTP endpoints. HTTP endpoints offer built-in security protocols that encrypt data and manage keys. To protect data during software development and deployment, use DevOps automation and secure HTTP endpoints.

2. Data Separation and Secure Configurations#

Preventative measures against DoW attacks include:

• Code scanning.
• Isolating commands and queries.
• Discovering exposed secret keys or unlinked triggers.
• Implementing those measures by the CSP's recommended practices for serverless apps.

It is also essential to reduce function timeouts to a minimum to prevent execution calls from being stalled by denial-of-service (DoS) attacks.

3. Dealing with Insecure Authentication#

Multiple specialized access control and authentication services should be implemented to reduce the danger of corrupted authentication. The CSP's Access control options include OAuth, OIDC, SAML, OpenID Connect, and multi-factor authentication (MFA) to make authentication more challenging to overcome. In addition, you may make it difficult for hackers to break your passwords by enforcing individualized regulations and criteria for the length and complexity of your passwords. Boosting password security is critical, and one way to achieve this is by using continuous management software that enforces unique restrictions and requirements for password length and complexity.

4. Serverless Monitoring/Logging#

Using a unique technology to see what's happening inside your serverless application is essential. There could be risks if you only rely on the cloud provider's logging and monitoring features. The information about how your application works might be exposed, which could be better. It could be a way for bad people to attack your application. So, having a sound monitoring system is essential to keep an eye on things and stay safe.

5. Minimize Privileges#

To keep things safe, it's a good idea to separate functions and control what they can do using IAM roles. This means giving each position only the permissions it needs to do its job. By doing this, we can ensure that programs only have the access they need and reduce the chances of any problems happening.

6. Independent Application Development Configuration#

To ensure continuous software development, integration, and deployment (CI/CD), developers can divide the process into stages: staging, development, and production. By doing this, they can prioritize effective vulnerability management at every step before moving on to the next version of the code. This approach helps developers stay ahead of attackers by patching vulnerabilities, protecting updates, and continuously testing and improving the program.

Effective continuous deployment software practices contribute to a streamlined and secure software development lifecycle.

Conclusion#

Serverless architecture is a new way of developing applications. It has its benefits and challenges. But it also brings some significant advantages, like making it easier to handle infrastructure, being more productive, and scaling things efficiently. However, it's essential to be careful when managing the application's infrastructure. It is because this approach focuses more on improving the infrastructure than just writing good code. So, we must pay attention to both aspects to make things work smoothly.

When we want to keep serverless applications safe, we must be careful and do things correctly. The good thing is that cloud providers now have perfect security features, mainly because more and more businesses are using serverless architecture. It's all about being smart and using our great security options. Organizations can enhance their serverless security practices by combining the power of DevOps automation and continuous deployment software.

Experience the next level of cloud security with Nife! Contact us today to explore our offerings and fortify your cloud infrastructure with Nife.

Lately, there's been a lot of talk about "serverless computing" in the computer industry. It's a cool new concept. Through this, programmers focus on coding without worrying about the technical stuff underneath. It's great for businesses and developers. It can adapt to their needs and save money. Research says the serverless computing industry will grow significantly, with a projected value of \$36.84 billion by 2028.

In this article, we'll explain what serverless computing is, talk about its benefits, and see how it can change software development in the future. It's a fun and exciting topic to explore!

Understanding the term “Serverless Computing”#

Serverless computing is a way of developing and deploying applications that eliminate the need for developers to worry about server management. In traditional cloud computing, developers must manage their applications' server infrastructure. But in serverless computing, the cloud management platform handles managing the infrastructure. This allows developers to focus on creating and launching their software without the burden of server setup and maintenance.

In a similar vein, Kubernetes simplifies robust distributed applications by combining modern container technology and Kubernetes. Kubernetes enables autoscaling, automatic failover, and resource management automation through deployment patterns and APIs. Though some infrastructure management is necessary, combining "serverless" and "Kubernetes" may seem counterintuitive.

Critical Components of Serverless Computing#

Several fundamental components of serverless architecture provide a streamlined and scalable environment for app development and deployment. Let's analyze these vital components in further detail:

Function as a Service (FaaS):#

Functions as a Service is the basic concept behind serverless cloud computing. FaaS allows its users to generate functions that may be executed independently and carry out specific tasks or procedures. The cloud service takes care of processing and scaling for these procedures when triggered by events or requests. With FaaS, Cloud DevOps don't need to worry about the underlying infrastructure, so they can concentrate on building code for particular tasks.

Event Sources and Triggers:#

In serverless computing, events are like triggers that make functions run. Many different things can cause events, like when people do something, when files are uploaded, or when databases are updated. These events can make tasks happen when certain conditions are met. It's like having a signal that tells the functions to start working.

Event-driven architecture is a big part of serverless computing. It helps create applications that can adapt and grow easily. They can quickly respond to what's going on around them. It's like having a super-intelligent system that knows exactly when to do things.

Cloud Provider Infrastructure:#

Cloud management platforms are responsible for maintaining the necessary hardware to make serverless computing work. The cloud service handles server management, network configuration, and resource allocation so that developers may concentrate on creating their applications. Each cloud management platform has a unique architecture and set of services regarding serverless computing. This comprises the compute operating configurations, the automated scaling techniques, and the event handling mechanisms.

Function Runtime Environment:#

The function runtime environment is where the cloud management platform executes serverless functions. It is equipped with all the necessary tools, files, and references to ensure the smooth running of the function code. The running context supports many programming languages, allowing developers to create methods in the language of their choice. A cloud service handles the whole lifecycle of these operational settings. This involves increasing capacity and adding more resources as required.

Developer Tools and SDKs:#

Cloud providers are like helpful friends to developers when making and launching serverless applications. They offer unique tools and software development kits (SDKs) that make things easier. With these tools, developers can test their code, fix issues, automate the release process, and track how things are going. It's like having a magic toolbox that helps them do their work smoothly.

SDKs are like secret codes that help developers work with the serverless platform. They make it easy to use its services and APIs. They also help developers connect with other services, manage authentication, and access different resources in the cloud. It's like having a unique guidebook that shows them the way.

Service Integration:#

Serverless computing platforms offer a plethora of pre-built features and interfaces that developers can take advantage of. These include databases, storage systems, message queues, authorization and security systems, machine learning services, etc. Leveraging these services eliminates the need to build everything from scratch when implementing new application features. By utilizing these pre-existing services, Cloud DevOps can harness their capabilities to enhance the core business operations of their applications.

Monitoring and Logging:#

Cloud DevOps may monitor the operation and behavior of their functions using the built-in monitoring and logging features of serverless platforms. Processing times, resource consumption, error rates, and other metrics are all easily accessible with the help of these instruments. Cloud DevOps may identify slow spots by monitoring and recording data, enhancing their operations, and addressing issues. These systems often integrate with third-party monitoring and logging services to round out the picture of an application's health and performance.

With this knowledge, developers can harness the potential of serverless architecture to create applications that are flexible, cost-effective, and responsive to changes. Each component contributes to the overall efficiency and scalability of the architecture, simplifies the development process, and ensures the proper execution and management of serverless functions.

Advantages of Serverless Computing#

There are several advantages to serverless computing for organizations and developers.

Reduced Infrastructure Management:#

Serverless architecture or computing eliminates the need for developers to handle servers, storage, and networking.

Reduced Costs:#

Serverless computing reduces expenses by charging customers only for the resources they consume. Companies may be able to save a lot of money.

Improved Scalability:#

With serverless computing, applications may grow autonomously in response to user demand. This can enhance performance and mitigate downtime during high use.

Faster Time to Market:#

Serverless computing accelerates time to market. It allows developers to focus on their application's core functionality.

Disadvantages of Serverless Computing#

There are several downsides to serverless computing despite its advantages.

Data Shipping Architecture:#

The Data Shipping Architecture is different from how serverless computing usually works. In serverless computing, we try to keep computations and data together in one place. But with the Data Shipping Architecture, we don't do that. Because serverless computing is unpredictable, it's not always possible to have computations and data in the same location.

This means that much data must be moved over the network, which can slow down the program. It's like constantly transferring data between different places, which can affect the program's speed.

No Concept of State:#

Since there is no "state" in serverless computing, data accessible to multiple processes must be kept in some central location. However, this causes a large number of database calls. This can harm performance. Basic memory read and write operations are transformed into database I/O operations.

Limited Execution Duration:#

Currently, there is a fixed length limit for serverless operations. Although this is not an issue at the core of serverless computing, it does limit the types of applications that may be run using a serverless architecture.

Conclusion#

Serverless computing saves money, so it will keep growing. That's why we must change how we develop applications and products to include serverless computing. We should consider how to use it to make applications work better, cost less, and handle more users. When we plan, we need to think about the good and bad parts of serverless computing. If we use serverless computing, we can stay up-to-date with technology and strengthen our market position. You can also streamline distributed applications with Serverless Kubernetes. Serverless Kubernetes is a powerful combination of container technology and Kubernetes.

You can also experience the power of cloud hosting with Nife to upgrade your website today.

The concept of Serverless Architecture is becoming popular among businesses of all sizes. In traditional practices, developers are responsible for maintaining servers and managing the load which is very time-consuming. In cloud computing for developers, the serverless architecture allows developers to focus on deploying applications and writing code rather than worrying about server management.

Serverless architecture works on the principle of Function as a Service (FaaS) where each function is responsible for a specific task. The real magic happens when this architecture is combined with cloud services like AWS, Google Cloud, and Microsoft Azure.

In this article, every aspect of building a serverless architecture will be covered. From designing functions to deploying them, from triggering and scaling to integrating with other cloud services, we will cover it all.

Understanding Serverless Architecture | Cloud Computing for Developers#

Serverless architecture refers to the utilization of cloud infrastructure services rather than physical infrastructure. It revolves around focusing on writing code and deploying functions that perform specific tasks. These tasks include automating scaling and event-driven executions.

Cloud computing for developers has many benefits. Benefits of cloud infrastructure services include reduced operation overhead, cost efficiency, flexibility, low latency, and seamless scalability. Serverless architecture is used for cloud-based web development, fast data processing, real-time streaming, and IoT.

Choosing the Right Cloud Provider#

The very first step towards building a serverless architecture is to choose a suitable cloud infrastructure service for your operations. In this critical step, you will encounter three giants: AWS Lambda, Azure Functions, and Google Cloud Functions. Each of these cloud infrastructure services has a unique set of features. You can choose one based on your needs. You should consider the following factors when choosing a cloud platform.

Pricing Model: First of all you should decide whether you want a "pay as you go" model or a fixed subscription plan. AWS Lambda and Azure Functions have a "pay as you go" model while Google Cloud Functions has a subscription plan. Choose the service based on your budget.

Performance: Evaluate the performance of each provider. AWS Lambda boasts a quick start-up time, Google Cloud Functions is best for event-based executions, and Azure can handle large-scale applications with ease. Understand your needs and select according to your requirements.

Ecosystem Maturity: You should also consider the availability of other features. For example, AWS Lambda has its ecosystem of services while Google Cloud Functions has its own. Choose the provider based on your compatibility with the overall model.

Lastly, you should also consider vendor lock-in and compatibility with new technologies like Artificial Intelligence (AI) and Machine Learning (ML).

The process of choosing a cloud provider becomes easier with Nife, a cloud computing platform that provides flexible pricing, high performance, security, and a mature ecosystem. It eliminates the hassle of managing different provider-specific interfaces and allows developers to focus on building their applications without worrying about the underlying infrastructure.

Designing Functions for Serverless Architecture#

Designing functions for serverless architecture requires careful consideration of responsibilities. Each function should be designed to perform an independent task. Complex applications should be divided into smaller ones for better management. Independent functions enable better scalability and maintainability. Here are two essential practices for designing functions for serverless architecture.

Single Responsibility Principle: Each function should be responsible for a single task. Complex functions should be divided into smaller focused functions. This practice keeps the codebase clean, easier to maintain, and makes debugging easier.#

Stateless Functions: In serverless architecture functions should not rely on stored data or previous state. Instead, data should be passed as input parameters from external sources like APIs. This allows for better scalability options.#

By following these principles you can get many benefits that include improved cloud infrastructure development, agility, reduced operational overhead, and scalability. You can also move your application to Nife, a cloud computing platform that simplifies function design in cloud infrastructure development.

With Nife, developers can seamlessly integrate and manage their function designs. Nife provides a user-friendly environment for developers to deploy their cloud applications.

Developing and Deploying Functions#

Developing and deploying functions in a serverless architecture is a streamlined process. Have a look at the step-by-step process, from setting up a cloud infrastructure development environment to packing and deploying your function to the cloud.

Setting up a Cloud Infrastructure Development Environment#

Firstly you need to create your cloud infrastructure development environment to get started. Most cloud services provide the necessary tools and services to help you get started. You can install command line interfaces (CLIs) and development kits. You can then start creating, testing, and deploying functions.

Writing Code:#

Cloud platforms support different languages like Python, Java, C++, and more. Select the language of your choice on your cloud platform and get started with writing your function.

Packing and Deploying Functions:#

In cloud-based web development, it is crucial to test every function with different input scenarios. Validate the result from each test to catch any errors. Once the testing phase is completed, it's time for packing and deployment. Utilize tools and other resources provided by your chosen cloud provider to deploy the functions.

You can also use version control and CI/CD to automate your deployment and development process.

Integrating with Other Cloud Services#

In serverless architecture, you can seamlessly integrate with other services provided by the provider of your choice. Cloud computing for developers provides different services that include databases, storage, authentication, and many more.

By integrating with all these services you can store and process data, manage files, send notifications, enhance security, and increase efficiency. Integration can also elevate your cloud-based web development projects so you can create interconnected applications.

Take advantage of Nife's comprehensive cloud computing platform for developers, where you can seamlessly deploy cloud services and unleash the true potential of your cloud-based web development projects.

Experience the power of cloud computing for developers with Nife and revolutionize the way you build, manage, scale, and deploy applications.

Build Your Serverless Architecture with Nife Today

Conclusion:#

In conclusion, serverless architecture has revolutionized the development process in cloud computing for developers. By leveraging cloud services like AWS Lambda, Azure Functions, or Google Cloud Functions, developers can build scalable and cost-effective applications.

Developers can also leverage Nife, a cloud computing platform, that offers a comprehensive solution for developers seeking to embrace serverless architecture. With Nife, developers can streamline deployment and monitor services efficiently. With Nife build, deploy, manage, and scale applications securely and efficiently.

In today's fast-paced digital landscape, startups need a cloud computing platform to gain a competitive edge. By leveraging scalable infrastructure, cost-effectiveness, and simplified operations, startups can focus on innovation, agility, and rapid growth while leaving the complexities of IT management to the cloud.

Cloud computing is becoming a powerful tool for startups and small to medium-sized enterprises (SMEs). With the potential to grow quickly, cut down fees, and get entry to advanced technologies, cloud computing has transformed how groups function, allowing them to innovate quicker and stay ahead of the opposition.

In this guide, you will find how cloud computing has become a game-changer for startups and SMEs and how they might utilize it for aggressive benefit.

Cloud Computing Platform for Startups and SMEs#

What actually Cloud Computing is?#

With the use of this technology, users may access computer resources like storage and processing power whenever they need them without having to take any direct physical control over the system.

Rather than investing in costly hardware and software programs, businesses can get the right of entry to those resources on-call, paying only for what they use.

Cloud computing and innovations offer your commercial enterprise more flexibility. You can scale resources and storage quickly to meet enterprise demands while not having to spend money on physical infrastructure. Companies want to avoid paying for or building the infrastructure to assist their highest load ranges. Likewise, they can quickly diminish if sources aren't being used.

Various Benefits of Utilizing Cloud Computing Platforms for Startups and SMEs#

1. Scalability#

Cloud computing's scalability is a boon to startups that quickly outgrow their initial funding. As the company expands, the systems may easily pick up additional functions.

Businesses can save costs by paying only for the resources they require, on an as-needed basis, instead of paying for unused resources throughout the year.

This is particularly crucial for startups and SMEs that may encounter sudden surges in demand.

In this way, cloud computing and innovations support the advancement and growth of startups.

2. Cost-effective support#

Instead of spending money on permanent or temporary support staff, you may use cloud technology to access a support system anywhere. Using the cloud for customer service and technical issues may help startups save money by eliminating the need to hire dedicated staff members to handle these tasks.

As a marketing tool, several cloud services provide free tutorials to potential customers. You may also find cloud assistance options that need a monthly membership cost in exchange for access. Businesses may choose accordingly keeping budget and profit in mind as various services are accessible in the cloud.

3. Advancement in Technologies#

Cloud computing allows companies to access advanced technologies that would otherwise be out of reach.

Cloud computing is considered a game changer for companies to access and utilize advanced technology. By leveraging cloud computing, startups, and SMEs can access these technologies without investing in expensive hardware or hiring a team of experts. It will be useful for the growth of your company.

While cloud technology offers many benefits for businesses worldwide, it's worth noting that region-specific cloud platforms cater to the unique needs of businesses in certain areas. For example, the Middle East has seen significant growth in cloud adoption in recent years. There are now several cloud platforms for the Middle East designed specifically for regional businesses.

These platforms offer features and services tailored to the Middle Eastern market, such as localized data storage, multi-lingual support, and compliance with local regulations. By leveraging a cloud platform for the Middle East, businesses in the region can benefit from the same advantages of cloud technology, such as cost savings, scalability, and flexibility, while meeting their specific needs and requirements.

4. Capital preservation#

Cloud management platforms are a critical component of cloud computing that can help businesses achieve greater efficiency and cost savings. Organizations can avoid the upfront costs of assembling expensive equipment and software by leveraging cloud management platforms. These platforms provide various tools and services that enable businesses to manage their cloud infrastructure and applications more effectively.

5. Cloud technology connectivity#

Working with a cloud technology provider will allow your firm to set up Internet connections quickly. Regarding internet connectivity, companies don't have to worry about location or weather since they know it's always there if they need it. So that companies are free to focus on other aspects of the business, seasoned cloud providers assist organizations in choosing the best connection options and systems for their needs.

Businesses may use wired or wireless connectivity if they have the right infrastructure.

Companies may save time and resources by not having to investigate connection choices independently. In addition to providing reliable internet connectivity, cloud technology providers offer a range of cloud application development services to help businesses build and deploy custom applications quickly and efficiently.

6. Lower infrastructure and space expenses#

Cloud technology offers several advantages for new businesses, such as saving space and money by eliminating the need to maintain hardware and storage space for files and media. This allows entrepreneurs to focus more on launching and developing their businesses, which are critical tasks that require their attention. Traditional servers and cooling systems can be expensive and take up significant space, but cloud technology allows businesses to avoid these costs and allocate their budgets toward other pressing needs.

Moreover, cloud technology also saves time by providing easy access to data by connecting to the internet from anywhere in the world. Collaboration is crucial for achieving initial success for new teams, and having cloud systems in place allows for seamless collaboration and data sharing.

With cloud computing power, even low-end laptops can access and use cloud resources effectively, enabling businesses to leverage the full benefits of cloud technology without the need for expensive hardware upgrades.

How Startups and SMEs Can Leverage Cloud Computing Platforms for Competitive Advantage#

• Rapid Innovation

Cloud computing and innovations permit startups and SMEs to innovate quicker, decreasing the time and resources required to broaden and install new products and services.

By accessing advanced technologies and scaling rapidly, businesses can quickly bring new ideas to market, allowing them to stay ahead of the competition.

• Improved Collaboration

Cloud computing also facilitates collaboration amongst group contributors, irrespective of their vicinity. By leveraging Cloud management platforms, businesses can enhance verbal exchange, streamline workflows, and have beneficial productiveness.

• Enhanced Customer Experience

By utilizing cloud application development services, businesses can enhance the client experience by delivering faster and more reliable services. These services take advantage of the scalability and flexibility of cloud technology, allowing for the creation and deployment of applications that can easily adapt to changing customer requirements and market conditions.

• Data Insights

With cloud computing and innovation, businesses can access advanced data analytics tools to make informed decisions. This enables startups and SMEs to acquire crucial insights into customer behavior, identify emerging trends, and optimize their operations for enhanced efficiency and profitability.

Conclusion#

The use of cloud computing platforms has revolutionized the methods used by startups and SMEs. The invention has sped up, expenses have been cut, and more resources have been made available, all because of technological advancements.

Businesses may improve their standing in the market and give customers a better experience by using cloud computing's many advantages. The advantages of cloud computing are projected to continue to be utilized by nascent and growing businesses as the industry matures.

Looking for a cost-effective and efficient web hosting solution? Choose Nife's cloud hosting services. Unlock the full potential of your website with Nife's cutting-edge cloud hosting platform.

Adopting a Cloud Platform Solution refers to implementing a comprehensive infrastructure and service framework that leverages cloud technologies. It enables organizations to harness the benefits of scalability, flexibility, cost optimization, and streamlined operations, empowering them to innovate and thrive in the digital landscape.

In recent years, developers have increasingly opted for deploying microservices-based applications in the cloud instead of traditional monolithic applications. Microservices architecture provides better scalability, flexibility, and fault tolerance.

Microservices architecture in the cloud allows developers to break complex applications into small, independently scalable services, providing more agility and faster response times.

In this blog, we'll explore the best practices for deploying microservices in the cloud, covering aspects like service discovery, load balancing, scaling, and more.

We will also delve into cloud platforms suited for the Middle East to address the region's unique needs. This blog will help you deploy robust and scalable microservices. Read till the end for valuable insights.

Best Practices for Deploying Microservices in the Cloud#

Service Discovery#

Imagine a big city with all similar-looking buildings housing thousands of businesses without any brand boards. Without a map or reliable directory, it would be impossible for you to find the service you are looking for. In the same way, service discovery is crucial for microservices in the cloud. Service discovery connects different microservices to work together seamlessly.

Service Discovery Best Practices#

There are different methods of navigating a business in a big city. Likewise, service discovery has different methods to navigate and connect microservices.

DNS-based Service Directory#

In this method, service names are mapped to their IP addresses. Services can query and find other services, similar to an online phone directory.

Client-side Service Directory#

In this method, each available service registers itself with the service discovery server. Clients can easily find and communicate with the required service.

Comparison of Cloud Platforms#

Here is a comparison of cloud application development services. Google Cloud Platform has its own service discovery service called Cloud DNS. Cloud DNS creates DNS records and simplifies deploying microservices in Google Cloud. On the other hand, Amazon offers Route 53, which creates DNS records and routes microservices, making it easier to deploy Java microservices in AWS.

Nife is another cloud platform providing a seamless service discovery solution that integrates with both Google Cloud and AWS. Nife's service discovery module automatically registers and updates microservices information in the service registry, facilitating communication between microservices.

Load Balancing#

Load balancing is another critical aspect of microservices architecture. With multiple microservices applications working independently with varying loads, managing these microservices efficiently is essential for a streamlined workflow. Load balancing acts as a traffic controller, distributing incoming requests to all available service instances.

Load Balancing Best Practices#

Just as there are different methods for controlling traffic, there are various practices for load balancing in a microservices architecture.

Round Robin#

In this load-balancing method, requests are distributed among services in a rotating fashion. Services are queued, and each new request is transferred to service instances following their position in the queue.

Weighted Round Robin#

In this method, each service is assigned a weight, and requests are served proportionally among all services based on their weight.

Least Connections#

In this load-balancing method, requests are directed according to the load on service instances. Requests are sent to services handling the least amount of load.

Comparison of Cloud Platforms#

Here is a comparison of two renowned cloud application development services. Google Cloud Platform offers load balancing services including HTTP(S) Load Balancing, TCP/UDP Load Balancing, and Internal Load Balancing, simplifying the deployment of microservices in Google Cloud. In contrast, Amazon provides Elastic Load Balancing (ELB), offering various load balancing options to handle load efficiently and making it easier to deploy Java microservices in AWS.

Nife is another cloud platform offering comprehensive load-balancing options. It integrates with both Google Cloud and AWS, leveraging effective load-balancing techniques for microservices architecture to ensure an efficient and streamlined workflow.

Scaling#

Scaling is another crucial aspect of microservices deployment, especially for cloud platforms in the Middle East region. Microservices break down complex applications into smaller, manageable services. The workload on each of these services can increase dramatically with higher demand. To manage these loads, a scalable infrastructure is essential. Here are some primary scaling approaches:

Horizontal Scaling#

In this practice, additional microservices are added to handle increasing load.

Vertical Scaling#

In this practice, the resources of microservices are increased to handle growing demand.

Nife: Simplifying Microservices Deployment in the Cloud | Cloud Platform Solution#

Developers are always seeking efficient and streamlined solutions for deploying microservices. That's where Nife comes in, a leading platform for cloud application development services. It simplifies the deployment of microservices and provides a wide range of features tailored to developers' needs. With Nife, you can enjoy a unified experience, whether deploying microservices in Google Cloud or Java microservices in AWS.

By leveraging Nife's Cloud Platform for the Middle East, developers can address the unique needs of that region. Nife's strength lies in its seamless integration of service discovery, load balancing, and scaling capabilities. Nife provides a service discovery mechanism to enable communication between microservices, automatic load balancing to distribute traffic across services, and automatic scaling to ensure optimal resource utilization based on demand.

To experience the power of Nife and simplify your microservices deployment, visit nife.io.

Discover Nife's Cloud Platform for Efficient Deployment of Microservices

Conclusion#

Are you looking to deploy microservices in the cloud? Discover the best practices for developers in this comprehensive article. Explore how to deploy microservices in Google Cloud and AWS, utilizing their cloud application development services.

Learn about service discovery, load balancing, and scaling techniques to ensure seamless communication and optimal resource utilization.

Discover how the Cloud Platform for the Middle East caters to developers' unique needs in the region. Experience the power of Nife's cloud platform solution, simplifying microservices deployments and empowering developers to build exceptional applications. Revolutionize your cloud journey today with Nife's comprehensive suite of tools and services.

Computer vision is a branch of AI(Artificial Intelligence) that deals with visual data. The role of computer vision technology is to improve the way images and videos are interpreted by machines. It uses mathematics and analysis to extract important information from visual data.

There have been several innovations in computer vision technology in recent years. These innovations have significantly improved the speed and accuracy of AI.

Computer vision is a very important part of AI. Computer vision has many important AI applications like self-driving, facial recognition, medical imaging, etc. It also has many applications in different fields including security, entertainment, surveillance, and healthcare. Computer vision is enabling machines to become more intelligent with visual data.

All these innovations in computer vision make AI more human-like.

Computer Vision Technology#

In this article, we'll discuss recent innovations in computer vision technology that have improved AI. We will discuss advancements like object detection, pose estimation, semantic segmentation, and video analysis. We will also explore some applications and limitations of computer vision.

Image Recognition:#

Image recognition is a very important task in computer vision. It has many practical applications including object detection, facial recognition, image segmentation, etc.

In recent years there have been many innovations in image recognition that have led to improved AI. All the advancements in image recognition we see today have been possible due to deep learning, CNNs, Transfer technology, and GANs. We will explore each of these in detail.

Deep Learning#

Deep Learning is a branch of machine learning that has completely changed image recognition technology. It involves training models with a vast amount of complex data from images.

It uses mathematical models and algorithms to identify patterns from visual input. Deep learning has advanced image recognition technology so much that it can make informed decisions without a human host.

Convolutional Neural Networks (CNNs)#

Convolutional neural networks (CNNs) are another innovation in image recognition that has many useful applications. It consists of multiple layers that include a convolution layer, pool layer, and fully connected layer. The purpose of CNN is to identify, process, and classify visual data.

All of this is done through these three layers. The convolution layer identifies the input and extracts useful information. Then the pooling layer compresses it. Lastly, a fully connected layer classifies the information.

Transfer Learning#

Transfer learning means transferring knowledge of a pre-existing model. It is a technique used to save time and resources. In this technique instead of training an AI model with deep learning, a pre-existing model trained with vast amounts of data in the same field is used.

It gives many advantages like accurately saved costs and efficiency.

Generative Adversarial Network (GAN)#

GAN is another innovation in image recognition. It consists of two neural networks that are constantly in battle. One neural network produces data (images) and the other has to differentiate it as real or fake.

As the other network identifies images to be fake, the first network creates a more realistic image that is more difficult to identify. This cycle goes on and on improving results further.

Object Detection:#

Object detection is also a very crucial task in computer vision. It has many applications including self-driving vehicles, security, surveillance, and robotics. It involves detecting objects in visual data.

In recent years many innovations have been made in object detection. There are tons of object-detecting models. Each model offers a unique set of advantages.

Have a look at some of them.

Faster R-CNN#

Faster R-CNN (Region-based Convolutional Neural Network) is an object detection model that consists of two parts: Regional proposal network (RPN) and fast R-CNN. The role of RPN is to analyze data in images and videos to identify objects. It identifies the likelihood of an object being present in a certain area of the picture or video. It then sends a proposal to fast R-CNN which then provides the final result.

YOLO#

YOLO (You Only Look Once) is another popular and innovative object detection model. It has taken object detection to the next level by providing real-time accurate results. It is being used in Self-driving vehicles due to its speed. It uses a grid model for identifying objects. The whole area of the image/video is divided into grids. The AI model then analyzes each cell to predict objects.

Semantic Segmentation:#

Semantic segmentation is an important innovation in Computer vision. It is a technique in computer vision that involves labeling each pixel of an image/video to identify objects.

This technique is very useful in object detection and has many important applications. Some popular approaches to semantic segmentation are Fully Convolutional Networks (FCNs), U-Net, and Mask R-CNN.

Fully Convolutional Networks (FCNs)#

Fully convolutional networks (FCNs) are a popular approach used in semantic segmentation. They consist of a neural network that can make pixel-wise predictions in images and videos.

FCN takes input data and extracts different features and information from that data. Then that image is compressed and every pixel is classified. This technique is very useful in semantic segmentation and has applications in robotics and self-driving vehicles. One downside of this technique is that it requires a lot of training.

U-Net#

U-Net is another popular approach to semantic segmentation. It is popular in the medical field. In this architecture, two parts of U- Net one contracting and the other expanding are used for semantic segmentation.

Contracting is used to extract information from images/videos taken through U shaped tube. These images/videos are then processed to classify pixels and detect objects in that image/video. This technique is particularly useful for tissue imaging.

Mask R-CNN#

Mask R-CNN is another popular approach to semantic segmentation. It is a more useful version of Faster R-CNN which we discussed earlier in the Object detection section. It has all the features of faster R-CNN except it can segment the image and classify each pixel. It can detect objects in an image and segment them at the same time.

Pose Estimation:#

Pose estimation is another part of computer vision. It is useful for detecting objects and people in an image with great accuracy and speed. It has applications in AR (Augmented Reality), Movement Capture, and Robotics. In recent years there have been many innovations in pose estimation.

Here are some of the innovative approaches in pose estimation in recent years.

Open Pose#

The open pose is a popular approach to pose estimation. It uses CNN(Convolutional Neural Networks) to detect a human body. It identifies 135 features of the human body to detect movement. It can detect limbs and facial features, and can accurately track body movements.

Mask R-CNN#

Mask R-CNN can also be used for pose estimation. As we have discussed earlier object detection and semantic segmentation. it can extract features and predict objects in an object. It can also be used to segment different human body parts.

Video Analysis:#

Video Analysis is another important innovation in computer vision. It involves interpreting and processing data from videos. Video analysis consists of many techniques that include. Some of these techniques are video captioning, motion detection, and tracking.

Motion Detection#

Motion detection is an important task in video analysis. It involves detecting and tracking objects in a video. Motion detecting algorithm subtracts the background from a frame to identify an object then each frame is compared for tracking movements.

Video Captioning#

It involves generating natural text in a video. It is useful for hearing-impaired people. It has many applications in the entertainment and sports industry. It usually involves combining visuals from video and text from language models to give captions.

Tracking#

Tracking is a feature in video analysis that involves following the movement of a target object. Tracking has a wide range of applications in the sports and entertainment industry. The target object can be a human or any sports gear. For example, some common target objects are the tennis ball, hard ball, football, and baseball. Tracking is done by comparing consecutive frames for details.

Applications of Innovations in Computer Vision#

Innovations in computer vision have created a wide range of applications in different fields. Some of the industries are healthcare, self-driving vehicles, and surveillance and security.

Healthcare#

Computer vision is being used in healthcare for the diagnosis and treatment of patients. It is being used to analyze CT scans, MRIs, and X-rays. Computer vision technology is being used to diagnose cancer, heart diseases, Alzheimer's, respiratory diseases, and many other hidden diseases. Computer vision is also being used for remote diagnoses and treatments. It has greatly improved efficiency in the medical field.

Self Driving Vehicles#

Innovation in Computer vision has enabled the automotive industry to improve its self-driving features significantly. Computer vision-based algorithms are used in car sensors to detect objects by vehicles. It has also enabled these vehicles to make real-time decisions based on information from sensors.

Security and Surveillance#

Another application of computer vision is security and surveillance. Computer vision is being used in cameras in public places for security. Facial recognition and object detection are being used for threat detection.

Challenges and Limitations#

No doubt innovation in computer vision has improved AI significantly. It has also raised some challenges and concerns about privacy, ethics, and Interoperability.

Data Privacy#

AI trains on vast amounts of visual data for improved decision-making. This training data is usually taken from surveillance cameras which raises huge privacy concerns. There are also concerns about the storage and collection of users' data because there is no way of knowing which information is being accessed about a person.

Ethics#

Ethics is also becoming a big concern as computer vision is integrated with AI. Pictures and videos of individuals are being used without their permission which goes against ethics. Moreover, it has been seen that some AI models discriminate against people of color. All these ethical concerns need to be addressed properly by taking necessary actions.

Interpretability#

Another important concern of computer vision is interpretability. As AI models continue to evolve, it becomes increasingly difficult to understand how they make decisions. It becomes difficult to interpret if decisions are made based on facts or biases. A new set of tools are required to address this issue.

Conclusion:#

Computer vision is an important field of AI. In recent years there have been many innovations in computer vision that have improved AI algorithms and models significantly. These innovations include image recognition, object detection, semantic segmentation, and video analysis. Due to all these innovations computer vision has become an important part of different fields.

Some of these fields are healthcare, robotics, self-driving vehicles, and security and surveillance. There are also some challenges and concerns which need to be addressed.

CV APIs are growing in popularity because they let developers build smart apps that read, recognize, and analyze visual data from photos and videos. As a consequence, the CV API market is likely to expand rapidly in the coming years to meet the rising demand for these sophisticated applications across a wide range of sectors.

According to MarketsandMarkets, the computer vision market will grow from $10.9 billion in 2019 to $17.4 billion in 2024, with a compound annual growth rate (CAGR) of 7.8 percent. The market for CV APIs is projected to be worth billions of dollars by 2030, continuing the upward trend seen since 2024.

What is Computer Vision?#

Computer Vision is a branch of artificial intelligence (AI) that aims to offer computers the same visual perception and understanding capabilities as humans. Computer Vision algorithms use machine learning and other cutting-edge methods to analyze and interpret visual input. These algorithms can recognize patterns, recognize features, and find anomalies by learning from large picture and video datasets.

The significance of Computer Vision as an indispensable tool in various industries continues to grow, with its applications continually expanding.

Below given are just a few examples of where computer vision is employed today:

• Automatic inspection in manufacturing applications
• Assisting humans in identification tasks
• Controlling robots
• Detecting events
• Modeling objects and environments
• Navigation
• Medical image processing
• Autonomous vehicles
• Military applications

Benefits of Using Computer Vision in Cloud Computing#

Cloud computing is a common platform utilized for scalable and flexible image and video processing by implementing Computer Vision APIs.

Image and Video Recognition:#

Using cloud-based Computer Vision APIs enables the analysis and recognition of various elements within images and videos, such as objects, faces, emotions, and text.

Augmented Reality:#

The utilization of Computer Vision APIs in augmented reality (AR) applications allows for the detection and tracking of real-world objects, which in turn facilitates the overlaying of virtual content.

Security:#

Computer Vision APIs, such as face recognition and object detection, may be used in security systems to detect and identify potential security risks.

Real-time Analytics:#

Real-time data processing is made possible by cloud-based Computer Vision APIs, resulting in quicker decision-making and an enhanced user experience.

Automated Quality Control:#

The automation of quality control processes and the identification of product defects can be achieved in manufacturing and production settings by utilizing Computer Vision APIs.

Visual Search:#

Visual search capabilities can be facilitated through the application of Computer Vision APIs, allowing for the upload of images to search for products in e-commerce and other related applications.

Natural Language Processing:#

Computer Vision APIs can be utilized alongside natural language processing (NLP) to achieve a more comprehensive understanding of text and images.

Way of Using Computer Vision on the Edge#

Certain conditions must be satisfied before computer vision may be deployed on edge. Computer vision often necessitates an edge device with a GPU or VPU (visual processing unit). Edge devices are often associated with IoT (Internet of Things) devices. However, a computer vision edge device might be any device that can interpret visual input to assess its environment.

The next phase of migration is application configuration. Having the program downloaded directly from the Cloud is the quickest and easiest method.

Once the device has been successfully deployed, it may stop communicating with the Cloud and start analyzing its collected data. The smartphone is an excellent example of a device that satisfies the requirements and is likely already known to most people.

Mobile app developers have been inadvertently developing on the Edge to some extent. Building sophisticated computer vision applications on a smartphone has always been challenging, partly due to the rapid evolution of smartphone hardware.

For instance, in 2021, Qualcomm introduced the Snapdragon 888 5G mobile platform, which will fuel top-of-the-line Android phones. This processor delivers advanced photography features, such as capturing 120 images per second at a resolution of 12 megapixels.

This processor provides advanced photography features, such as capturing 120 images per second at a resolution of 12 megapixels.

An edge device's power enables developers to build complicated apps that can run directly on the smartphone.

Beyond mobile phones, there are more extensive uses for computer vision on Edge. Computer vision at the border is increasingly used in many industries, especially manufacturing. Engineers can monitor the whole process in near real-time due to software deployed at the Edge that allows them to do so.

Real-time examples#

The following is an overview of some of the most well-known Computer Vision APIs and the services they provide:

1. Google Cloud Vision API:#

Images and videos can be recognized, OCR can be read, faces can be identified, and objects can be tracked with the help of Google's Cloud Vision API, a robust Computer Vision API. It has a solid record for accuracy and dependability and provides an easy-to-use application programming interface.

2. Amazon Rekognition:#

Other well-known Computer Vision APIs include Amazon's Rekognition, which can recognize objects, faces, texts, and even famous people. It's renowned for being user-friendly and scalable and works well with other Amazon Web Services.

3. Microsoft Azure Computer Vision API:#

Image and video recognition, optical character recognition, and face recognition are just a few of the capabilities provided by the Microsoft Azure Computer Vision API. It has a stellar history of clarity and speed and supports many languages.

4. IBM Watson Visual Recognition:#

Image recognition, face recognition, and individualized training are only some of the capabilities the IBM Watson Visual Recognition API provides. It may be customized to meet specific needs and works seamlessly with other IBM Watson offerings.

5. Clarifai:#

In addition to custom training and object detection, image and video identification are just some of the popular Computer Vision API capabilities offered by Clarifai. It has a solid record for accuracy and simplicity, including an accessible application programming interface.

Conclusion#

In conclusion, AI's popularity has skyrocketed in the recent past. Companies that have already adopted AI are looking for ways to improve their processes, while those that still need to are likely to do so shortly.

Computer vision, a cutting-edge subfield of artificial intelligence, is more popular than ever and finds widespread application.

Licensees often fail to report payments accurately in their license agreements. This is sometimes the result of willful under-reporting, gaps created by obsolete or manual systems, or simple human mistakes.

Considering the potentially substantial financial advantages to a licensor's organization, every business that receives rights or license fees should consider implementing such a model. Running across a few myths concerning license compliance audits is possible when doing this review.

With the context provided here, you may firmly debunk these myths and decide whether a license compliance program is acceptable for your business.

Do Compliance Officers play an important role in your company?#

On September 26th, we celebrate Compliance Officer Day, a holiday first observed in the United States in 2016 but has since spread worldwide.

Compliance Officers still have a negative stereotype as "fun police," and we often see the compliance department as a "business prevention unit." This is far from reality; on the contrary, compliance professionals are essential to the success of every financial institution, like cloud computing in financial services.

Many people believe in myths related to compliance, and licenses for any financial sector whether it is related to cloud computing for banking or any other platform.

License Compliance Program Myths#

1. License compliance programs reduce profit because they are costly and inefficient, in fact, it's totally opposite#

It is believed that audits take too long and cost too much. Hence this misconception persists. Many often assume compliance is counterproductive to a company's bottom line since it only generates revenue after some time.

This is particularly true when considering the expense of staffing a dedicated compliance unit. Companies' bottom lines have benefited greatly from the efforts of licensors who have collaborated with experienced businesses to design a license compliance program targeted to their business model and clientele.

Cloud computing in the banking sector is increasing day by day in the finance industry. However, ensuring compliance and data security in cloud-based systems is crucial to maintaining a company's reputation and avoiding regulatory penalties.

First and foremost, a company's ability to attract new customers depends on its reputation and compliance with industry standards.

Second, it is statistically shown that companies with established compliance cultures earn fewer regulatory penalties and fines. The failure of several financial institutions to adequately monitor their communications has resulted in fines of over USD 200 million in recent months.

Finally, a skilled compliance officer knows how to assess existing procedures and improve them by filling in loopholes or removing unnecessary steps. This allows higher-ups to make more informed judgments.

Also, you can implement cloud computing in the banking sector to run the system smoothly.

2. Although achieving full compliance is no easy task, there are a few things that can be done to make the process easier for organizations.#

There is a common misconception that achieving compliance is impossible, full of repetitive checklists, demanding standards, and extensive safety measures. A company's compliance activities, however, might be greatly eased by the tools it employs.

Cloud computing in finance has enabled companies in the finance industry to simplify compliance procedures and proactively detect risks and problems through the use of SaaS providers and central repository systems.

Financial companies often pay the most in fines and penalties from authorities when they manually manage procedures using spreadsheets or papers, which need periodic modifications and have inadequate reporting capabilities.

Every member of a regulated organization is responsible for fostering a culture of compliance. If the rest of the firm follows the rules, it will matter how many processes and procedures the Compliance Officer puts in place to prevent rule violations. The key to ensuring that businesses achieve full compliance is to embed a culture of compliance.

Cloud computing for banking has turned to various cloud technologies to help embed a culture of compliance and ensure full compliance with regulations.

3. The job of a compliance officer begins long before there is a problem in the organization.#

It may seem that a company is only paying more attention to compliance measures after it has been called out for wrongdoing and is attempting to rebuild its reputation via damage management. Yet, if this ever occurs at your company, it likely means compliance standards have yet to be addressed.

That's why most companies employ Compliance Officers in the first place; they work relentlessly to prevent problems before they ever arise. A Compliance Officer's ability to avoid public scrutiny is often equated with how quickly and thoroughly they implement effective policies and practices.

Various banks are adopting cloud computing in the banking sector. So compliance in the banking sector is a must to avoid public scrutiny and maintain a strong reputation.

4. Officers of compliance don't just answer with a "no" One of the most common words in their vocabulary is "yes."#

Many people falsely believe compliance teams are conditioned to reject new ideas and suggestions from other areas. It's also true that Compliance Officers have to be very strict, meticulous, and even suspicious at times because of the nature of their job. Cloud computing in the Financial sector requires such a person to maintain the integrity of the industry.

However, cloud computing technology has provided Compliance Officers with powerful tools to enhance their abilities.

Understandably, it might lead them to tell their employees to "try again" or "no." Yet, Compliance Officers are just as many team members as everyone else, and they have the same interest in the team's success as anyone else.

Although it may be part of their job to take a different tack on a procedure or issue than the rest of the firm, doing so on purpose will only slow things down. Relationships between departments may be severed as a result of this strategy.

That's why it's cause for excitement and a sure indication of progress whenever a business finds a way to implement a process or procedure that helps everyone involved and gets the support of the compliance department.

Cloud computing in finance also makes any institution reach its desired goals.

5. Compliance is only for large businesses#

Compliance is a necessity for every company dealing with money. Banks need to deal with money daily. Nowadays banks use technology like cloud computing. So, cloud computing in the Financial sector is increasingly popular.

There is no set annual income limit below which you would be exempt from compliance rules. Auditors from the state must check in with all licensees to ensure they're functioning by the rules.

The impact of a fine may be felt more acutely by a smaller firm than by a bigger one, depending on the size of the company and the number of non-compliant loans. It is common for businesses to employ a compliance officer whose job is to verify the firm is following all applicable regulations.

Conclusion#

In the ever-evolving world of finance, compliance is a must. The value offered by compliance officers is immense. Successful businesses understand that streamlined procedures are key to staying ahead of the competition.

A license compliance program that is effectively managed can sustain itself and deliver considerable benefits to a licensor's company in both the short and long run.

Also, we have learned about the advantages of cloud computing in financial services and what it has to offer us.

The financial industry of today has several challenges. Some include security threats, various operating procedures, and inconsistent regulations. Every day, banks and other financial institutions try new strategies to expand their operations and better serve their customers.

As in today's world, financial services are continuing to evolve, and digitalization takes over, scaling applications are necessary. However, it takes work to scale applications in financial services due to various challenges.

This article describes the challenges faced by financial services while scaling applications and how to overcome them.

Understanding the terms “Financial Services” and “Scaling Application”#

Professional financial services include various subfields, including banking, investing, money management, and insurance. Only businesses and individuals working in the financial sector may provide financial services. The financial sector is the most significant and influential part of the economy.

"Scaling application" describes an application's potential for dynamic performance and scalability changes, particularly when more people are using your product or service. Nowadays, the ability to scale apps is essential for every successful enterprise. Many factors must be considered while attempting to scale an application, such as the underlying system, the application's architecture, and code optimization.

10 Different Challenges Faced by Scaling Applications#

There are many challenges that financial institutions face while scaling applications. Below are some common challenges that institutions face.

1. Security Concerns:#

Financial security has always been a top priority, but it has taken on growing importance as apps have been more widely used. Many fraudsters want access to the financial data managed by financial organizations.

Hence, financial applications should set up firewalls, implement strong security procedures, and frequently test for risks to protect their customers' privacy and the scalability of their apps.

Firewalls protect sensitive enterprise information from the public internet. They are useful for securing a private network from outside intrusion. To access private information, users of multi-factor authentication systems must provide several forms of identity.

The countermeasures mentioned above may help alleviate fears about the safety of financial application software.

2. Scalability and performance:#

When the best financial apps become popular, they need to accommodate growing users. The performance of any application must be guaranteed to withstand heavy use. Optimization of the system and investment in new infrastructure might resolve this issue. When a company's performance keeps dropping, it may ruin its image and upset its consumers.

3. Cost:#

It may be quite costly to scale a financial application software, which is particularly problematic for cash-strapped financial institutions. The financial services industry is known for its rigorous cost analysis and well-defined strategy for maximizing available resources.

Financial institutions must invest in cutting-edge technology and heavy restrictions to enhance their services and conform to regulatory mandates.

Using open-source software and hybrid cloud computing is the most efficient way to lower the cost of financial services. To efficiently grow their application without breaking the bank, they must recruit full-time workers. Financial institutions may enhance their services and conform to regulations while decreasing costs.

4. Regulatory Compliance:#

Compliance with complex rules and regulations is a must in the financial sector. They may vary from nation to country and even over short periods. Data privacy, AML, KYC, and other verification factors are only some requirements that financial services must comply with.

Failing to fulfill these rules may subject financial institutions to fines and even harm their reputations. So it is important to be thoroughly aware of the regulatory environment to ensure that financial services comply with all applicable regulations.

The best financial app in the market follows each and every rule to stay ahead in the market.

5. Customer Experience:#

Scaling applications in the financial services sector requires thorough customer experience analysis. Customers have come to demand the constant availability of banking services. Dissatisfaction may result from even little delays or interruptions. Customer satisfaction is important while scaling apps.

Thus it's important to provide users with uninterrupted access to essential services. The best strategy for financial institutions to keep their clients happy is to provide excellent service through helplines, chat boxes, and other similar hybrid cloud computing technology.

You can also opt for application autoscaling while choosing cloud computing technology.

6. Collaboration and communication:#

Successful scaling and implementation of financial application software require close coordination and open lines of communication across many parties, including individuals, groups, security personnel, organizations, etc. Teamwork may be difficult when members are distracted, under time constraints, or far apart.

7. Risk management:#

Financial institutions can only function with effective risk management. Credit, operational, and market risks are only some of the concerns that financial services providers need to monitor and control.

Companies that help spot, evaluate, and measure reputation and financial stability may find this information particularly useful.

Yet, several best financial apps are available that help financial services organizations fulfill regulatory requirements. These applications include features like automatic compliance checks, safe record-keeping, and risk management tools to guarantee that organizations are following the rules.

8. Vendor management:#

A company's vendors are the people and businesses that provide it with the goods and services it needs to function. As vendors may profoundly affect a business, efficient vendor management is especially important for financial services firms.

Delays, cost increases, security threats, and other issues may all result from improper vendor management. It calls for constant vigilance and cordial ties with suppliers.

9. Customization and personalization:#

The financial sector must customize its software to each user's requirements. It must not be easy to scale the specialized application. Implementing the customization may be time-consuming and expensive.

Even so, there is the potential for personalization to raise privacy concerns. Before making any specific plans, businesses should consider all of their options carefully.

10. Innovation and future proofing:#

Even as they grow and adapt to new technologies, financial services providers must maintain their applications fresh and future-proof. Considering the increasing significance of technological factors, it may be difficult for a business to stay abreast of all the new technical developments, particularly in a highly regulated field.

Financial companies have various benefits from hybrid cloud computing, which is increasingly popular nowadays. Financial companies also have to deal with many challenging factors when adopting cloud computing technology. But at last, it provides smooth performance and running of the institution.

By utilizing application autoscaling, you can optimize the operation of your applications by running them on instances in the cloud that can be automatically scaled up or down based on demand.

Conclusion#

Many issues make it difficult to scale financial applications used in financial services. Financial institutions will have to overcome these obstacles if they want to provide their consumers with the best service possible.

In sum, you'll need all of the mentioned qualities and more to scale an application for financial services successfully. Financial institutions can only succeed by spending money on cutting-edge technology like cloud computing, protections, human talent, and expertise while keeping expenses low.

Also investing in application autoscaling you can run financial applications smoothly. This enables you to efficiently allocate resources and ensure that your application can handle changes in usage without incurring additional costs or causing performance issues.

Cloud computing has been a topic of discussion for quite a while now. Cloud computing refers to the distribution of services online or "over the cloud". These services include storage, servers, software, databases, and analytics. Cloud Computing allows organizations to utilize resources without the need for any on-premise infrastructure.

In recent years business dynamics have changed very much. Everything service is driven by customer experience. Good customer experience creates loyalty and customer retention. It has become an important factor in the success of an organization. Technology is largely used in financial services and banking for the delivery of services.

Cloud Computing provides many benefits to organizations including flexibility, scalability, reliability, security, and cost-effectiveness. It allows organizations to channel resources into enhancing customer experience. That is why global organizations of all sizes are moving towards cloud computing.

Benefits of Cloud Computing in Financial Services and Banking#

There has never been a change so big and innovative in the financial services and banking industry as cloud computing. It has provided organizations with flexibility, scalability, and cost-effectiveness. These features are the reason for satisfactory customer experience. Here are some benefits of cloud computing in financial services and banking.

Cost Effectiveness#

One of the main benefits of cloud computing in financial services is cost-effectiveness. With Cloud-based solutions, organizations are no longer dependent on physical IT infrastructure. Instead, organizations can now utilize cloud computing resources according to their need. These online resources are better than on-prem IT infrastructure and provide efficiency.

Scalability#

Scalability is a very important factor, especially in financial services and banking. Cloud computing allows organizations to scale up and down on the basis of their needs. This helps organizations deploy new services fast, and control their resources based on changing customer needs.

Flexibility#

Another benefit of cloud computing in financial services and banking is flexibility. Many cloud service providers are available in the market. Organizations can choose a cloud provider based on their specific needs. Cloud-based infrastructure enables organizations to provide the best customer experience by enabling access to resources from anywhere anytime.

Security#

Security is another important benefit of cloud computing. Cloud-based solutions have better security measures to handle breaches and other cybersecurity-related issues as compared to independent organizations. Cloud-based solutions have dedicated teams to look for vulnerabilities and threats every hour of the day. Moreover, cloud solutions have built-in security features that provide extra layers of security.

Data Analytics#

Cloud computing provides financial services and banking organizations with plenty of useful analytics tools. These tools help financial institutions analyze the behavior patterns of their customer and market trends. These two features combined help them make important decisions about their services.

Customer Experience in Financial Services#

In recent years business dynamics have changed completely. Customer experience is now a big factor in the success of a financial institution. Customers expect a personalized experience that addresses all of their pain points.

Financial services and banking organizations need to focus on enhancing customer experience to retain existing customers and gain new ones.

Customer experience in financial services can be enhanced by understanding key factors influencing it. These factors include personalization, trust, efficiency, and constant innovation. Financial services organizations can also use a technique called customer journey mapping. It involves tracking customers' histories to give personalized suggestions.

Enhancing Customer Experience with Cloud Computing#

Here are some of the ways cloud computing services can enhance the customer experience in financial services and banking industry.

Personalization#

Personalization is a key factor in improving customer experience. It can be improved by using cloud computing services. Financial services and banks can use analytics and AI (Artificial Intelligence) to understand customer behavior and tailor their services accordingly.

Financial organizations can use customer data and insight to create targeted ads and customized products. For example, they can target insurance ads if a person's financial record shows a purchase of a car or house. They can also tailor products like credit cards based on specific needs. These personalizations create loyalty and customer retention.

Speed and Efficiency#

In today's world speed and efficiency is very important to improve customer experience, especially in the financial services and banking industry. One of the key benefits of cloud computing in financial services and banking is its speed and efficiency. Cloud-based solutions provide users with seamless processing power in real-time. This allows financial organizations to process large volumes of transactions and access customer data in real-time.

Cloud computing services like project management and instant messaging allow teams to collaborate efficiently. This results in fast decision-making and constant deployment of features.

Seamless Integration#

Seamless Integration is another factor that can enhance the customer experience in the financial services and banking industry. Cloud computing services offer various software to ensure the accessibility of different services seamlessly.

It also helps financial institutes to remain consistent across devices. This means customers can access banking applications on their smartphones and desktops.

Enhanced Data Analysis#

Enhanced data analysis provided by cloud computing can also increase customer satisfaction. Financial services and banks can use data analysis to give their customers personalized services. This data is very useful for these institutions to understand changing customer behavior and market trends. By using this data seamless customer experience can be provided across all channels.

Case Studies#

Here are some case studies that demonstrate the benefits of cloud computing in enhancing customer experience in financial services and banking.

JP Morgan Chase#

JP Morgan is one the world's largest financial companies and an early adopter of cloud computing services. The organization has been using cloud computing to manage risk, streamline workflow, and enhance customer experience.

JP Morgan Chase has utilized cloud computing to scale up and down based on their customer needs. Moreover, with the help of cloud computing, they have been able to roll out services to fulfill their customer's needs. They have also effectively managed their cost by moving their resources to the cloud.

Capital One#

Capital One is another financial institution that has adopted cloud computing to enhance its customer experience. They have been using cloud computing to roll out services according to the needs of their customers. Capital One has used cloud computing services to make the customer experience seamless across all platforms. Moreover, they have also moved many of their important resources to the cloud to save costs.

Challenges and Risks#

There is no doubt that cloud computing has completely changed the dynamics of the financial services and banking industry. But the technology is still new and there are some challenges and risks that need to be taken into account. Here are some of the challenges that organizations should consider before moving to the cloud.

Data Privacy and Security#

One of the major challenges financial services and banks face in adopting cloud computing is security. Cloud computing involves storing and processing data on third-party servers. This information includes customer personal details and transaction history.

Due to the nature of the information, these servers are most likely to be attacked by cybercriminals. Financial organizations need to choose a cloud service provider that can ensure data privacy and security.

Regulatory Compliance#

Financial Services and banking is a sensitive industry and is regulated by different government bodies. Some of these regulations are about the storage of customer data. These organizations need to make sure they comply with all the regulations before making a transition. This will help them avoid any issues with regulatory bodies and ensure the privacy and security of their customers.

Technical Issues#

Another important challenge for financial services in adopting cloud computing is technical issues. Cloud computing relies completely on complex technology. Any glitch can cause downtime that disrupts important operations. This affects customer experience negatively. That is why financial institutions should take necessary measures to ensure the reliability of their systems.

Vendor Lock-In#

Vendor Lock-in is another challenge for financial services and banks in adopting cloud infrastructure. These organizations sign long-term contracts with other companies. Long-term contracts with a single cloud provider may result in vendor lock-in. This causes less flexibility, higher costs, and a low level of security. Financial organizations should diversify the use of cloud services. Depending only on one cloud provider is a recipe for disaster.

Future of Cloud Computing in Financial Services and Banking#

The adoption of cloud computing in financial services and banking has already started on a massive scale. According to a recent survey around 79% of all the banks in the US have adopted cloud computing infrastructure.

This number is expected to grow. This is because the cloud provides organizations with benefits like security, flexibility, reliability, and cost-effectiveness. Organizations resisting cloud adoption will be left way behind.

Emerging Trends in Cloud Computing#

The future of cloud computing in banking and finance will be shaped by emerging trends like AI (Artificial Intelligence), Blockchain, and IoT (Internet of Things). AI is expected to improve customer experience. While the blockchain can be used to store important customer data. The Internet of Things (IoT) can be used to create personalized services for customers in the future.

Conclusion#

Cloud computing plays a crucial role in enhancing customer experience in the financial services and banking industry. It provides benefits like flexibility, availability, security, and reduced cost.

Organizations are using it successfully to enhance customer experience. Many financial institutions like JP Morgan Chase and Capital One have already adopted cloud computing.

Cloud computing has also some security and regulatory challenges. Financial institutions can overcome these challenges with proper planning and infrastructure. It is important for financial organizations to adopt cloud computing to remain competitive in the long run.

Introduction#

Banks and financial institutions handle large volumes of data daily. With advancements in technology, the financial sector has evolved beyond mere names and numbers. Technologies like cloud computing and data analytics are now integral to leveraging this data effectively. These technologies enhance customer experience, cost efficiency, and security, providing deeper insights into customer behavior and marketing trends. This article explores the applications, benefits, and challenges of cloud computing and data analytics in the financial sector.

Cloud Computing in Banking and Financial Services#

Cloud computing has transformed the banking sector, allowing organizations to scale resources up or down as needed without maintaining physical infrastructure. Services such as servers, storage, software, and analytics tools are now available online.

Benefits of Cloud Computing#

Cost Efficiency#

Cloud computing enables organizations to pay only for what they use. This is crucial for the banking sector, which deals with large volumes of customer data daily. With cloud computing, organizations can seamlessly store and process this data without the need for on-premises IT infrastructure.

Flexibility#

Cloud computing offers more flexibility and agility compared to traditional systems. Financial institutions can scale operations based on customer needs and market trends. For example, during tax season, organizations can easily scale up operations and scale down afterward without upgrading physical infrastructure.

Security#

Security is a significant concern for financial institutions, which are prime targets for hackers. Cloud providers offer robust security features, including encryption, firewalls, access control, and authentication. They also have dedicated IT teams to provide continuous support.

Applications of Cloud Computing#

Payment Processing#

Cloud computing enhances payment processing efficiency. It allows organizations to handle large volumes of transactions seamlessly.

Loan Origination#

Cloud-based systems facilitate effective loan management. They enable real-time analysis of customer data, helping organizations make informed decisions.

Customer Relationship Management#

Cloud computing improves customer experience by allowing financial organizations to create personalized services and advertisements, which helps in customer retention and attraction.

Data Analytics in Financial Services and Banking#

Data analytics is crucial for understanding customer needs and making informed decisions. It enhances profit potential and builds customer trust and loyalty.

Advantages of Data Analytics#

Improved Decisions#

Data analytics enables organizations to make data-driven decisions by analyzing past trends and predicting future outcomes.

Increased Efficiency#

Automation of tasks such as data cleaning, risk assessment, and data entry through data analytics increases efficiency and reduces costs.

Better Customer Service#

Data analytics helps in providing a personalized experience by analyzing customer behavior and preferences.

Applications of Data Analytics#

Fraud Detection#

Data analytics helps in detecting fraud by analyzing customer behavior, transaction history, and credit details. It can identify identity theft, money laundering, and other financial frauds.

Risk Analysis#

Data analytics aids in risk management by identifying risks related to operations, markets, and fraud. It helps in predicting market trends and avoiding risky investments.

Predictive Modeling#

Predictive modeling uses past data to forecast future trends, enhance customer experience, maximize profits, and identify potential fraud.

Challenges and Concerns#

Privacy and Security#

Privacy and security are major concerns due to the sensitive nature of data handled by financial institutions. Cloud computing and data analytics can make data vulnerable to cyber threats.

Compliance Issues#

Financial institutions must comply with regulations such as GDPR, PCI DSS, and FFIEC. Cloud computing can complicate compliance with these regulations.

Data Governance Challenges#

Data governance challenges include managing data availability, security, quality, and adherence to standards.

Conclusion#

Cloud computing and data analytics are vital in enhancing the performance of financial services and banks. They offer scalability, flexibility, and security but also come with challenges that need to be addressed. Financial institutions should adopt these technologies while understanding and mitigating their challenges.

For a more detailed explanation, watch the video.

Kubernetes and Docker are important implementations in container orchestration.

Kubernetes is an open-source orchestration system that has recently gained popularity among IT operations teams and developers. Its primary functions include automating the administration of containers and their placement, scaling, and routing. Google first created it, and in 2014, Google gave it to Open Source. Since then, the Cloud Native Computing Foundation has been responsible for its maintenance. Kubernetes is surrounded by an active community and ecosystem that is now in the process of development. This community has thousands of contributors and dozens of certified partners.

What are containers, and what do they do with Kubernetes and Docker?#

Containers provide a solution to an important problem that arises throughout application development. When developers work on a piece of code in their local development environment, they are said to be "writing code." The moment they are ready to deploy that code into production is when they run into issues. The code, which functioned well on their system, cannot be replicated in production. Several distinct factors are at play here, including different operating systems, dependencies, and libraries.

Multiple containers overcame this fundamental portability problem by separating the code from the underlying infrastructure it was executing on. This allowed for more flexibility. The developers might bundle up the program and all the bins and libraries required to operate properly and store them in a compact container image. The container may be executed in production on any machine equipped with a containerization platform.

Docker In Action#

Docker makes life a lot simpler for software developers by assisting them in running their programs in a similar environment without any complications, such as OS difficulties or dependencies because a Docker container gives its OS libraries. Before the advent of Docker, a developer would submit code to a tester; but due to a variety of dependency difficulties, the code often failed to run on the tester's system, despite running without any problems on the developer's machine.

Because the developer and the tester now share the same system operating on a Docker container, there is no longer any pandemonium. Both of them can execute the application in the Docker environment without any challenges or variations in the dependencies that they need.

Build and Deploy Containers With Docker#

Docker is a tool that assists developers in creating and deploying applications inside containers. This program is free for download and can be used to "Build, Ship, and Run apps, Anywhere."

Docker enables users to generate a special file called a Dockerfile. The Dockerfile file will then outline a build procedure, creating an immutable image when given to the 'docker build' command. Consider the Docker image a snapshot of the program with all its prerequisites and dependencies. When a user wishes to start the process, they will use the 'docker run' command to launch it in any environment where the Docker daemon is supported and active.

Docker also has a cloud repository hosted in the cloud called Docker Hub. Docker Hub may act as a registry for you, allowing you to store and share the container images that you have built.

Implementing containerization in container orchestration with Docker and Kubernetes#

The following is a list of the actions that may be taken to implement containerization as well as container orchestration using Docker and Kubernetes:

1. Install Docker#

Docker must initially be installed on the host system as the first step in the process. Containers may be created using Docker, deployed with Docker, and operated with Docker. Docker containers can only be constructed and operated using the Docker engine.

2. Create a Docker image#

Create a Docker image for your application after Docker has been successfully installed. The Dockerfile lays out the steps that must be taken to generate the image.

3. Build the Docker image#

To create the Docker image, you should use the Docker engine. The program and all of its prerequisites are included in the picture file.

4. Push the Docker image to a registry#

Publish the Docker image to a Docker registry, such as Docker Hub, which serves as a repository for Docker images and also allows for their distribution.

By Kubernetes#

1. Install Kubernetes#

The installation of Kubernetes on the host system is the next step to take. Containers may be managed and orchestrated with the help of Kubernetes.

2. Create a Kubernetes cluster#

Create a group of nodes to work together using Kubernetes. A collection of nodes that collaborate to execute software programs is known as a cluster.

3. Create Kubernetes objects#

To manage and execute the containers, you must create Kubernetes objects such as pods, services, and deployments.

4. Deploy the Docker image#

When deploying the Docker image to the cluster, Kubernetes should be used. Kubernetes is responsible for managing the application's deployment and scalability.

5. Scale the application#

Make it as large or as small as necessary using Kubernetes.

To implement containerization and container orchestration using Docker and Kubernetes, the process begins with creating a Docker image, then pushing that image to a registry, creating a Kubernetes cluster, and finally, deploying the Docker image to the cluster using Kubernetes.

Kubernetes vs. Docker: Advantages of Docker Containers#

Managing containers and container platforms provide various benefits over conventional virtualization, in addition to resolving the primary problem of portability, which was one of the key challenges.

Containers have very little environmental impact. The application and a specification of all the binaries and libraries necessary for the container to execute are all needed. Container isolation is performed on the kernel level, eliminating the need for a separate guest operating system. This contrasts virtual machines (VMs), each with a copy of a guest operating system. Because libraries may exist across containers, storing 10 copies of the same library on a server is no longer required, reducing the required space.

Conclusion#

Kubernetes has been rapidly adopted in the cloud computing industry, which is expected to continue in the foreseeable future. Containers as a service (CaaS) and platform as a service (PaaS) are two business models companies such as IBM, Amazon, Microsoft, Google, and Red Hat use to market their managed Kubernetes offerings. Kubernetes is already being used in production on a vast scale by some enterprises throughout the globe. Docker is another incredible combination of software and hardware. Docker is leading the container category, as stated in the "RightScale 2019 State of the Cloud Report," due to its huge surge in adoption from the previous year.

The banking sector is increasingly turning to cloud technology to help them meet the demands of the digital age. By using cloud services, financial institutions can take advantage of cloud technology's scalability, security, and cost-effectiveness. Additionally, these cloud providers offer a wide range of services and features that can be used to meet the specific needs of the banking sector, such as compliance and security. This article will discuss cloud technologies' benefits to the banking sector or any other financial organization.

Benefits that the Banking Sector gets from using Cloud Technologies#

Cloud technology in banking offers many benefits to banking and other financial institutions. Here are the top 8 benefits of using cloud computing in the banking sector:

Increased flexibility and scalability:#

Cloud technology in banking allows banks to scale their infrastructure and services up or down as needed. This is particularly beneficial for banks that experience seasonal fluctuations in demand or need to accommodate sudden spikes in traffic.

Reduced costs:#

Cloud technology in banking can help banks reduce costs by eliminating the need for expensive hardware and software. Banks can also reduce costs by using pay-as-you-go pricing models, which allow them to only pay for the resources they use.

Improved security:#

Cloud providers typically invest heavily in security, offering banks a higher level of security than they could achieve. Many cloud providers also offer compliance with various security standards, such as SOC 2 and PCI DSS.

Increased agility:#

Cloud technology allows banks to quickly and easily launch new services and applications, which can help them stay ahead of the competition.

Improved disaster recovery:#

Cloud computing in banking allows banks to quickly and easily recover from disasters, such as natural disasters or cyber-attacks. Banks can use cloud-based disaster recovery solutions to keep critical systems and data safe and accessible.

Better collaboration and communication:#

Cloud computing in banking can help banks improve collaboration and communication between different departments and teams. This can lead to more efficient processes and better decision-making.

Increased access to data and analytics:#

Cloud computing in banking can provide banks with easy access to large amounts of data and analytics, which can help them make more informed decisions.

Better customer experience:#

Banks can improve the customer experience by using cloud technology by offering new and innovative services, such as mobile banking, online account management, and real-time notifications.

Hence, cloud computing in finance is increasing day by day. Not only can they get all these benefits but also other financial organizations that employ cloud computing in the finance system get the same benefits.

Cloud service models#

Cloud service models refer to the different types of cloud computing services offered to customers. These models include:

Infrastructure as a Service (IaaS):#

This model provides customers with virtualized computing resources, such as servers, storage, and networking, over the internet. Examples of IaaS providers include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

Platform as a Service (PaaS):#

This model provides customers with a platform for developing, running, and managing applications without the complexity of building and maintaining the underlying infrastructure. Examples of PaaS providers include AWS Elastic Beanstalk, Azure App Service, and GCP App Engine.

Software as a Service (SaaS):#

This model provides customers access to software applications over the internet. Examples of SaaS providers include Salesforce, Microsoft Office 365, and Google G Suite.

Function as a Service (FaaS):#

This model allows customers to execute code in response to specific events, such as changes to data in a database or the arrival of new data in a stream, without having to provision and manage the underlying infrastructure. Examples of FaaS providers include AWS Lambda, Azure Functions, and Google Cloud Functions.

Backup as a Service (BaaS):#

This model allows customers to back up their data to cloud storage. Examples of BaaS providers include AWS Backup, Azure Backup, and Google Cloud Backup.

Each model provides different benefits and is suited to different workloads and use cases.

Which cloud technology is used more in the Banking sector#

The banking sector has been using cloud technology for several years now, with many financial institutions recognizing the benefits that it can bring. A variety of different cloud technologies are used in the banking sector, but some of the most popular include Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).

Amazon Web Services (AWS)#

Amazon Web Services (AWS) is one of the banking sector's most widely used cloud technologies. This is largely due to its scalability, security, and cost-effectiveness. AWS offers a wide range of services, including computing, storage, and databases, which can be easily scaled up or down to meet the changing needs of the business. Additionally, AWS has several security features that can be used to protect sensitive financial data, including encryption, access controls, and network security.

Microsoft Azure#

Microsoft Azure is another popular cloud technology used in the banking sector. Azure offers similar services to AWS, including computing, storage, and databases, but it also has several additional features that are particularly useful for the banking sector. For example, Azure's Active Directory can be used to manage user access and authentication, and its Azure Key Vault can securely store and manage encryption keys. Additionally, Azure's compliance certifications can help financial institutions meet regulatory requirements.

Google Cloud Platform (GCP)#

Google Cloud Platform (GCP) is a widely used cloud computing in the banking sector. GCP offers services similar to those provided by AWS and Azure, including computing, storage, and databases. Additionally, GCP provides several security and compliance features, such as encryption and access controls, that can be used to protect financial data. GCP is also known for its machine learning and big data analytics capabilities, which can be used to gain insights from financial data.

In addition to these major cloud providers, several other cloud computing in the banking sector are used. For example, some financial institutions use private clouds or hybrid clouds to provide a more secure and compliant environment for their data.

Conclusion#

Cloud computing in finance offers many benefits for banks and other financial institutions. From increased flexibility and scalability to improved security and customer experience, cloud technology can help banks stay ahead of the competition and provide better customer service. As more and more banks adopt cloud technology, it will become increasingly important for banks to stay up-to-date with the latest cloud technologies to remain competitive.

Cloud computing in financial sector provides the opportunity to process large chunks of data without needing to spend money on IT infrastructure. Cloud computing in finance provides organizations with different tools and storage that help them improve the scalability, flexibility, and availability of data. In this article, we will discuss the impact of cloud computing on the banking and finance sector.

Let's talk about the Impact of Cloud Computing in Financial Sector And Banking#

The financial service sector handles big chunks of sensitive financial data of individuals, organizations, and governments. The amount of data these organizations process every day requires them to have a robust IT infrastructure. Maintaining this kind of infrastructure is difficult for these banking services. That is why these institutions are looking for more cost-effective and efficient ways of handling and processing this much data.

Advantages of Cloud Technology in the Banking and Financial Services Industry#

Cloud computing in banking sector provides many advantages that help financial institutions manage customer resources and information effectively. Here are some of the advantages.

Increased efficiency and cost-effective#

One of the main advantages Cloud technology provides is different management tools that are used to manage information to complete day-to-day operations effectively. Moreover, cloud technology provides the finance sector with the infrastructure that has features like cost effectiveness, scalability, flexibility, and availability of data.

Improved security and compliance#

Financial institutions and banks are major targets of cyberattacks and fraud. Cloud computing in financial sector allows these institutions to have robust security infrastructure. Cloud computing in finance allows organizations to identify real-time threats and eliminate them.

Moreover with cloud-based risk management systems banks can identify potential threats in advance by modeling and can prioritize them based on their impact on the banking operations and customer experience. This method of identifying real-time threats has provided financial institutions with the advantage of being prepared which was not available in the traditional banking system.

Enhanced customer experience and satisfaction#

Cloud computing in financial sector provides institutions with the advantage to incorporate Artificial Intelligence (AI) and Machine Learning (ML). These technologies help financial institutions understand customer needs and incorporate changes accordingly. Cloud computing in finance also provides users with real-time information to help them make informed decisions.

All of these features combine to enhance customer experience and provide satisfaction.

Access to real-time data and analytics#

Cloud computing in banking sector also provides financial organizations with the advantage to access real-time information from different locations with low latency. This helps financial organizations process large chunks of financial data and transactions in seconds hence increasing the efficiency of the organization.

This feature can be utilized by financial sectors to effectively share real-time data with organizations and regulatory bodies. The response from these organizations will help implement the necessary changes in time.

Improved collaboration and teamwork#

Another big advantage that cloud computing in financial sector provides is improved collaboration between organizations for data sharing. These collaborations help financial institutions to perform efficient and successful financial operations, effective risk management, fraud detection, and increased efficiency of operations.

Challenges faced by the Banking and Financial Services Industry in Adopting Cloud Technology#

While cloud computing in financial sector provides many advantages for banks and other financial institutions. But adopting cloud computing in finance raises some concerns. Here are some of the challenges faced by the banking and financial services industry in adopting cloud technology.

Data privacy and security concerns#

Cloud computing in finance raises privacy and security concerns. In a cloud-based system, most of the data is stored online in cloud storage which makes it vulnerable to cyberattacks. According to a study, 44% of all cyber-attacks are on financial institutions. This makes it difficult for financial institutions like banks to shift to cloud-based solutions.

Cost of implementation and maintenance#

Another challenge in cloud computing for banking is a cost consideration. Most banks do not have the necessary infrastructure for cloud-based solutions. Banks process large volumes of data every day. In a cloud-based banking system, the cost depends on the amount of data processed. It will be very difficult for financial institutions to handle costs in the early stages.

Integration with legacy systems#

Another challenge financial institutions face while adopting cloud computing for banking is integration with legacy systems. Most financial institutions have legacy systems that are vital for their day-to-day operations. Replacing legacy systems is not an immediate option for the organization. But legacy systems can be connected to the cloud using APIs and other techniques.

Regulatory and compliance issues#

Banks and financial service institutions are regulated by different government bodies. These financial institutions are needed to comply with regulations by these bodies to continue their operations otherwise they may face restrictions and fines from these bodies. Cloud computing in financial sector makes it hard for financial institutions to comply with these regulations.

Most of the time it is required for these companies to store data at a specific place which is not possible in cloud-based systems. Sometimes it is also required for financial institutions to give access to information to only certain persons but in cloud-based systems it is required to give access to multiple developers to maintain stability.

Case Studies of Cloud Technology Adoption in the Banking and Financial Services Industry#

Here are some case studies of financial institutes that have adopted cloud computing technology. These financial organizations have properly leveraged cloud technology to scale their operations. Have a look at all these organizations to have a better understanding of the impact.

JPMorgan Chase#

JP Morgan Chase is an American multinational financial organization that has adopted Amazon Web Services (AWS) to increase the efficiency of operations, control cost, and enhance security. This bank leveraged different cloud service tools to successfully enhance the efficiency of its everyday operations.

Moreover, with the help of a cloud-based solution, the bank was able to modify its technology to cope with modern changes. It has created different cloud-based services like banking apps to globally scale up its operations with the help of cloud technology.

Citigroup#

Citigroup is another American multinational bank that leveraged cloud computing in financial services to benefit from the latest technology. To effectively benefit from the cloud, Citigroup adopted a multi-cloud strategy. This strategy helped Citi to benefit from the different technologies of different cloud computing services.

Citigroup uses Amazon cloud services for their robust security, it leverages Google cloud services for its expertise in Machine learning, and Microsoft Azure for Artificial Intelligence and big data. In this way, Citigroup has effectively used cloud computing technology to scale its global operations by showing flexibility to meet the changing needs of customers.

Deutsche Bank#

Deutsche Bank is another great example of a financial institution that has successfully adopted cloud computing in banking sector. The bank has adopted a multi-cloud strategy to manage its operations. The bank has been very successful in adopting cloud computing in the financial sector. The bank has been able to improve its IT infrastructure to meet customers' changing needs using cloud computing for banking.

Moreover, Deutsche Bank has also leveraged cloud technology to support its digital initiatives like its online banking platform and mobile app. It has also been able to improve its security. Overall it has been beneficial for the bank to adopt cloud technology because it has helped them improve efficiency, reduce cost, and improve security.

We have only discussed three banks here but there are a large number of successful multinational banks that are in the process of adopting or have adopted cloud computing for banking.

Future of Cloud Technology in the Banking and Financial Services Industry#

Cloud Technology's future in the banking and financial services industry looks promising. More and more financial organizations are understanding the importance of cloud technology and making a shift to cope with changing technology. Cloud computing for banking has promising features like improved efficiency, seamless connectivity, increased security, and cost-effectiveness.

More banks and financial organizations will leverage the cloud for flexibility, scalability, cost-effectiveness, and availability. Cloud technology will play a vital role in transforming the financial sector. Banks will be able to create new streams of revenue by utilizing cloud technology.

Heavy investments are being made to make clouds more secure. This will attract more banks in near future to make a shift toward cloud-based solutions. With each passing day, cloud-based solutions are becoming more secure and reliable.

Conclusion:#

Cloud tech in banking and financial institutions is becoming important day by day. Cloud tech is heavily impacting the banking and financial sector. With the current rate of technological development, it is becoming difficult for banks to survive without a cloud-based infrastructure. Cloud-based infrastructure provides banks and financial institutions with advantages like increased efficiency, cost-effectiveness, increased security and compliance, and enhanced customer experience.

Banks and financial institutions are facing different challenges in implementing cloud-based solutions which are also affecting these institutions. The majority of the financial sector will adopt cloud tech in the near future if its development in it is continued at the current rate.

Introduction#

Technological modernization makes it easier to carry out various business operations within a second. One can manage different tasks by adopting leading computer software.

The financial services industry is one of the world's most heavily regulated and complex industries. As such, choosing a software as a service (SaaS) tool to help manage their operations can be a challenging task. This article will discuss some of the most significant challenges financial services companies face when choosing a SaaS tool and what they can do to overcome them.

What is SaaS?#

SaaS stands for "Software as a Service." It is a model of delivering software applications over the web browser. Cloud providers host this software and associated data. Instead of installing and maintaining software on individual computers or servers, users access the software through a web browser. This allows them to access the software and their data from any device with an internet connection. According to businesses, 70% of the business software they use today is SaaS-based. They further say that by 2025, this will rise to 85%.

Some examples of popular SaaS applications include customer relationship management (CRM) software such as Salesforce, email platforms like Microsoft Office 365 and G Suite, and project management software like Asana. Many small businesses and startups also use cloud-based accounting software like QuickBooks, Xero, and Wave.

Challenges Faced by Financial Services#

Regular Compliance#

Compliance is one of the biggest challenges that financial services companies face when choosing a SaaS tool. Financial services companies must comply with a wide range of regulations, including data privacy, data security, and anti-money laundering. To ensure compliance, financial services companies must choose a SaaS tool that meets all regulatory requirements. This can be difficult, as many SaaS tools on the market are not specifically designed for the financial services industry and may not meet all of the necessary regulatory requirements.

Data Security#

Another significant challenge that financial services companies face when choosing a SaaS tool is data security. Financial services companies handle sensitive customer information, and it is essential to keep this information secure. In order to ensure data security, financial services companies must choose a SaaS tool with robust security features, such as encryption, multi-factor authentication, and regular security updates. However, finding a SaaS tool that meets these requirements can be difficult. Cloud computing for banking is challenging as many SaaS tools on the market do not have the necessary security features.

Integration#

A third major challenge that financial services companies face when choosing a SaaS tool is integration. Financial services companies often have a wide range of systems and applications in place, and it can be difficult to find a SaaS tool that integrates with all of them. In order to overcome this challenge, financial services companies must choose a SaaS tool that can integrate with their existing systems and applications or that can be customized to meet their specific needs. However, finding a SaaS tool that meets these requirements can be difficult, as many SaaS tools on the market are not designed to be easily integrated with other systems and applications.

Scalability and Flexibility Challenge#

Financial services companies may also face challenges in terms of the scalability and flexibility of the SaaS tool. As the financial services industry is a rapidly evolving field, it is crucial for the SaaS tool to evolve and adapt to the company's changing needs. This includes the ability to handle an increasing amount of data and transactions and integrate new technologies and features as they become available.

Lost Productivity#

Many financial organizations and banks are striving to join the cloud revolution. Cloud computing for banking is now easier than it has been ever before. The majority of firms, however, do not have the expertise or funding to utilize cloud technologies. Most banks are still considering moving their outdated monolithic systems to the cloud. Older systems-dependent businesses miss out on cloud apps' productivity advantages. As banks race to transition to the cloud, there may be hours or days of server downtime, which will damage both consumers and employees.

Dealing with Challenges#

In order to overcome these challenges, financial services companies must do their research and carefully evaluate the various SaaS tools on the market. Though Cloud computing for banking can be difficult, it can be improved by following below given steps:

• Have a strong customer support team to respond to and address customer concerns quickly.
• Continuously monitor and analyze customer feedback to identify patterns and common issues.
• Implement a robust testing process to catch and fix bugs before they reach customers.
• Have a disaster recovery plan to minimize downtime and data loss in case of unexpected outages.
• Regularly update and improve your service to stay ahead of competitors and meet changing customer needs.
• Have a clearly defined process for handling and addressing security concerns to protect customer data and minimize risk.
• Develop a plan for scaling the infrastructure as the number of users increases.
• Keep track of industry trends and updates in the software to stay ahead of the curve and anticipate potential problems.
• Use analytics to measure the performance of the software and identify areas that need improvement.
• Be transparent with your customers, keep them informed of any issues or planned maintenance, and involve them in resolving any issues they face.

Conclusion#

Choosing a SaaS tool for a financial services company can be challenging due to the industry's highly regulated and complex nature. However, by thoroughly researching and evaluating the various SaaS tools on the market and working with a vendor. They should look for SaaS tools that meet all of the necessary regulatory requirements, have robust security features, can be easily integrated with existing systems and applications, and are scalable and flexible enough to evolve with the company's changing needs. Additionally, they can also consider working with a vendor who specializes in providing software solutions to financial services companies, as they will better understand the industry's specific needs and requirements.

How can BFSI companies leverage the latest cloud technology?#

What does BFSI stand for?#

BFSI stands for “Banking, Financial Services, and Insurance” companies. It refers to companies that operate in the financial sector, including banks, insurance companies, and other organizations that provide financial services. These companies may offer a wide range of services, such as banking, lending, investment, wealth management, and insurance.

BFSI companies play a crucial role in the economy by providing various financial services to individuals and businesses. Banks, for example, provide services such as managing current and savings accounts, loans, credit cards, etc. Insurance companies, on the other hand, offer protection against potential financial losses from events such as accidents, illnesses, and natural disasters.

BFSI companies are heavily regulated by government agencies to ensure that they operate in a safe and sound manner and protect the interests of their customers. They also use advanced technology and data analytics to manage risks and make better business decisions. They play an important role in the flow of money and financial transactions, and they also help businesses and individuals manage their finances and plan for the future.

BFSI companies adopting Cloud Technology#

The BFSI sector has played a significant role in the development of fintech, which refers to the use of technology to improve and automate financial services. Banks and other financial institutions have been some of the early adopters of fintech, using it to improve their internal operations and enhance the services they provide to customers.

One of the key areas where BFSI companies have embraced fintech is digital banking. Banks have introduced online and mobile banking platforms, which allow customers to access their accounts, transfer money, pay bills, and manage their finances from anywhere using their smartphones or computers. It has enhanced the convenience and accessibility of banking services for customers.

BFSI companies have played a major role in shaping the fintech landscape and continue to be major players in the industry. They are leveraging technology to improve their operations, increase efficiency, and offer better services to customers.

The BFSI sector has played a significant role in driving digital transformation in the financial industry. Digital transformation refers to the integration of digital technology into all aspects of an organization, which can lead to significant improvements in efficiency, cost savings, and customer experience.

Additionally, the BFSI sector has been increasingly adopting cloud architecture in recent years, in order to improve their operations, reduce costs, and increase scalability. Cloud architecture refers to the use of remote servers and data centers, accessed through the internet, to store and manage data and applications.

BFSI companies are also using cloud-based services such as SaaS, PaaS, and IaaS to improve their customer engagement, analytics, and compliance. Services like Salesforce, Workday, Adobe, and AWS provide an end-to-end solution for customer relationship management, human resources, and compliance, which can help BFSI companies improve customer engagement and streamline internal operations.

The BFSI sector is leveraging cloud architecture to improve its operations, reduce costs, and increase scalability by using remote servers and data centers to store and manage data, and by using cloud-based platforms to develop and deploy new applications. This has led to a more efficient and adaptable financial industry, which is better able to meet the needs of customers and adapt to the changing digital landscape.

Insurance companies are using cloud-based platforms to automate and digitize their back-office processes, such as underwriting, claims processing, and policy management. This has led to significant improvements in efficiency, cost savings, and reduced risk of errors and fraud. Cloud-based analytics and machine learning tools are used to identify risks and detect fraud in real-time, which helps insurance companies take proactive measures to protect their customers.

Use of Big Data and AI#

Due to big data, AI has become increasingly important in the BFSI sector, as financial institutions look for ways to gain insights from large amounts of data and improve their operations. BFSI companies are also using RPA to automate repetitive tasks like data entry, customer service, and compliance, which reduces the risk of errors, improves efficiency, and reduces labor costs.

Hyper automation in the BFSI sector refers to the use of advanced technologies, such as artificial intelligence (AI), robotic process automation (RPA), and machine learning, to automate and optimize business processes. Hyper automation is an advanced form of automation that uses a combination of technologies.

It also provides better compliance. Hyper automation can help BFSI companies meet the regulatory requirements for data security and privacy. For example, by using AI and machine learning to detect and prevent fraud, financial institutions can comply with regulations such as the Payment Card Industry Data Security Standards (PCI-DSS).

Cloud migration provides security in the BFSI sector#

Data encryption, multi-factor authentication, and compliance (Cloud providers also offer compliance certifications, like SOC2, PCI-DSS, and HIPAA, which are mandatory for BFSI companies. This helps them meet regulatory compliance for data security and privacy, without having to invest in the compliance infrastructure.), etc. As well as by allowing for more effective disaster recovery and business continuity planning. This can lead to a more secure and compliant financial industry, which is better able to protect sensitive customer data and maintain operations in the face of cyber threats and other disruptions.

In addition, BFSI companies have also used fintech to improve their risk management and compliance processes. By using advanced analytics and machine learning algorithms, they can identify potential fraud and other risks more quickly and accurately, helping to protect their customers and the overall financial system.

Cloud is not limited to technology. It will play a major role in how BFSI companies will function in the future. With changing customer expectations, new technologies, and new business strategies, BFSI companies should start adopting new strategies for the future. By the year 2030, we will see BFSI companies operating in an entirely different manner.

We have seen a lot more digital transformation globally in recent years. Cloud computing has become an increasingly popular technology in the banking industry. Banks use cloud computing to improve their operations, reduce costs, and increase efficiency. In this blog, you will learn about various cloud infrastructures, how the banking industry will grow using cloud computing services, and what challenges they face while working on cloud computing. So let's get started with our very first topic.

Various types of Cloud Infrastructure are needed to get BFSI.#

The banking, financial services, and insurance (BFSI) sector rely heavily on technology to conduct day-to-day operations. These operations include processing transactions, managing customer data, and analyzing financial data. To ensure continuous operations, BFSI organizations need to have a robust and reliable cloud infrastructure in place.

BFSI organizations can use several types of cloud infrastructure to achieve continuous operations. These include:

Public Cloud:#

Public cloud infrastructure is provided by third-party providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). These providers offer a wide range of services, such as storage, computing, and networking. Public cloud infrastructure is ideal for BFSI organizations that do not want to invest in building and maintaining their data centers.

Private Cloud:#

The organization owns and operates private cloud infrastructure. BFSI organizations with strict security and compliance requirements typically use it. Private cloud infrastructure allows organizations full control over their data and applications, which is crucial for the BFSI sector.

Hybrid Cloud:#

Hybrid cloud architecture combines public and private cloud benefits. It allows organizations to use public cloud infrastructure for non-sensitive workloads and private cloud infrastructure for sensitive workloads. This approach is ideal for BFSI organizations that must balance cost and security.

Multi-cloud:#

The Multi-cloud infrastructure allows organizations to use multiple cloud providers for different workloads. This approach is ideal for BFSI organizations that want to take advantage of the strengths of other cloud providers. For example, an organization may use AWS for storage and GCP for computing.

Another important aspect of cloud infrastructure for BFSI organizations is disaster recovery (DR). This refers to the ability to recover from a disaster or outage quickly. BFSI organizations need to have a DR plan that allows them to restore operations in case of an outage promptly. This can be achieved using cloud-based DR solutions such as AWS Backup and Azure Site Recovery.

In addition, BFSI organizations need to ensure compliance with various regulations, such as the General Data Protection Regulation (GDPR) and the Payment Card Industry Data Security Standard (PCI DSS). Cloud providers such as AWS, Azure, and GCP offer compliance solutions that allow organizations to meet these regulations.

How Cloud Computing is Used in Banks#

One of the main ways that banks are using cloud computing is through the use of cloud-based storage solutions. Banks must store and manage large amounts of data, including customer information, transaction records, and other sensitive information. Cloud storage solutions offer a cost-effective and scalable way for banks to store this data, allowing them to increase storage capacity as needed easily. Additionally, with cloud storage, data is stored in a centralized location, making it more secure and easier to manage.

Another way that banks are using agile and adaptive cloud computing is through the use of cloud-based applications. Cloud-based applications, such as customer relationship management (CRM) and enterprise resource planning (ERP) systems, allow banks to access and use these applications without maintaining them on their servers. This reduces the need for expensive hardware and software licenses and will enable banks to scale the number of users accessing the applications easily.

Cloud-based analytics is another important area where banks are using cloud computing. Banks use cloud-based analytics to gain insights into customer behavior, transactions, and other data. This information can be used to improve marketing efforts, detect fraud, and identify potential risks. Additionally, with cloud-based analytics, banks can access real-time data and insights, allowing them to make more informed decisions.

Banks are also using cloud computing to improve the customer experience. Banks are using cloud-based mobile banking and online banking solutions to allow customers to access their accounts from anywhere at any time. Additionally, banks are using cloud-based chatbots and virtual assistants to provide customers with 24/7 support and assistance.

Finally, banks are also using cloud computing to improve their security. Cloud-based security solutions, such as firewalls and intrusion detection systems, can be used to protect banks' networks and data. Additionally, banks can take advantage of the latest security technologies and best practices with cloud computing without investing in expensive hardware and software.

Hence, cloud computing is being used by banks in a variety of ways to improve operations, reduce costs, and increase efficiency. By leveraging the scalability and flexibility of cloud computing, banks can serve their customers better, reduce risks, and stay competitive in the ever-changing banking industry.

Challenges faced by the Banking Industry that come with cloud computing.#

Several challenges come with implementing cloud computing in the banking industry, including:

Security:#

Banking and payment sector handle sensitive financial information and must ensure that this information is protected from cyber threats. Cloud providers must meet strict security regulations, and banks must trust that the cloud provider can adequately protect their data.

Compliance:#

Banks must comply with various regulations such as the Gramm-Leach-Bliley Act and the Dodd-Frank Wall Street Reform and Consumer Protection Act. These regulations can be difficult to navigate and comply with when using cloud services.

Integration:#

Banks often have legacy systems and infrastructure that can be difficult to integrate with cloud services. This can be a significant challenge for banks looking to move to the cloud.

Reliability:#

Banks must ensure that their systems and services are always available to customers. Cloud providers must provide a high level of service availability to meet the needs of banks.

Cost:#

While cloud computing can offer cost savings, it can also be expensive, depending on the services and providers used. Banks must carefully evaluate the cost and benefits of cloud computing to ensure that it is the right fit for their organization.

Data sovereignty, data privacy, and data residency issues:#

Banks need to ensure that their data is stored in a compliant location and also should be in control of their data.

Conclusion#

BFSI organizations must have robust and reliable cloud solutions to ensure continuous operations. Several types of cloud infrastructure can be used, including public, private, hybrid, and multi-cloud. Organizations must also have a disaster recovery plan and ensure compliance with various regulations. By having a well-planned and executed cloud infrastructure, BFSI organizations can ensure their operations remain uninterrupted and their customers and partners can rely on them.

As the financial services industry continues to evolve and adapt to new technologies, many organizations are turning to cloud computing as a way to modernize their IT infrastructure and gain a competitive edge. However, not all cloud providers are created equal, and many financial services organizations are finding that a multi-cloud strategy is the best way to take full advantage of the benefits of cloud computing by minimizing the risks.

One of the main reasons why multi-cloud is becoming the go-to strategy for financial services organizations is the need for business continuity and disaster recovery. Financial services organizations handle sensitive customer data and are subject to strict regulatory requirements. A single point of failure in their IT infrastructure could have serious consequences. By spreading their data and workloads across multiple cloud providers, they can ensure that their systems will continue to function even if one provider experiences an outage or face any other issue.

The advantage of multi-cloud is the ability to comply with a wide range of regulatory requirements. Financial services organizations are subject to a variety of laws and standards, such as the General Data Protection Regulation (GDPR) and the Payment Card Industry Data Security Standard (PCI-DSS). Going for the multi-cloud option by spreading data and workload across multiple cloud providers, it becomes simple and easy to comply with these regulations by default.

Beyond business continuity and compliance, financial services organizations are also turning to multi-cloud to take advantage of the best performance options available. Quick turn-around gives an overall smooth experience to the users.

Different cloud providers have different strengths and capabilities, and by spreading their workloads across multiple providers, financial services organizations can ensure that they are taking full advantage of these capabilities. For example, one provider may be better suited for running large-scale data analytics, while another may be better for running high-performance trading systems.

Of course, cost is always a major concern for financial services organizations, and multi-cloud allows them to take advantage of different pricing models and cost-saving options offered by different providers. The savings could be reinvested by the company for some other operations.

For example, they may choose to run certain workloads on a provider that offers a pay-per-use model, while running other workloads on a provider that offers a reserved capacity model. It allows financial services organizations to be more flexible and adapt quickly to changing business needs. As new technologies become available, they can take advantage of them without being locked into a single provider.

Why is multi-cloud the first choice?#

● Geographical diversity:#

Financial services organizations often operate on a global scale and may need to comply with different laws and regulations in different regions. Multi-cloud allows them to store their data and run their workloads in different regions, which can help them to comply with local laws and regulations and reduce the risks associated with data sovereignty.

● Global reach:#

Multi-cloud enables companies to use providers with data centers in different geographic locations, providing better performance and reducing latency for global users. By having a hotspot of service at different locations in different countries they can provide their services seamlessly and smoothly to customers and service providers. By cloud, we can reach any country because it won't be required any infrastructure to provide services or be limited to any particular place. It can get a diversified audience.

● Cloud agnostic:#

Multi-cloud can also be considered as a cloud-agnostic approach, which means that organizations can select the best cloud provider for their specific use case without being limited by the technology. This allows them to leverage the best-suited provider for each workload based on the required performance, security, and cost, without the limitations of a single provider.

● Scalability:#

Multi-cloud allows financial services organizations to scale their IT infrastructure as needed, without being limited by the capabilities of a single provider. This can be especially important for organizations that need to handle large amounts of data or support high-traffic workloads.

● Customization:#

Multi-cloud allows financial services organizations to tailor their IT infrastructure to their specific needs, without being limited by the capabilities of a single provider. This can be useful for organizations that need to run specialized workloads or use specific technologies. It also enables financial services providers to act as per the latest system running at that time by providing the latest features.

● Cloud Brokerage:#

Multi-cloud enables companies to use a third-party service that can manage and optimize their cloud usage across different providers. Which allover makes it easy to calculate where and how much amount we spent with help of third-party services.

● Cloud-Native:#

It refers to the design and development of applications specifically for deployment in cloud computing environments. Multi-cloud allows companies to take advantage of the latest cloud-native technologies and practices, such as containers, serverless, and Kubernetes. By using multi-cloud, companies can take advantage of the latest cloud-native technologies and practices to improve their agility, scalability, and cost-efficiency.

The financial services industry is increasingly turning to cloud computing to shape its IT infrastructure as per present-day needs and expectations. Technology has made it necessary for everyone to adapt new strategies for staying in the market. According to a study by Accenture, 84% of financial services organizations are already using cloud computing, and this number is expected to grow in the coming years.

In conclusion, multi-cloud is becoming the first choice for financial services organizations looking to become cloud-native. It allows them to ensure business continuity, comply with regulatory requirements, take advantage of the best performance options, control costs, and adapt to new technologies. With multi-cloud, financial services organizations can have more control over their IT infrastructure and take advantage of the strengths of multiple cloud providers, while minimizing the risks associated with relying on a single provider.

Ways BFSI can thrive in dynamic technological advancements#

The banking, financial services, and insurance (BFSI) sector are facing unprecedented challenges as technological advancements continue to disrupt the industry. From digital transformation to data analytics, cybersecurity to partnerships, the BFSI sector must adapt to stay competitive.

In this article, we will explore ways in which BFSI companies can thrive in the face of these challenges. The key way that BFSI companies can thrive in the face of dynamic technological advancements is by embracing digital transformation.

Using AI, Machine Learning, Big Data, and Cloud Computing#

This means investing in technologies such as artificial intelligence (AI), machine learning, blockchain, Big Data, and cloud computing to improve operations and customer experience.

For example, using AI-powered chatbots can improve customer service and reduce costs for banks, while blockchain technology can increase transparency and security for financial transactions. By leveraging these technologies, BFSI companies can improve efficiency, reduce costs, and gain a competitive edge.

Using Data Analytics#

Another good option for BFSI companies to thrive in a rapidly changing technological landscape is by leveraging data analytics. By analysing data based on customer behaviour, market trends, and business performance, BFSI companies can gain valuable insights that can help them identify new opportunities and make more accurate decisions.

For example, data analytics can help insurers identify fraudulent claims, while banks can use data to identify potential customers for loans. By using data analytics, BFSI companies can improve the effectiveness of their marketing and sales efforts, as well as reduce risks.

Role of Cybersecurity#

Cybersecurity is also crucial for BFSI companies as they increasingly rely on digital technologies. With the increasing use of digital technologies, BFSI companies must prioritize cybersecurity to protect customer data, prevent cyber-attacks, and protect customers from any frauds or scams. This means investing in security protocols, firewalls, and intrusion detection systems, as well as training employees on best practices for data security. By doing so, BFSI companies can protect their customer's sensitive information and prevent costly data breaches.

Partnerships and Alliances#

It is important for BFSI companies to build partnerships and collaborations with tech giants to have their technological advancement. By working with fintech firms, tech companies, and other partners, BFSI companies can gain access to the newest technologies and services, as well as new markets.

For example, partnering with a fintech firm can help a bank offer new digital services to customers while collaborating with a tech company can help an insurer develop new products and services. By building these partnerships and collaborations, BFSI companies can stay ahead of the curve in an ever-changing landscape.

Innovations#

Innovation is also a key element for BFSI to thrive in the dynamic technological advancements. Developing new products and services that meet the changing needs of customers is critical for staying competitive.

For example, a bank could develop a new mobile app that allows customers to deposit checks using their smartphones, while an insurer could develop a new policy that covers damages from cyber attacks. By developing new products and services, BFSI companies can attract new customers and retain existing ones. These small innovations could make a huge impact on their overall market.

Employee Training and Development#

Investing in employee training and development is crucial for BFSI companies to thrive in a rapidly changing technological landscape. By providing employees with the skills and knowledge needed to work with new technologies, BFSI companies can ensure they have the talent they need to stay competitive.

For example, training employees in data analytics can help them make more accurate decisions, while training in cybersecurity can help them protect customer data. By investing in employee training and development, BFSI companies can ensure that they have the workforce they need to succeed in a dynamic technological landscape.

Building a Strong Digital Ecosystem#

BFSI companies should build a strong digital ecosystem by integrating various technologies and services to create a seamless customer experience. This includes leveraging technologies such as biometrics, natural language processing, and machine learning. It will make the BFSI ecosystem strong and improve the overall customer experience. BFSI can strengthen its security, privacy, and user experience by upgrading its ecosystem digitally.

Identify Emerging Technologies#

BFSI companies should stay updated about emerging technologies such as quantum computing, 5G, and the Internet of Things, and assess how they can be leveraged to improve operations or create new products and services. By adopting emerging digital technologies for services such as mobile banking, online banking, and blockchain, it can improve its customer experience and automate operations.

Digital Identity#

Implementing digital identity solutions to improve security and convenience for customers. Nowadays, we find many fake websites and frauds operating in the name of huge financial companies. Such scammers hunt down customers by spamming them with emails and SMSs. They sell collected data to the 3rd party services for financial gains. Digital identity solutions reduce these scams.

Digital Wallets#

Developing digital wallets to enable customers to store, manage, and transact with digital currency anytime. Supporting contactless payments such as NFC, QR codes, and digital wallets to improve convenience for customers and reduce the risk of fraud.

The BFSI sector is facing unprecedented challenges as technological advancements continue to disrupt the industry. By embracing digital transformation, leveraging data analytics, focusing on cybersecurity, building partnerships and collaborations, developing new products and services, and investing in employee training and development, the BFSI sector could thrive very well.

So the conclusion is like, It's important to note that BFSI companies should also be aware of the regulatory and compliance requirements that come with the adoption of new technologies. They must ensure that their operations and services remain compliant with local and international laws and regulations to avoid any legal issues. To thrive in this dynamic landscape, BFSI companies must take a strategic approach, embracing digital transformation, leveraging data analytics, prioritizing cybersecurity, building partnerships, innovating new products and services, and investing in employee training and development. By doing so, BFSI companies can stay competitive, improve efficiency and customer experience, and ultimately achieve long-term success.

For businesses managing multiple clouds, it can be difficult to optimize their budget to get the most out of their cloud investments. Cloud costs can quickly add up, so it's important to know how to effectively manage your costs. In this blog post, we'll cover the tactics you can use to help manage your multi-cloud budget and optimize your costs.

What are Multi-Cloud Budgets?#

Before moving to understand the tactics of smart budgeting for multi-cloud business, it is important to go through a basic capital expenditure over cloud computing. One unique thing about spending on cloud operations is, it varies from business to business and therefore, no model spending template can be drafted. The report from Gartner shows positive growth trends in the IaaS market doubling between 2016 - 2020. Therefore, cloud budgeting become core areas of concern for businesses to remain profitable. It is equally important to curb the waste of money when dealing with cloud-based services. Overpaying for cloud services and money getting wasted are growing financial concerns. As per industry estimates, nearly 30% to 35% of the money gets wasted when public cloud services were used.

Let us look at some of the tactics now!

Understanding Multi-Cloud Budgets#

It's important to understand the different cost models associated with different cloud providers to ensure you're maximizing your savings. When leveraging multiple cloud providers, it is important to consider the cost of the individual services, as well as the total cost of ownership. Each provider typically uses their own pricing model, such as pay-as-you-go or discounted commitment plans. Additionally, it is important to monitor usage and leverage automation to ensure you are staying within your budget. This can be accomplished through the use of tools such as AWS Cost Explorer and Google Cloud Platform's Budget API. By understanding and utilizing these strategies, it is possible to effectively manage your multi cloud budget.

Developing a clear budgeting strategy can help you optimize your use of multiple cloud services and plan for any unexpected costs. To ensure that you are effectively managing your multi cloud budget, it is important to determine which services are necessary and prioritize the use of those services. Additionally, it is essential to develop a cost estimation model that incorporates the usage of the different cloud service offerings. This model should be able to identify any potential cost overruns before they occur, so that you can take proactive steps to prevent them. Finally, it is important to review your current cloud usage on a regular basis and identify methods of reducing expenses while also ensuring that your applications continue to remain reliable and perform well. By implementing these strategies, you can create an effective budgeting plan for your multiple cloud services and protect yourself from unexpected expenses.

Establishing usage thresholds for each service can also help ensure you aren't overspending on any one cloud provider thereafter, establishing usage thresholds for each service can help ensure you aren't overspending on any one cloud provider. This will better equip you to manage your overall budget when it comes to multiple cloud services. By setting limits and monitoring your usage, you can ensure that you are staying within your allocated budget.

Establishing Clear Cloud Investment Goals#

When setting up your cloud budget, it is important to establish clear goals that will help you measure the success of your cloud investment. One of the best ways to manage a multi-cloud budget is to create a well-defined budgeting process. This will allow you to identify costs and understand when and where money is being spent in the cloud. Additionally, it is important to review budgets regularly in order to ensure that costs are kept under control. Finally, it is beneficial to utilize cost optimization strategies, such as auto-scaling, right-sizing, and spot instances, in order to ensure that you are spending resources efficiently and are not overspending on unnecessary cloud services. By following these strategies, you can ensure that your multi-cloud budget is managed carefully and effectively.

Identify which areas of your business need the most cloud investment and determine how much you are willing to invest in them. The key to successful multi-cloud budget management is to use an API-driven platform that enable you to build and manage any application with total control over cloud costs. This platform can help you quickly identify areas where spending can be optimized, connecting cost insights and business objectives in real time while leaving room for innovation. Additionally, such a platform can allow you to set guardrails around cloud costs across multiple clouds, so you are able to stay on top of your budget and adjust it as needed.

Create a plan for monitoring costs and evaluating if the investments are meeting their objectives, as well as staying within budget Moreover, creating a comprehensive plan for cost monitoring and evaluating the success of your investments is key to managing a multi-cloud budget. By having a detailed understanding of the costs associated with your cloud investments and setting up regular reviews, you will be able to ensure that you remain within your budget while also achieving the desired results. This kind of in-depth analysis will also help you identify when additional investment or adjustments need to be made.

Leveraging Cost Optimization Tools and Strategies#

Cost optimization tools and strategies can help organizations get the most bang for their buck when it comes to multi cloud budgets. Building and managing any application on a multi cloud environment requires careful budget planning. Firstly, organizations must analyze their current cloud usage in order to identify where they may be over- or under-utilizing resources. This analysis can help them understand which services are most cost effective and how to best configure the cloud environment to reduce expenses while still getting the most out of their investments. Additionally, organizations should consider implementing cost optimization tools such as analytics and cost management tools that can provide guidance on how to further optimize their multi cloud budgets. Ultimately, with the right approach, organizations can ensure that their multi cloud budgets are managed efficiently and effectively.

Utilizing cost optimization tools such as AWS Cost Explorer, Azure Price Calculator, and Google Cloud Platform Price Estimator can help reduce costs associated with cloud usage. These tools can break down usage cost and allow enterprises to have a better understanding of their costs. Additionally, budget alerts can be setup to automatically notify administrators when cloud spending reaches a certain threshold. Automated scaling of cloud resources can also be configured to reduce costs associated with over provisioning, while keeping the performance of the services up to the expectations. Lastly, enterprises should look into utilizing spot instances and reserved instances in order to reduce their overall cloud budget.

Enterprises should also consider leveraging services such as Reserved Instances and Spot Instances to lower costs associated with running applications in the cloud next, it is important for enterprises to build and manage any application, no matter the cloud platform, in a more cost-effective way.

Sustaining Long-Term Cost Savings in a Multi-Cloud Environment#

Developing a clear understanding of the cost structure and capabilities of each cloud platform can help you identify areas for potential cost savings. One of the best ways to manage a multi-cloud budget is to build and manage any application on the most cost-effective cloud platform available. It is also beneficial to create a comprehensive plan that accounts for all costs associated with each cloud platform over the long term, including data storage, computing resources, and any other services associated with the use of multiple cloud platforms. Additionally, it is essential to research and compare different providers for the best pricing and feature set that fits your needs. Lastly, assess usage patterns and consider the scalability of your applications when building a multi-cloud budget; this will help ensure you are utilizing the right resources and avoiding any unnecessary costs.

Automating processes such as resource provisioning and workload migrations can help you reduce manual labor costs and gain efficiency when managing your multi cloud budget. Additionally, leveraging tools designed to build and manage any application on multiple clouds can help you save time and money. Furthermore, using built-in management tools such as cost optimization to control resource utilization and cloud bursting to quickly scale up or down when needed can increase your overall budget efficiency. Finally, investing in a cloud management platform can enable you to monitor, manage, and secure all of your resources from one centralized location. Overall, these methods can help you significantly reduce costs and maximize your multi cloud budget.

Making use of third-party cloud management tools can make it easier to track usage and optimize your spending in a multi-cloud environment similarly, making use of third-party cloud management tools is a great way to help manage a multi cloud budget. Such tools can allow for tracking usage and help to optimize spending in a multi-cloud environment. This helps to ensure that companies are not overspending and are able to gain the most from their multi cloud budget.

Conclusion#

In conclusion, managing your multi-cloud budget can be a complex process, but with the right strategies and tactics in place, you can ensure that you're getting the most out of your cloud investments. Make sure to regularly review your cloud costs and be aware of how much you're spending on each service or resource, as this could save you a lot of money in the long run. Knowing how to optimize your multi-cloud budget can help you ensure that your business is getting the most out of its investments.

The global trend in a post-pandemic world shows that businesses are moving towards to digital environment. The increased availability of options to digitalize business management is a healthy sign for any business.

Introduction#

The invention of cloud computing techniques has already impacted the pace of transformation and transition. The benefit of having a cloud-based business certainly boosts risk-free business growth. Thus, according to new trends, business migration to cloud computing has created new demand and insights about handling business on the cloud. Among the cloud computing techniques, migration to multi-cloud is getting highly popular. Based on the success case of migration, other businesses are likely to follow migrating to cloud infrastructure.

But the migration to a multi-cloud system or for that matter any cloud computing system requires thorough background research. Migration to cloud infrastructure needs keen introspection from the business future perspective that must involve a roll-back strategy if the migration fails. Successful migration to cloud infrastructure also deals with the continuous challenges of complex computing systems. Therefore, it is desirable that businesses must gain cloud visibility before migrating to the cloud system. Every business is required to follow certain strategies before migrating to cloud infrastructure. The benefit of looking at certain key strategies is to make a risk-free transition of business on the cloud.

Cloud Migration Strategies#

The importance of setting the key strategies before migration to multi-cloud infrastructure is to mitigate the risk post-migration. It is obvious that every business will prioritize the strategies based on the business area and service delivery. The basic charting of key strategies to look at before migration helps businesses in a swift and hassle-free transfer. It also enables the optimization of resources required in the migration. A look at the five best strategic actions that every business must work on before migrating to cloud infrastructure is elaborated.

1. Pre and Post-Planning for the cloud migration#

Planning is an essential part of any business activity. Migration to cloud infrastructure requires pre-planning that starts right from the moment the idea to migrate comes to light. Planning before and after the migration is so important more than 60% of migration fails only because of a lack of planning.

• The business organizations while planning must consider the residual data and machine workload along with main operations.
• A simple and meaningful illustration of the business conditions must be completed "before" migration.
• This will help to compare to "after" migration business flow and will highlight the success or failure.
• An inventory of applications, servers, and support systems must be documented based on the machine data.
• The visualization of key performance metrics is also essential to take the business growth in a pre and post-migration assessment.

2. Monitoring Application Performance#

The monitoring of applications when shifted to multi-cloud infrastructure empowers the working efficiency of resources. This monitoring is vital to the transition-related economy. When a business decides to migrate to multi-cloud, the economic cost of migration is one of the criteria that facilitates or hinders the change-over. Hence, putting in place an effective and working customized system of monitoring the application performance will impact the outcome of the migration. NIFE as a key service provider helps monitor businesses when working on multi-cloud architecture. It shares the monthly reports of assessment with the businesses and also helps in analyzing the performance to improve productivity.

3. Establish key KPIs#

The key performance indicator (KPIs) are used to track the effectiveness of the transition to multi-cloud. The setting up of KPIs for migration to multi-cloud infrastructure will enable to replacement of larger non-functioning assets with more predictable operational activities. Businesses need to pay attention to prioritizing the scalable model with the flexibility to use cloud capabilities. The customization of KPIs as per the business requirement and assessment will generate key strategic decisions. The KPIs will be a guiding factor to ensure the cost-effectiveness of business using cloud computing strengths.

4. Codify workflows#

The business operates on a cloud system that generates and streams data signals. Such data signals carry vital customer and business information. The cloud infrastructure enables one to put an observation to flowing data and be able to collate for business insights. NIFE can collect the observed data for businesses, interpolate the data, and can provide a holistic vision for future business actions. The use of codification to monitor the workflows also enables the protection of residual data. Simultaneously also allows the technicians to code, edit, review, and revise the data flow.

5. In-place data portability and interoperability#

The changeover from one cloud to multi-cloud has changed the way data is being observed and analyzed. The business functions that are operated on multi-cloud require to be shared between various service providers. Thus, the effectiveness of data portability without compromising the authenticity of the data and the information generated. With the increasing trend to shift business to multi-cloud infrastructure, the issue of interoperability has become evident. Businesses on multi-cloud use vendors from multiple cloud systems. Hence it is important to place an organizational policy of data portability and interoperability. The effectiveness of working on multi-cloud will only be possible when data interchange is swift and secure. It is mandatory to capture the data in a seamless manner. This will be helpful during the analysis process that will help in making useful business decisions.

Summary#

The migration to multi-cloud infrastructure is an ongoing process. Businesses want to migrate to multi-cloud to reap the benefits of cloud computing. Cost-effectiveness and scalability are key attractions for businesses migrating to the cloud. But certain key strategies require adherence before moving to multi-cloud. The importance of such strategies is it offers risk-free transition of business on multi-cloud and ensures productivity.

• Planning becomes one of the key aspects of migration to multi-cloud.
• A pre and post-planning simulation is required to think accordingly about the plans are made to migrate.
• A pre and post-planning simulation shall be made available to help manage the business in pre and post-migration.
• Monitoring the application performance is a key aspect that highlights the success or failure of the decision.
• The NIFE-based monitoring application is an example of monitoring the workflow on the cloud.
• The codification of workflow will generate cost-effective business decisions using residual information.

Introduction#

The nature of technology reflects a gradual shift towards leaner, affordable, and resilient innovation. The conversion of LAN-based internet access into remote access to 5G internet has made the approach to new information smarter. This change in computing data storage devices from bulky hard drives to cloud storage. Every transformation and innovation story relates to the changing human needs. Multi-Cloud is an effective tool for future business, offering cheaper storage for databases to save data. Similarly, the multi-cloud use is diverse and unique and showcases the future applicability of multi-cloud computing.

The role of multi-cloud computing systems and processes will transform to deliver future applications aiming to change business propositions. The future of cloud computing is now hybrid and multi–cloud computing applications. The future holds more promises and new innovations within multi-cloud computing.

Future Applications of Multi-Cloud#

The future holds promises for multi-cloud computing to be developed in Next-Gen business platforms. Hence organizations are re-inventing their product platform and service delivery based on multi-cloud computing. Significantly, to adapt to safe working environments where data is created daily, multi-cloud computing techniques hold future applications. The difference between conventional and multi-cloud storage is the flexibility of business adoption.

Diverse Product and Service Application Utility#

The recent projections conducted by IBM Survey showcase that Covid-19 jitters and uncertainty in the physical workspace have accelerated the demand for multi-cloud business presence for global organizations. This is in response to creating a risk-free business to cope with future pandemics and disasters. Multi-cloud enables businesses to operate with high precision that effectively manages services and applications. The resultant use of multi-cloud offers risk-free business and better profitability. The operational cost of running a product or services on multi-cloud computing boosts the application profitability of running the business.

The multi-cloud applications help organizations scale up the deployments that may be required to enter into a new market as per the demand. As illustrated in Figure 02, businesses are using multi-cloud architecture for a variety of purposes to effectively diversify their product and services. It is evident that multi-cloud applications are offering greater freedom to businesses to increase their efficiency.

Independence Nature of Business#

The new mantra of working within the global IT business is Independence first; which means zero vendor lock-in along with a function of high integration whenever demand arises. The multi-cloud computing renders the organizational approach independent yet offers multiple vendors to select from, resulting in the use of the best possible vendor without any last-minute vendor lock-in. The future selection criteria for cloud computing is the independent nature of services offered to organizations that improve the space for course correction and innovation in vendor selection.

Automation First#

IT firms around the world are looking towards automated work processes. The pandemic period was a reminder to the IT sector that certain parts of the business work best when automated. The use of Multi-Cloud computing systems enables organizations to automate access to the information stored centrally on the cloud, making it approachable to everyone irrespective of remote locations. Multi-cloud computing offers built-in functions that help run and optimize the business activities by it, therefore helping the organization to function automatically even if the employees are fewer as well. This is in sync with the future work policies wherein technology is replacing man-enabled applications and services such as driverless cars, drones, or the use of robots.

Technology Stacks#

Cloud-computing stacks are a technology comprised of layers of cloud-computing services and components that create individual applications like a stack. Organizations thus require obtaining services based on stacks to gain maximum productivity from a single vendor. The multi-cloud selection enables organizations to avoid vendor lock-in. Thereafter, the stacking technology of multi-cloud enables organizations to work on scalability and ensure network stability offering a high degree of services. Surely, the business preferences using multi-cloud stacking will run the service components based on the vendor's expertise. It will also aim to develop effective productivity by analyzing detailed workflow patterns and tracing the delivery speed of the products and services.

Summarization#

• It is evident that the future of the computing business is hooked to multi-cloud computing systems and processes.
• Organizations across the IT sector and associated areas are adapting to the working functionality based on multi-cloud system networking.
• The effectiveness of multi-cloud computing for the future is perfectly aligned with new business development.
• Therefore organizations developing products and services are to be deployed on the multi-cloud system only to enhance customer outreach.
• The future is about managing the terabytes of data that require multi-cloud management and computing systems.
• Multi-cloud computing enables the availability of technology stacks coupled with automation features.
• Therefore marking multi-cloud computing as perfect for future applications and being the next face of cloud computing technology.

Introduction#

The multi-cloud management is an innovative solution to increase business effectiveness. Because of the custom-made IT solutions on multi-cloud used by businesses for rapid deployments, it results in greater profitability. The use of multi-cloud by large and medium size organizations is based on the advantages offered by cloud computing. The competitive edge to select from the best cloud solution provider is a unique tool for business growth. The global organizations with maximum workloads gets benefitted from multi-cloud operations. The multi-cloud management offers uniqueness to business organizations and makes their operations reliable and safe. However, a business organization can also get negative impacts from technology. There are pros and cons of multi-cloud computing for organizations moving to multi-cloud infrastructure from private cloud services.

Multi-cloud Migration Pros and Cons#

Businesses always migrate from one technolgical platform to other searching profitability. Cloud based migration is enabling businesses to open up to innovative solutions. Currently, there is an on-demand scope of migrating to multi-cloud architecture. The aim is to get benefitted from the pile of IT solutions available from across the best on the cloud. Businesses are carefully selecting the most competitive cloud management considering pros and cons simultanesouly.

Benefits of Migrating to Multi-Cloud Solutions#

There are various benefits that organizations can drive from multi-cloud management elaborated below:

Rapid Innovation#

• Modern businesses migrating to multi-cloud deployment are seeking innovation at a rapid pace that results in changing branding and scalability.
• The use of multi-cloud management offers limitless solutions to business that improves customer approachability.
• Best outcomes from the selection of best services on multi-cloud gives freedom to choose from the very best.

Risk Mitigation#

• Using the multi-cloud infrastructure the businesses are given a risk-free workability that is generated through an independent copy of the application on the cloud server.
• The use of multi-cloud deployment in case of any disruption ensures that businesses on the multi-cloud computing management are working continuously.

Avoiding Vendor Lock-In#

• This is one of the greater benefits to organizations moving their business onto multi-cloud computing management. The private and public cloud services offer restricted access to the services and capabilities.
• Hence, businesses using public or private cloud services offer a lock-In that does not generate competitiveness of the services. Thus, multi-cloud management and multi-cloud providers effectively render opportunities that enable the business to switch services reducing its dependency.

Lower Latency#

• The use of multi-cloud computing is effective in transferring data from one application to another. Migration of the business to a multi-cloud management platform offers lower latency that enables the application and services to transfer their data at a rapid pace.
• This is directly connected with the application usage and its effectiveness for the user and is an advantage to the business migrating to the multi-cloud service.

Drawbacks of Migrating to Multi-Cloud Solutions#

The following are the drawbacks that businesses had to look into when migrating to the multi-cloud management platform:

Talent Management#

• with the growing conversion of business into multi-cloud computing platforms, organizations are struggling to find the right talent to operate and function effectively on the cloud systems.
• The decision to move to multi-cloud management requires skilled people who know how to work on cloud computing systems. With the increased pace of migration to multi-cloud, there is a shortage in the market for the right talent.

Increased Complexity#

• Adding a multi-cloud management platform into the business results in taking in services from the multi vendors as a part of risk mitigation, but it also adds complexity to the business.

• Handling various operational frameworks of software used by various vendors requires knowledge and training, a level of transparency, and technical know-how.

• The cost of managing a multi-talent team comes at accost along with managing the licensing, compliance, and security of the data.

• Thus, businesses migrating to multi-cloud management need to prepare a comprehensive cloud handling strategy to restrict the operational and financial dead-load.

Security Issues#

• The bitter truth is that realizes migrating to a multi-cloud management platform system is an increased risk to data safety.
• Multi-cloud services are provided by various vendors and thus create a vulnerability of IT risks.
• There is a regular issue of access control and ID verification as reported by users.
• Thus, a multi-cloud infrastructure is more difficult to handle as compared to a private cloud.
• Encryption keys and resource policies, requires multi-layer security because of different vendor accessibility.

It is evident that the use of multi-cloud infrastructure to innovate and grow the business has resulted in large-scale migration of businesses and companies across the globe. Post-pandemic work culture and business strategies also place migrating to multi-cloud as a part of future sustainability. Subsequently, there are issues in migrating to multi-cloud management and seeking multi-cloud services from various vendors. The advantages such as risk mitigation, rapid innovation, and avoiding vendor lock-in are the biggest motivation for businesses to migrate to multi-cloud as compared to the high security risks and need for expertise and its associated cost to hire and retain the talent within an organization are some of the positives. Thus, the future belongs to the multi cloud as the benefit offered are more then negatives.

If your enterprise is looking for a way to save cloud budget, do check out this video!

Why is there a need for Cloud Computing?#

Cloud computing is getting famous as an alternative to physical storage. Various advantages enable business organizers to prefer cloud computing to other data servers and storage options. One of the most prominent reasons setting the global acceptance and upsurge in the use of cloud computing is cost-saving applications of cloud computing reducing the cost of hardware and software required at the consumer end. The versatility of cloud computing provides the option to workload data access online through the internet from anywhere in the world with restriction of access timing. The innovation in cloud computing such as the integration of paying options, and switching over to applications in an easy manner highlights the growing need for cloud computing as a future solution to computing.

The effectiveness of cloud computing is linked to its massive use as a driver of transformation interlinking artificial intelligence, the Internet of Things (IoT) with remote and hybrid working. The involvement of metaverse, cloud-based gaming technologies, and even virtual and augmented reality (VR/AR). Using cloud computing enables users to avoid investing in buying or either owning an infrastructure that facilitates complex computing applications. Cloud computing is an example of “as-a-service” that makes running servers and data centers located miles apart like a connected ecosystem of technologies.

Multi-Cloud Market and its Trends in 2022 - 2023#

Early Trends#

The rise of cloud computing in the year 2020 and 2021 promises that market trends and acceptability to use multi-cloud computing will further increase. It was post-pandemic that the focus was on digital applications for conducting business within safety limits. With the development of new technologies and capabilities in cloud computing, every organization and business house is starting to get cloud computing integrated with daily business operations. Multi-cloud computing is a system of tools and process that helps organize, integrate, control, and manage the operations of more than one cloud service that were provided by more than one service vendor. As per the reports from Gartner, the predicted spending on the usage of multi-cloud services has reached \$482.155 billion in the year 2022 which is 20% more spending than in 2020.

Innovation Requirement#

The current market management of multi-cloud is segmented on the lines of deployment and market size. The strategic geographic location and demographic trends are also shaping the growth of multi-cloud use. Multi-cloud computing is resulting in increased usage of artificial intelligence (AI), and the internet of Things (IoT). Thus, further accelerating the use of remote and hybrid working as a new business culture. The role of multi-cloud is to be an enabler to move forward swiftly with the development of new technologies such as virtual and augmented reality (AR/VR), the metaverse, cloud-based virtual gaming, and leading quantum computing as well. By 2028, it is expected that the multi-cloud market will grow to become a multimillion-USD service industry.

Trends of Multi-cloud Computing in Asian Markets#

In the Asian region, the use multi-cloud market will increase because of greater workforce dependency on computing-related businesses. International Digitial Corporation (IDC) projected that in 2023, South Asian companies will generate 15% more revenue from digital products. A major bulk of this revenue will be based on growth and the emergence of multi-cloud services. Thus, one in every three companies will conduct business and earn 15% more while working on the cloud in 2023. In 2020, every one in six companies was getting benefitted from the cloud market. The existence of cloud computing knowledge is leading the upward trends in the Asian market.

Asian and African countries have traditionally been a place of physical connection rather than virtual ones. But, the pandemic of Covid-19 has changed that perception and the cultural stigma of going away to work. Governments of India, China, Hong Kong, Thailand, and Singapore are working towards taking their workloads on virtual cloud formats. Therefore, focusing on the future resilience of the work in case of the sudden emergence of any public health disaster. Thus, multi-cloud has become a prominent driver in changing the working process and methods of business. All organizations are developing contingency planning and emergency data recovery solutions. Multi-cloud provides recovery opportunities by storing the data on separate cloud providers.

The emergence and growth of multi-cloud computing is the next revolution in the IT world. The post-pandemic trends reflect greater demand for resilient infrastructure to safeguard businesses from global calamities in the near future. Therefore, Asian and South Asian countries are taking up multi-cloud computing as an alternative to private cloud services. Small and medium organizations in Asian countries are also taking up advantage of multi-cloud computing to improve their business prospects.

Cloud use is increasing, and enterprises are increasingly implementing easy cloud deployment tactics to cut IT expenses. New digital businesses must prioritize service costs. When organizations first launch digital services, the emphasis is on growth rather than cost. However, as a new service or firm expands, profitability becomes increasingly important. New digital service businesses frequently go public while still losing money. However, attention shifts to how they can begin to increase the top line faster than expenses grow. Creating profitable digital services and enterprises requires having a plan, a cheap cloud alternative and knowing how expenses scale.

Why Cloud Deployment on Nife is profitable?#

[Nife] is a serverless and cost-effective cloud alternative platform for developers that allows enterprises to efficiently manage, launch, and scale applications internationally. It runs your apps near your users and scales computing in locations where your program is most frequently used.

Nife's Hybrid Cloud is constructed in the style of a Lego set. To build a multi-region architecture for your applications over a restricted number of cloud locations, you must understand each component—network, infrastructure, capacity, and computing resources. Manage and monitor the infrastructure as well. This does not affect application performance.

Nife's PaaS Platform enables you to deploy various types of services near the end-user, such as entire web apps, APIs, and event-driven serverless operations, without worrying about the underlying infrastructure. Nife includes rapid, continuous deployments as well as an integrated versioning mechanism for managing applications. To allow your apps to migrate across infrastructure globally, you may deploy standard Docker containers or plug your code directly from your Git repositories. Applications may be deployed in many locations as NIFE is a Multi-Cloud platform in Singapore/US/Middle East. The Nife edge network includes an intelligent load balancer and geo-routing based on rules.

How can Cloud Deployment on Nife drive business growth?#

Here are 7 ways you can use Nife's hybrid cloud to grow your business.

1. Increase your output.#

Easy cloud deployment from Nife improves productivity in various ways. For example, you may use your accounting software to conduct reports to identify which items or services sell the best and which salespeople generate the most income. The instant availability of precise, up-to-date business information and a cheap cloud alternative makes it easier to identify and correct inefficiencies inside your organization [(Asmus, Fattah, and Pavlovski, 2016)].

2. Maintain current business data.#

On NIFE, easy cloud deployment makes it easier than ever to keep data and records from all departments in one place. When a business app connects to the central database, it obtains the most recent version. When a database entry is added or altered, it does not need to be manually transferred across to other databases.

3. Protect your company's data and paperwork.#

The latest cloud data encryption technology on NIFE guarantees that all data transmitted to and from your devices is secure, even if it is intercepted by thieves. This covers all documents and communications, both internal and external.

4. Scale as necessary.#

Before investing in an on-premises IT system, you must be certain that you will use it to its maximum capacity to justify the significant initial expenditure [(Attaran and Woods, 2018)]. It also takes months of preparation and specification. NIFE's easy cloud deployment technology adapts to changing business demands significantly better than traditional IT infrastructure and is far less expensive.

5. More chores should be automated.#

Cloud task automation minimizes employee burdens, providing them with more time to be productive. Productivity software plans out the work that needs to be done in the next days and weeks and informs team members well before anything is due, allowing employees to achieve more while requiring less day-to-day supervision [(Surbiryala and Rong, 2019)].

6. Spend less money.#

Cloud computing eliminates the need for IT infrastructure, hardware, and software. This saves money on power and is a terrific way to demonstrate to your clients that you can be socially responsible while still making more money by using cheap cloud alternatives [(Shah and Dubaria, 2019)].

7. Hire fewer programmers and IT personnel.#

The less equipment you need to maintain on-site, the better. You may get started with Nife's cloud computing by sending an email to their customer care staff.

Conclusion#

The cost of easy cloud deployment is determined by the company you select and the services you require. You must decide which cloud type is ideal for your company, how much data you will save, and why you are transferring to the cloud.

NIFE's Hybrid Cloud Platform is the quickest method to build, manage, deploy, and scale any application securely globally using Auto Deployment from Git. It requires no DevOps, servers, or infrastructure management and it's the cheap cloud alternative and Multi-Cloud platform in Singapore/US/Middle East.

Learn more about Hybrid Cloud Deployment.

This blog will explain the scope and future of Smart Cities in Singapore and India.

The future of "smart" cities begins with people, not technology. Cities are becoming increasingly habitable and adaptive as they become innovative. We are just witnessing what smart city technology can achieve in the urban environment.

Introduction#

According to [Smart City Index (2022)],

"An urban setting that uses a wide range of technological applications and executions for the enhancement and benefit of its citizens and reduce the urban management gaps is defined as a Smart City."

Singapore was ranked the top smart city in the world, followed by Helsinki and Zurich. India, however, lost its position in the top 100 list for 2020. It could be a result of pandemic-induced halts and stringent lockdowns applications in Indian cities.

Smart cities in the post-pandemic era are more relevant. It is especially considering the opportunities provided by smart city solutions in the management and effective service delivery for healthcare, education, and city management [(Hassankhani et al., 2021)].

Smart City Solutions#

Rapid urbanization has necessitated the development of smart city solutions. According to [(Elfrink & Kirkland, 2012)], future smart cities will be the facilitators of speeding economic growth and smart city infrastructure.

Smart City solutions extend across various domains.

Smart Parking#

• There are three types of smart parking solutions for Smart Parking:
  • ZigBee sensor-based
  • Ultrasonic sensor-based
  • Wi-Fi camera-based

which caters to street parking, interior parking, and multi-level parking.

• The Car Parking Occupancy Detection and Management system employs field-mounted Wi-Fi-based cameras. It is an end-to-end solution that is durable, dependable, and cost-effective.

Smart Traffic Management#

The Smart Traffic Management system provides centralized traffic lights and sensors that govern traffic flow across the city in response to demand. It includes the following:

• The smart vehicle inspection system
• System of Junction Control
• System for Counting Vehicles
• Junction Control Unit (JCU)

Smart Lights#

The cost-efficient rays of light from an innovative, networked street lighting solution illuminate the effective way to a future of a Smart City.

Smart Street Lighting Characteristics or Solutions:

• Maintenance Planning
• ON / OFF autonomy
• Grid Monitoring, Optimization, and Reporting
• Integrations of Smart City Platforms
• Installations are quick and inexpensive
• Communication Technology Agnostic

Smart Governance#

Smart Governance combines smart city technology with creative approaches to improve government service delivery and citizen participation in policy development and implementation [(Tan & Taeihagh, 2020)]. This approach, when used successfully, enables responsive, transparent, and inclusive policy decisions.

Smart City Solutions for e-Governance:

• The Citizen Portal
• Residential Data Hub for the State
• Monitoring of Service Desk Infrastructure
• Billing Administration
• E-Procurement
• Project administration
• Facility administration
• Election Details
• Monitoring of the road
• Management of Encroachment
• Job administration
• Monitoring of Parking Meters
• Fleet administration
• Monitoring of Road Sweeping
• Dashboard for City Performance

Smart Cities in India#

Smart city projects in India have been going on since 2014. Solutions include using digital mobile applications to provide beneficial services to everyday citizens, digital payment systems for government facilities and non-government services, and incorporating digital databases to manage the negative effects of urbanization.

Indian IoT smart cities like Delhi and Mumbai are facing uncontrolled urbanization and a crunch in public infrastructure. The government of India sees a possibility of developing IoT smart cities, effectively providing the roadmap for other cities to join the bandwagon as a part of growing smart cities in India. However, infrastructure is a primary requirement for growth.

The use of smart city technology in producing clean energy, clean energy consumption, and waste management requires the development of smart city infrastructure.

Smart Cities in Singapore#

Singapore is ranked 1st on the list of smart cities in the world. Smart city infrastructure, such as the decentralization of wastewater to produce clean potable water, smart cities in Singapore's infrastructure to create clean transportation, and enabling the participation of citizens in regular city management. These make Singapore a model for smart city solutions.

The innovative solution made for the smart city has enabled Singapore to become a nation that has always been among the top three countries leading smart cities in the world. Technology transfer, especially in sustainable transport, will be a hallmark of technology-driven collaboration between India and Singapore.

Singapore uses this infrastructure for sustainable transport that relies heavily on digitalization, making Singapore an IoT smart city.

Conclusion#

The potential of IoT is limitless. Urban data platforms, big data, and artificial intelligence can convert our urban centers into smart, sustainable, and efficient environments with large-scale implementation, deliberate deployment, and careful management.

The shared use of information is the key to the success of all industries, from healthcare to manufacturing and transportation to education. Our next-generation smart cities will be more innovative than ever by collecting data and implementing real solutions.

In today's article, we'll go over 7 Proven Methods for Addressing DevOps Challenges.

Dev and Ops have cemented their place in the global software development community and are being adopted by an increasing number of organizations worldwide. DevOps effectively speeds up the resolution of certain types of problems and challenges that may arise during a project's lifecycle. DevOps as a Service in Singapore focuses on leveraging the best DevOps practices and tools to fast-track your cloud adoption.

Proven Approaches to Addressing Dev and Ops Challenges#

While Dev and Ops may introduce security flaws and compatibility issues among SDLC teams, there are ways to overcome these obstacles.

Consider implementing the following methods in your organization to strengthen DevOps security while maintaining a balance between different teams and DevOps as a Service for agility.

1. Implement Security-Oriented Policies#

Governance implementation and good communication are critical in creating comprehensive security settings. Develop a set of cybersecurity processes and regulations that are simple, easy to understand, and transparent in areas like access restrictions, software testing, gateways, and configuration management.

The notion of "Infrastructure as Code" (IaC) is central to DevOps. IaC eliminates environmental drifting in the workflow. Teams must maintain the parameters of each application area without IaC. IaC-integrated DevOps teams collaborate with a consistent set of security standards and tools to assist infrastructure and ensure safe, rapid, and scalable operations [(Tanzil et al., 2022)].

2. Adopt a DevSecOps Approach#

Encourage cross-functional partnerships across the DevOps lifecycle to ensure effective DevOps security. DevOps teams should collaborate and actively engage in the development lifecycle to achieve mutual security goals.

DevSecOps combines cybersecurity functions with governance to decrease the risk of security breaches caused by lax account restrictions and other flaws [(Nisha T. N. and Khandebharad, 2022)]. It goes beyond technical tools and software to ensure that security is a fundamental tenet of the company. DevSecOps encourages teams to understand and implement core security principles.

3. Use Automation to Increase Speed and Scalability#

Automation is critical for developing secure applications and environments. It mitigates the risks associated with manual mistakes and reduces vulnerabilities and downtime.

Effective automated technology and techniques are essential for security staff to keep pace with DevOps as a Service teams [(Jamal, 2022)]. Automated tools can be used for configuration management, vulnerability assessments, verification management, and code analysis.

4. Effectively Manage Vulnerabilities#

Incorporating security from the start of the SDLC helps in the early discovery of faults and vulnerabilities. Implement an effective vulnerability management system to track and prioritize the resolution of each vulnerability (remediation, acceptance, transfer, etc.).

Successful vulnerability management programs regularly adapt to comply with the latest risk reduction goals of the organization's cybersecurity rules and regulations.

5. Comply with the DevOps Lifecycle#

DevOps refers to the agile interaction between development and operations. It is a method followed by development teams and operational engineers throughout the product's lifecycle [(P P, 2019)].

Understanding the DevOps lifecycle phases is crucial to learning DevOps as a Service. The DevOps lifecycle is divided into seven stages:

• Continuous Development
• Continuous Integration
• Continuous Testing
• Continuous Monitoring
• Continuous Feedback
• Continuous Deployment
• Continuous Operations

6. Implement Efficient DevOps Secrets Management#

Remove private data such as credentials from code, files, accounts, services, and other platforms for effective DevOps secrets management. When not in use, store passwords in a centralized password safe.

Privileged password management software ensures that scripts and programs request passwords from a centralized password safe. Develop APIs in the system to gain control over code, scripts, files, and embedded keys.

7. Implement Efficient Privileged Access Management#

Limiting privileged account access can greatly reduce the chances of abuse by internal and external attackers. Enforce a restrictive privileged model by limiting developers' and testers' access to specific development, production, and management systems.

Consider deploying advanced privileged access management systems, such as OpenIAM, to automate privileged access control, monitoring, and auditing across the development lifecycle [(Sairam, 2018)].

Conclusion#

The extended DevOps platform has propelled enterprises forward by delivering efficient solutions that aid in faster delivery, improve team communication, and foster an Agile environment.

While DevOps as a Service offers numerous benefits, it also presents challenges. Integrating security early in the DevOps lifecycle ensures that it is embedded at the core of the system and maintains its effectiveness throughout the product's lifespan. This approach protects the code against data breaches and cybersecurity threats.

Which is preferable: DevSecOps or DevOps? While the two may appear quite similar, fundamental differences will affect IT and business performance and your ability to go forward with the appropriate application development framework for your firm.

In this article, we will look at the similarities and differences between DevOps and DevSecOps, as well as everything you need to know.

What is DevOps?#

DevOps is a synthesis of cultural concepts, practices, and tools designed to accelerate the delivery of applications and services (Leite et al., 2020). The method enables firms better to serve their consumers, such as Cloud DevOps. We do not separate development and operations teams from each other in a DevOps approach. We sometimes combine these groups into a single group where developers work across the DevOps lifecycle, from development to testing and deployment.

What is DevSecOps?#

DevSecOps optimizes security integration across the DevOps lifecycle, from basic design to validation, installation, and delivery. It resolves security vulnerabilities when they are more accessible and less expensive to fix. Furthermore, DevSecOps makes application and security architecture a shared responsibility for the development, security, and IT task groups rather than the primary responsibility of a security silo.

What is the connection between DevOps and DevSecOps?#

Culture of Collaboration#

A collaborative culture is essential to DevOps and DevSecOps to meet development goals, such as quick iteration and deployment, without jeopardizing an app environment's safety and security. Both strategies entail consolidating formerly segregated teams to enhance visibility across the application's lifetime - from planning to application performance monitoring.

Automation.#

AI has the potential to automate phases in application development for both DevOps and DevSecOps. Auto-complete code and anomaly detection, among other devices, can be used in DevOps as a service. In DevSecOps, automated and frequent security checks and anomaly detection can aid in the proactive identification of vulnerabilities and security threats, especially in complex and dispersed systems.

Active surveillance.#

Continuously recording and monitoring application data to solve problems and promote improvements is an essential component of DevOps and DevSecOps methodologies. Access to real-time data is critical for improving system performance, minimizing the application's system vulnerabilities, and strengthening the organization's overall stance.

What distinguishes DevOps from DevSecOps?#

DevOps is primarily concerned with the collaboration between development and testing teams throughout the application development and deployment process. DevOps teams work together to implement standardized KPIs and tools. A DevOps strategy aims to increase deployment frequency while ensuring the application's consistency and productivity. A DevOps engineer considers how to distribute updates to an application while minimizing disruption to the client's experience.

DevSecOps originated from DevOps as teams discovered that the DevOps paradigm did not address security concerns adequately. Rather than retrofitting security into the build, DevSecOps arose to incorporate security management before all stages of the development cycle. This technique places application security at the start of the build process rather than after the development pipeline. A DevSecOps expert uses this new technique to ensure that apps are secure against cyberattacks before being delivered to the client and remain safe during application upgrades.

What activities differentiate DevOps and DevSecOps?#

• Continuous Integration
• Continuous delivery and continuous deployment
• Microservices
• Infrastructure as code (IaC)

The DevSecOps strategy includes the following aspects in addition to:

• Common weakness enumeration (CWE)
• Modeling of threats
• Automated security testing
• Management of Incidents

DevOps to DevSecOps transition#

Before making any modifications to your development process, get your teams on board with the concept of DevSecOps. Ensure that everyone understands the importance and advantages of protecting apps immediately and how they might affect application development.

Choose the best combination of security testing techniques#

The majority of security testing methodologies are available. SAST DAST IAST RASP, for example [(Landry, Schuette, and Schurgot, 2022)].

Create Coding Standards.#

Evaluating code quality is an important aspect of DevSecOps. Your team will be able to quickly safeguard its code in the future if it is solid and normalized.

Protect Your Application.#

Rather than attempting to protect the expanding perimeter, secure apps that run on dispersed infrastructure [(Landry, Schuette, and Schurgot, 2022)]. As a result, an implicit security strategy is more straightforward in IT organizations and strengthens your security in the long run.

Conclusion#

Should you use DevSecOps practices? There are, as we believe, no valid reasons not to. Even organizations that do not already have specialized IT security departments may have them coordinate a substantial number of the techniques and policies outlined above. DevSecOps may continuously improve the security and reliability of your software production without overburdening the development lifecycle or putting organizational assets at risk.

The cloud hosting industry's growth pace continues to accelerate, with new developments becoming more interesting and enjoyable. The gaming industry is also jumping on board; cloud gaming entails hosting and processing games on cloud gaming servers.

In this blog, we will list down top cloud gaming servers for a better gaming experience.

What is Cloud Gaming?#

Cloud gaming is a type of internet or cloud gaming service that allows you to play video games over remote cloud gaming servers. Cloud gaming eliminates the need to download the game to your local device; instead, it streams straight to your device and remotely plays the game from the cloud.

How does Cloud Gaming function?#

Cloud gaming services execute it on their servers, which are outfitted with high-end graphics RAM [(Yates et al., 2017)]. The game will then respond to your orders, and each frame will be broadcast directly to your smartphone. If you have a solid internet connection, the end-user experience is fairly comparable to traditional gaming.

Cloud Gaming Servers vs. Cloud Gaming Services#

A widespread misunderstanding is that Cloud Gaming Services and cloud gaming servers are synonymous. While there are some parallels between the two, they are essentially extremely distinct. Cloud gaming servers are a service used by game developers to manage members on their platforms All online multiplayer games require game servers to receive and reply to user replies.

Cloud Gaming Services, on the other hand, is a consumer-centric solution that allows you to stream any game of your choosing. After paying their subscription costs, cloud gaming providers often offer a variety of games from various genres that you may play.

Benefits of Cloud Gaming Servers#

The following are the benefit of cloud game servers:

• Advanced processors and SSDs
• High traffic handling
• Increased uptime and bandwidth flexibility
• No overheating concerns.
• Smooth voice interactions.
• Quick assistance
• Many plugins, modifications, and gameplay environments.
• Switching between games and simple control panels

Top Cloud Gaming Servers#

The following list of Cloud Game Servers to help you decide which one offers the finest mix of characteristics.

ScalaCube#

ScalaCube, a well-known company in the cloud game server hosting industry, is an ideal choice for you. It provides gaming servers for Minecraft, Minecraft PE, ARK, Rust, and Hytale. ScalaCube provides limitless and unrestricted bandwidth with no throttling.

HostHavoc#

HostHavoc is another well-known brand in the cloud game server hosting industry. Their gaming servers have sophisticated features and bespoke tools that are continuously updated alongside mod and game updates. With HostHavoc, you may pick from over 25 different games.

Cloudzy#

With Cloudzy's distinctive hosting options, you can set up your high-performance gaming servers. They provide gaming servers that run on both Windows and Linux. For extremely low pricing, you may receive a game hosting solution with ultra-high bandwidth, NVMe storage, and 1 Gbps connection speeds.

OVHcloud#

OVHcloud's dedicated servers provide the highest performance and stability for online gaming. Their servers are built on 3rd generation AMD Ryzen CPUs with ZEN-2 architecture to provide players with a lag-free online gaming experience. They can efficiently handle video and image processing, concurrent jobs, and multiplayer gaming.

Google Cloud#

Host your games on Google Cloud game servers for an uninterrupted gaming experience. With its solid worldwide infrastructure and no negative impacts on performance, server maintenance is straightforward here. Their gaming servers may operate at a maximum speed of 3.8 GHz.

Citadel Servers#

Choose Citadel Servers as your gaming server hosting partner to play your games without worrying about frequent delays and crashes. The hosting service fits all of the required characteristics of gamers, whether it is performance, server quality, or dependability. Citadel Servers provides server security with 24/7 network monitoring and anti-DDoS protection.

Amazon GameLift#

Use Amazon GameLift's gaming server hosting, which uses AWS and its capabilities to provide optimal performance, minimal latency, and cost savings. Take your game to the next level with dedicated servers that expand, install, and run rapidly.

Vultr#

Using Vultr's server hosting options, you can deploy high-quality gaming servers with a single click. After you click the deploy button, they will orchestrate the Vultr cloud platform and distribute your instances throughout the selected data centre.

So you Start#

Hire a gaming server from So you Start and feel the real power of innovation and organizational performance. They provide excellent specs and low latency.

Conclusion#

The ever-changing gaming world is reaching new heights to help gamers discover new experiences and pleasures. To make things even simpler for you, technology companies provide complex cloud game servers with amazing features and functions, allowing you to play with anybody on the globe and have an unrivaled gaming experience.

So, immediately acquire your cloud gaming server from any platforms listed above.

Get to know how Nife's Hybrid Cloud Platform makes the life of developers so easy-going, with

Let's start with the basics.. So what is DevOps?

DevOps refers to the techniques that development and IT operations teams use to speed and expand software delivery. These approaches include automation, continuous integration, development, testing, and infrastructure as code implementation.

Optimize your Development process with these free cloud platforms.

So what is Nife ?#

Nife is a Singapore-based Unified Public Cloud Edge best cloud computing platform for securely managing, deploying, and scaling any application globally using Auto Deployment from Git. It requires no DevOps, servers, or infrastructure management. Nife's Hybrid Cloud Platform can deploy all your applications instantly. Nife is a serverless platform for developers that allows enterprises to efficiently manage, launch, and scale applications internationally. It runs your apps near your users and grows to compute in cities where your programme is most often used.

Features of the Nife Hybrid Cloud Platform are:#

• Deploy in Seconds - Deploy your app using Docker images, or connect to your GIT repository and deploy it manually.

• Run globally in a Single Click - Run your applications in one or more of our locations, or link your infrastructure. With 500 Cloud, Edge, and Telco sites, you can go worldwide.

• Auto Scaling Seamlessly - Any region or place at the nearest endpoint is at your fingertips.

Salesforce Heroku

Heroku is a cloud application platform that integrates computation, data, and workflow with a developer experience focused on productivity. The platform enables business teams to deliver trusted client experiences at scale in the shortest amount of time.

Recently Heroku announced that the Heroku Postgres (10K rows, $5/month) and Heroku Data for Redis® (25 MB, $3/month) now have Mini plans. New plans will be available before Heroku's free product offerings are phased out on November 28, 2022.

Render

Render is a comprehensive platform for building and running all of your applications and websites, complete with free SSL, a worldwide CDN, private networks, and Git auto deployments. Recently Render has stopped the free plans for students and developers. The free plan only offers email support and community support while it has three paid plans named ‘All paid plan, Enterprise Plan and Premium Plan' with many paid features.

Cloudways

Cloudways is a managed hosting company that prioritises performance and ease of use. Cloudways handles all aspects of server administration, from simple server and application deployment to continuous server maintenance, so you can focus on expanding your business. Cloudways' main selling point is choice - the option of cloud providers, the choice of hosting practically any PHP-powered application, the choice of utilising a premium or free SSL, and the choice of developer and agency-focused processes.

The entry-level charge of Cloudways is $10.00 per month.

Plesk

Plesk's goal is to make web professionals' life easier so they may focus on their primary business rather than infrastructure administration. Automation and control of domains, mail accounts, web apps, programming languages, and databases are key Plesk platform capabilities. Providing a code-ready environment as well as excellent security across all layers and operating systems.

The entry-level charge of Plesk is $9.90

Platform.sh

Platform. sh is a contemporary Platform as a Service (PaaS) for building, running, and scaling websites and online applications. Platform.sh contains a varied library of development languages and frameworks, built-in tools to manage application lifecycle at scale, and flexible workflows to enable teams to create together, unlike managed hosting providers, IaaS providers, or traditional DevOps tools. Platform.sh enables enterprises to develop more quickly, reduce time to market, increase collaboration, and shift investment from infrastructure to customer benefit.

The entry-level charge of Platform.sh is $10.00

Zoho Creator

Zoho Creator is a low-code application creation platform that helps organisations digitise their processes without the headache of traditional programming. The platform enables organisations of all sizes to manage their data and operations, gain insights from their data, and effortlessly integrate with their existing software. Create custom forms, set up processes, and design informative pages in minutes to get your app up and running. More than 13,000 enterprises and over 7 million people worldwide rely on us as their technology partner.

The entry-level charge of Zoho Creator is $25 per month.

Glitch

Glitch is a browser-based collaborative programming environment that deploys code as you type. Glitch may be used to create everything from a basic webpage to full-stack Node apps. Glitch is a fantastic IDE and hosting platform, far superior to one of its primary competitors. The only issue with the Glitch is that non-static projects "sleep" after a while. That means you have to wait for it to "wake up," which might take up to a minute.

Conclusion#

Nife is the best free cloud platform for DevOps Developers as compared to others, It offers a free cloud platform with many features. Nife PaaS Platform enables you to deploy various types of services near the end-user, such as entire web apps, APIs, and event-driven serverless operations, without worrying about the underlying infrastructure.

Are you in search of a Hybrid Cloud Platform, which can help you build, deploy, and scale apps seamlessly, within less time span? Nife offers it all! Read on.

The cloud profoundly alters how we develop and operate apps. The rate at which DevOps make updates to their goods and services has been dramatically influenced by digital transformation. With over 500 million new apps projected to be produced in the next years, DevOps must strike a balance between managing the latest technology and developing new features.

Developers are crucial to today's environment, and the job you perform is critical to fuelling enterprises in every industry. Each developer and development team brings new ideas and creativity to the table. Our goal with Nife's Hybrid Cloud Platform is to serve as the foundation for all of this innovation, empowering the whole community as they construct what comes next. Using Nife's Hybrid Cloud Platform design patterns will help you achieve the agility, efficiency, and speed of innovation that your organization requires.

Nife's Modern Architecture opens up new options

Organizations throughout the world are focusing their main business goals on innovation, customer happiness, and operational efficiency. To achieve these objectives, businesses must rely on their applications to pave the way.

The following list could be useful for DevOps in Modern architecture using Nife's Hybrid Cloud Platform

Modern apps should be accelerated#

With Nife, you can help your firm innovate, cut expenses, speed time to market, and increase dependability.

Create new applications from scratch.#

Nife's application development is a powerful method for designing, producing, and managing cloud software that improves the agility of your development teams as well as the stability and security of your applications, allowing you to build and distribute better products more quickly. Get professional advice and understand fundamental principles to help you progress faster now.

Adopt a cutting-edge DevOps model.#

You may transfer resources from business as usual to distinguishing activities with deep customer value by using NIFE services, methods, and strategies that allow innovation and agility. Learn how NIFE can help you bring your builders, developers, and operations closer together so you can create, deploy, and innovate at scale.

Mitigate to update your applications.#

Many firms are upgrading to maximize corporate value. Discover NIFE's best practices and discover how to relocate and upgrade your business-critical apps now for increased availability, quick deployment, reduce DevOps investment and improved productivity.

Hybrid Cloud Platform: Nife's cloud-native designs enable large-scale innovation.#

At NIFE, cloud-native is at the heart of application innovation and Modern architecture. When we talk about cloud-native, we mean, reducing DevOps investment, the latest technology, and development processes that enable enterprises to design and deploy scaled apps easily. The speed and agility of cloud-native in NIFE are enabled by certain core pillars such as NIFE's PAAS Platform, entire web apps, APIs, and event-driven serverless functions that are proximate to the end-user without requiring them to worry about the underlying infrastructure.

The following are the characteristics of Nife's Hybrid Cloud Development and quick deployment:

Comprehensive automation Scale and adaptability Consistent knowledge Security with speed "Code to cloud" simplified Cost reduction

How Does Nife's Hybrid Cloud Platform Work?#

Nife's Hybrid Cloud Platform offers access to on-demand robust infrastructure from a global array of providers to seamlessly deploy any application anywhere. Nife includes rapid, quick deployment, reduce DevOps investment as well as an integrated versioning mechanism for managing applications. To allow your apps to migrate across robust infrastructure globally, you may deploy normal Docker containers or plug your code straight from your git repositories.

Deploy in Seconds#

Deploy your app from Docker images, or connect your GIT repository and simply deploy

Run globally in a Single Click#

Run your apps in some or all of the growing fast expanding regions or connect your robust infrastructure. Go global with 500 Cloud, Edge, and Telco locations.

Auto Scaling Seamlessly#

Any growing fast expanding region, any location at the closest endpoint at fingertips.

Nife's Hybrid Cloud Platform's strength and scalability#

The services provided by Nife's Hybrid Cloud Platform, as well as the underlying cloud architecture that lets you focus on creating and releasing code, distinguish it as a development platform and ecosystem. You may build on and exploit a full cloud-native platform, including containers, PaaS Platform APIs, event-driven serverless functions, and a developer-friendly serverless platform.

Conclusion on the Advantages of a Hybrid Cloud Platform#

Nife is a serverless platform for developers that allows enterprises to efficiently manage, launch, and scale applications internationally. It runs your apps near your users and grows to compute in cities where your program is most often used. Nife PaaS Platform enables you to deploy various types of services near the end-user, such as entire web apps, APIs, and event-driven serverless operations, without worrying about the underlying robust infrastructure. Applications may be deployed in growing fast expanding regions spanning North America, Latin America, Europe, and the Asia Pacific. The Nife edge network includes an intelligent load balancer and geo-routing based on rules.

Development and operations are critical aspects of every software company. Your company's success depends on effectively coordinating these roles to increase software delivery speed and quality. DevOps as a service is also crucial to delivering software more quickly and efficiently.

Development and operations teams often operate in isolation, but DevOps acts as a bridge to enhance cooperation and efficiency.

Why Does DevOps Matter in Modern Business?#

Implementing DevOps methods successfully in your firm can substantially influence efficiency, security, and corporate cooperation. According to the 2017 State of DevOps Report, firms that use DevOps principles spend 21% less time on unplanned work and rework and 44% more time on additional work, resulting in improved efficiency (Díaz et al., 2021).

8 Reasons Why DevOps is Essential for Modern Businesses#

1. Reduced Development Cycles#

Companies thrive by innovating more quickly than their competition. The primary goals of DevOps are automation, continuous delivery, and a short feedback loop, similar to Microsoft Azure DevOps. Immediate and constant feedback allows for speedier releases. In Cloud DevOps, merging development and operations activities results in the rapid creation and distribution of applications to the market [(Khan et al., 2022)]. The overall advantage is a shorter cycle time to fully realize an idea, with superior quality and precise alignment.

2. Reduced Failure Rates of Implementation#

DevOps automation encourages regular code versions, leading to easier and quicker identification of coding errors. Teams can use agile programming techniques to reduce the number of implementation failures (Maroukian and Gulliver, 2020). Recovery from mistakes is faster when development and operations teams collaborate, addressing issues collectively.

3. Continuous Improvement and Software Delivery#

Implementing DevOps principles enhances software quality while releasing new features and enables rapid changes. Continuous Integration and Continuous Deployment (CI/CD) involves making incremental changes and swiftly merging them into the source code, as seen in Azure DevOps. This approach allows software to reach the market faster while addressing consumer complaints promptly. [DevOps as a service] fosters higher quality and efficiency in continuous release and deployment.

4. Improved Inter-Team Communication#

DevOps automation enhances business agility by promoting a culture of cooperation, effective communication, and integration among all global teams within an IT company. The DevOps culture values performance over individual ambitions, making procedures more transparent and allowing employees to learn quickly and impact the business significantly.

5. Increased Value Delivery Scope#

Using DevOps as a service fosters a continuous delivery environment, focusing on innovations and better value generation through digital transformation (Wiedemann et al., 2019). This approach ensures that work is adequately integrated and managed in a conducive environment.

6. Reduced Deployment Time#

DevOps methods improve the effectiveness of building new systems by incorporating feedback from developers, stakeholders, and colleagues (Plant, van Hillegersberg, and Aldea, 2021). This approach results in consistent execution and faster deployment compared to competitors.

7. Faster Response#

One of the primary benefits of Cloud DevOps' continuous deployment cycle is the ability for firms to iterate rapidly based on consumer feedback and evaluations. This enhances the ability to manage uncertainty and speeds up procedures.

8. Reduces Waste#

Enterprises that adopt lean practices and iterate quickly use resources more effectively and minimize waste. DevOps as a service helps firms reduce operational inefficiencies by shifting various responsibilities to the development team.

In the previous decade, the idea and evolution of DevOps have drastically altered the way IT teams work. When small and big teams convert from traditional software development cycles to a DevOps cycle, they see a difference in terms of quicker innovation, enhanced collaboration, and faster time to market.

We will discuss DevOps as a Service to optimise the Ops resources including DevOps as a Service in the Singapore region and finally answer “how to optimise Ops resources by collaborating with an extended DevOps platform” in this blog.

What is a DevOps platform?#

A [DevOps platform] integrates the capabilities of developing, securing, and running software in a single application. A DevOps platform enables enterprises to optimise their total return on software development by delivering software more quickly and efficiently, while also improving security and compliance.

How to optimise the Ops resources in Extended DevOps Platforms?

DevOps teams are turning to the cloud to optimise their tech stacks and to build and deliver new solutions continually. Extended DevOps Platform teams may have complete visibility into their cloud infrastructure.

The three important areas for Optimising Ops resources with Extended DevOps Platforms are listed below.

Resource Utilization#

The cloud is perfect for fostering fast innovation since teams may add and delete instances and other resources as needed to meet business needs. This flexibility in the cloud assists DevOps in particular. A cloud management platform helps DevOps teams reallocate, resize, and even alter Reserved Instances (RIs) so that they always have the correct workload [(Alonso et al., 2019)].

Cost Management#

The cloud is perfect for enterprises that use varying amounts of data. But, regardless of the size of the budget, no one likes a surprise charge at the end of the month. DevOps teams may better manage and optimise their cloud cost by tackling resource consumption first. The correct automation solutions will assist them in locating these cost reductions without the need for time-consuming manual assessments.

Security & Compliance#

Cloud security is a critical responsibility for every sort of enterprise, including DevOps. Creating and installing the necessary security measures is only the beginning. DevOps teams must regularly monitor their cloud infrastructures to regulate and optimise cloud security. DevOps cloud optimization should also entail detecting any vulnerable areas in the development pipeline, particularly when developing or improving security features.

DevOps as a Service to optimize the Ops resources

DevOps as a Service provides full-service consulting and engineering services ranging from audit and strategy planning to project infrastructure evaluation and development. DevOps as a Service can assist you in expanding or contracting SDLC sections based on your operational requirements. Simultaneously, using on-demand, low-cost DevOps as a service may free up your in-house full-time personnel to focus on more important activities.

Extended DevOps Platform professionals will handle all requirements clarification, risk and opportunity identification, architecture creation, automation and IaaC implementation, and other duties. Instead of doing it yourself, you will receive a thorough roadmap established by specialists, as well as core infrastructure with configured pipelines ready for support administration and growth.

DevOps as a Service in Singapore to optimize IT resources.#

Businesses and DevOps as a Service in Singapore that incorporate security inside DevOps give better value, more responsiveness, and faster service delivery as a collaboration between software development and IT operations teams. The CI/CD pipeline, which enables more dependable and consistent code modifications, is the operational philosophy that raises the standard for Singaporean DevOps teams. NIFE Cloud Computing is among the leading DevOps as services in Singapore.

Recommendations for Optimizing Ops Resources Extended DevOps Platform#

Release often.

DevOps "increase an organization's capacity to deploy applications and services at high velocity," therefore releasing frequently is more than a nice to have; it's essential to the overall function of an extended DevOps Platform. Small additions, such as code modifications and bug repairs, are a fantastic place to start a fast release process since they can be implemented without significantly affecting the overall user experience.

Create a unified code base.

One method for not just streamlining DevOps but also making frequent releases easier is to standardize a single code base. Instead of having many code bases to pull from for various portions of the product or separate development teams, a single code base may make iterating and testing easy for everyone.

Scaling Automation

It may be difficult to believe, but DevOps may be effective with or without humans. In reality, while improving DevOps, you should analyse where automation can replace human involvement.

Engineers should be made responsible.

Putting engineers in charge of the final code push ensures that everything runs well and that any post-deployment issues are identified immediately.

We have access to a common pool of computer resources in the cloud (servers, storage, applications, and so on) when we use cloud computing. You just need to request extra resources as needed. Continue reading as we discuss the various types of cloud deployment models and service models to assist you in determining the best option for your company.

What is a cloud deployment model?#

A cloud deployment model denotes a specific cloud environment depending on who controls security, who has access to resources, and whether they are shared or dedicated. The cloud deployment model explains how your cloud architecture will appear, how much you may adjust, and whether or not you will receive services [(Patel and Kansara, 2021)]. The links between the infrastructure and your users are also represented by types of cloud deployment models. Because each type of cloud deployment model may satisfy different organizational goals, you should choose the model that best suits the approach of your institution.

Different Types of Cloud Deployment Models#

The cloud deployment model specifies the sort of cloud environment based on ownership, scalability, and access, as well as the nature and purpose of the cloud [(Gupta, Gupta and Shankar, 2021)]. It defines the location of the servers you're using and who owns them. The cloud deployment model describes the appearance of your cloud infrastructure, what you may alter, and whether you will be provided with services or must design everything yourself.

Types of cloud deployment models are:

Public Cloud Deployment#

Anyone may use the public cloud to access systems and services. Because it is exposed to everybody, the public cloud may be less secure. The public cloud is one in which cloud infrastructure services are made available to the general public or significant industrial organizations over the internet. In this deployment model, the infrastructure is controlled by the organization that provides the cloud services, not by the user.

Private Cloud Deployment#

The private cloud deployment approach is opposed to that of the public cloud. It is a one-on-one setting for a single user (customer). It is not necessary to share your hardware with anyone. The contrast between private and public clouds is in how all of the hardware is handled. In this deployment model of cloud computing, the cloud platform is deployed in a secure cloud environment secured by robust firewalls and overseen by an organization's IT staff.

Hybrid Cloud Deployment#

Hybrid cloud deployment provides the best of both worlds by linking the public and private worlds with a layer of proprietary software. With hybrid cloud deployment, you may host the app in a secure environment while benefiting from the cost benefits of the public cloud. In this, organizations can migrate data and applications between clouds by combining two or more cloud deployment strategies. The hybrid cloud deployment is also popular for 'cloud bursting.' It means that if a company operates an application on-premises, but it experiences a high load, it might explode onto the public cloud.

Community Cloud Deployment#

It enables a collection of businesses to access systems and services. It is a distributed system formed by combining the services of many clouds to meet the special demands of a community, industry, or enterprise. The community's infrastructure might be shared by organizations with similar interests or duties. In this deployment model of cloud computing, cloud deployment is often handled by a third party or a collaboration of one or more community organizations.

Cloud Computing Service Models#

Cloud computing enables the delivery of a variety of services defined by roles, service providers, and user firms. The following are major categories of cloud deployment models and services:

Infrastructure as a Service (IaaS)#

IaaS refers to the employment and use of a third-party provider's IT Physical Infrastructure (network, storage, and servers) [(Malla and Christensen, 2019)]. Users can access IT resources via an internet connection because they are hosted on external servers.

Platform as a Service (PaaS)#

PaaS provides for the outsourcing of physical infrastructure as well as the software environment, which includes databases, integration layers, runtimes, and other components.

Software as a Service (SaaS)#

SaaS is delivered through the internet and does not require any prior installation. The services are available from anywhere in the world for a low monthly charge.

Conclusion#

Over time, the cloud has changed drastically. It was initially only an unusual choice with a few modifications. It is available in a variety of flavors, and you can even establish your Private cloud deployment or Hybrid Cloud deployment in your data center. Each deployment model of cloud computing offers a unique offering that may considerably boost your company's worth. You may also change your Cloud deployment model as your needs change.

A hybrid cloud environment combines on-premises infrastructure, private cloud services, and a public cloud, with orchestration across multiple platforms. If you use a mixture of public clouds, on-premises computing, and private clouds in your data center, you have a hybrid cloud infrastructure.

We recognize the significance of hybrid cloud in cloud computing and its role in organizational development. In this blog article, we'll explore the top five characteristics that define powerful and practical hybrid cloud computing.

What is Hybrid Cloud Computing?#

A hybrid cloud computing approach combines a private cloud (or on-premises data center) with one or more public cloud products connected by public or private networks [(Tariq, 2018)]. Consistent operations enable the public cloud to serve as an extension of a private or on-premises system, with equivalent management processes and tools. Because nearly no one nowadays relies solely on the public cloud, hybrid cloud computing options are becoming increasingly popular. Companies have invested millions of dollars and thousands of hours in on-premises infrastructure. Combining a public and private cloud environment, such as an on-premises data center and a public cloud computing environment, is a common example of hybrid cloud computing provided by AWS, Microsoft Azure, and Google Cloud.

Hybrid Cloud Providers#

The digital revolution has radically changed the IT sector with the introduction of cloud computing. There are several hybrid cloud providers on the market, including:

1. Amazon Web Services (AWS)
2. Microsoft Azure
3. Google Cloud
4. VMware
5. VMware Cloud on AWS, VMware Cloud on Dell EMC, HCI powered by VMware vSAN, and VMware vRealize cloud management
6. Rackspace
7. Red Hat OpenShift
8. Hewlett Packard Enterprise
9. Cisco HyperFlex solutions
10. Nife Cloud Computing

Characteristics of Hybrid Cloud Computing#

Characteristic #1: Speed#

The capacity to automatically adjust to changes in demand is critical for innovation and competitiveness. The market expects updates immediately, and rivals are optimizing rapidly. Hybrid computing must be quick and portable, with maximum flexibility. Technologies like Docker and hybrid cloud providers such as IBM Bluemix facilitate this agility in a virtualized environment.

Characteristic #2: Cost Reduction#

One advantage of cloud computing is lowering expenses. Previously, purchasing IT assets meant paying for unused capacity, impacting the bottom line. Hybrid computing reduces IT costs while allowing enterprises to pay only for what they use. This optimization frees up funds for innovation and market introduction, potentially saving enterprises up to 30%.

Characteristic #3: Intelligent Capabilities and Automation#

Creating a digital experience in hybrid cloud computing requires integrating various technologies, which can be challenging for DevOps teams traditionally relying on numerous tools [(Aktas, 2018)]. Leveraging intelligent, unified, and centralized management capabilities enhances productivity and flexibility. IT automation in hybrid computing reduces human error, enforces policies, supports predictive maintenance, and fosters self-service habits.

Characteristic #4: Security#

Hybrid computing provides critical control over data and enhanced security by reducing data exposure. Organizations can decide where to store data based on compliance, regulatory, or security concerns. Hybrid architectures also support centralized security features like encryption, automation, access control, orchestration, and endpoint security, which are crucial for disaster recovery and data insurance [(Gordon, 2016)].

Characteristic #5: Lightweight Applications#

The final characteristic pertains to application size. DevOps teams need to develop agile apps that load quickly, boost efficiency, and occupy minimal space. Despite inexpensive storage, the focus should be on managing and understanding client data. Hybrid cloud computing supports DevOps in creating applications for global markets while meeting technological demands.

References#

Aktas, M.S. (2018). Hybrid cloud computing monitoring software architecture. Concurrency and Computation: Practice and Experience, 30(21), p.e4694. doi:10.1002/cpe.4694.

Diaby, T. and Rad, B.B. (2017). Cloud computing: a review of the concepts and deployment models. International Journal of Information Technology and Computer Science, 9(6), pp.50-58.

Gordon, A. (2016). The Hybrid Cloud Security Professional. IEEE Cloud Computing, 3(1), pp.82–86. doi:10.1109/mcc.2016.21.

Lee, I. (2019). An optimization approach to capacity evaluation and investment decision of hybrid cloud: a corporate customer's perspective. Journal of Cloud Computing, 8(1). doi:10.1186/s13677-019-0140-0.

Tariq, M.I. (2018). Analysis of the effectiveness of cloud control matrix for hybrid cloud computing. International Journal of Future Generation Communication and Networking, 11(4), pp.1-10.

Read more on Hybrid Cloud Computing: All You Need to Know About Hybrid Cloud Deployment

Cloud computing companies may assist IT executives in laying the groundwork for success, such as increasing deployment speed and assuring future flexibility. However, the landscape is complicated. While technology is rapidly changing the corporate landscape, technology investment procedures have not always kept up. Let's look at how cloud computing may affect CIO budget predictability.

Role of CIOs in Cloud Budget Predictability#

CIOs will need to remain up to date on the newest innovations to make the best decisions on behalf of their businesses to drive their digital transformation. Because of the cloud's influence, as well as the DevOps movement, software development and IT operations have been merged and simplified. As infrastructure and applications are no longer independent, the CIO is no longer required to manage manual IT chores [(Makhlouf, 2020)]. Cost-effectiveness and efficiency must be prioritised in their strategy to save cloud budgets, which will bring a new dimension to their conventional job inside a company.

CIOs must also become more adaptable and agile. There are now so many distinct cloud providers that enterprises must employ a multi-access edge computing-cloud approach.

This implies:

• Businesses will be free to select cloud solutions based on their merits rather than being dependent on a single source.
• The CIO will be in charge of expanding a multi-access edge computing-cloud strategy, which means they must think about things like security, service integration, and cost.

Cloud computing companies will increasingly rely on their CIO to develop useful solutions to support digital transformation as cloud computing platforms evolve. As demand grows more than ever, businesses will have a broader selection of cloud-based solutions to choose from. As a result, the CIO's function will be expanded to include both technical expertise and business-oriented strategic thinking.

CIOs Perspective: From Cost to Investment#

CIOs have long struggled with the impression of IT as a cost centre. The convergence of technology and business strategy might provide CIOs with the chance to abandon a cost-cutting attitude in favour of an investment philosophy that values strategic expenditure to boost revenue, growth, stock price, or other measures of company and shareholder value.

As the technology function assumes a more prominent role, CIOs may need to address critical issues such as core modernization, cloud business models, investment governance and value measurement, the incompatibility of fixed budgets with Agile development, and the impact of automation on the workforce to save cloud budgets [(Liu et al., 2020)].

Cloud Computing Affecting Core Modernization#

Many CIOs acknowledge that old core systems lack the agility required to build and scale creative and disruptive new technology solutions. Legacy systems can be rehosted, re-platformed, rearchitected, rebuilt, or replaced—strategies that vary in impact, cost, risk, and value. However, core modernization should be considered as a technological investment with other options. A big distribution company's CIO opted to postpone a modernization initiative and shift funding to a bespoke warehouse management program that provided the firm with a competitive edge.

Cloud Business Models on OPEX/CAPEX#

Cloud computing companies have welcomed cloud solutions with open arms, drawn by their ease of use and deployment. Cloud computing platforms may foster innovation and encourage experimentation by removing the burden of purchasing and maintaining technological infrastructure [(Kholidy, 2020)]. However, every investment involves risks, and cloud computing platforms are no exception. Because the cloud switches technology spending from the capital expense column to the operating expense column, rushing to the cloud might have a significant impact on firm financials. Finance and IT divisions may collaborate to properly identify these expenses and analyze and maximize the impact to save cloud budgets.

Governance and Value Assessment#

Technology leaders may improve their capacity to create convincing business cases that properly anticipate technology project ROI and assess the performance and value of each investment [(Liu et al., 2018)]. It can be beneficial to have a specialized financial team responsible for modeling, administering, and analyzing the value of IT investments to save cloud budgets.

Taking such actions can help decrease the notion that technology is an incomprehensible black box, make it simpler for technology executives to justify spending, and help them create closer connections with CFOs.

Incompatibility of Fixed Budgets#

Agile and other flexible delivery techniques are on the increase. CIOs may manage investment portfolios in the same way that venture capitalists do, but only if financing mechanisms are changed to favor Agile, product-focused settings. A flexible budgeting methodology may provide product teams with the necessary creativity and responsibility to achieve business value and save cloud budgets.

Automation Impact#

Automation and robotics' ability to streamline and accelerate IT delivery is changing the way technology and cloud computing companies work, collaborate, and create value [(Raj and Raman, 2018)]. Better workflows and various resource needs might drive increased production output and save cloud budgets as automation enables teams to exchange manual and repetitive jobs for those requiring higher-order abilities.

The lack of a standardized methodology for evaluating Cloud Service Providers (CSPs), along with the reality that no two Cloud Service Providers are alike, complicates the process of picking the best one for your firm. This post will help you work through the characteristics you may use to pick a supplier that can best meet your organization's technological and operational demands.

So, how do you go about selecting a Cloud hosting provider? To begin, it is useful to understand who the primary players are today.

The Players#

The sector is crowded, with the big three — AWS, Microsoft Azure, and Google Cloud Services — as well as smaller specialized firms. Of course, AWS, Google Cloud Services, and Azure reign supreme. There are many cloud providers in Singapore such as NIFE, which is a developer-friendly serverless platform designed to let businesses quickly manage, deploy, and scale applications globally.

Criteria for Primary Evaluation#

When deciding which Cloud Service Providers to utilize, consider the alternatives that different providers supply and how they will complement your specific company characteristics and objectives. The following are the main factors to consider for practically any business:

1. Cloud Security#

You want to know exactly what your security objectives are, the security measures provided by each provider, and the procedures they employ to protect your apps and data. Furthermore, ensure that you properly grasp the exact areas for which each party is accountable.

Security is a primary priority in Cloud Computing Services, therefore it's vital to ask specific questions about your specific use cases, industry, legal needs, and any other issues you may have [(Kumar and Goyal, 2019)]. Do not fail to assess this key element of functioning in the cloud.

2. Cloud Compliance#

Next, select a Cloud Computing Service that can assist you in meeting compliance criteria specific to your sector and business. Whether you are subject to GDPR, SOC 2, PCI DSS, HIPAA, or another standard, ensure that you understand what it will take to accomplish compliance once your apps and data are housed on a public cloud architecture [(Brandis et al., 2019)]. Make sure you understand your duties and which parts of compliance the supplier will assist you in checking off.

3. Architecture#

Consider how the architecture will be integrated into your processes today and in the future when selecting a cloud provider. If your company depends heavily on Amazon or Google Cloud Services, it could be wise to go to such Cloud hosting providers for ease of integration and consolidation. When making your selection, you should also consider cloud storage designs. When it comes to storage, the three major suppliers have comparable architectures and offer a variety of storage options to meet a variety of demands, but they all have various forms of archive storage [(Narasayya and Chaudhuri, 2021)].

4. Manageability#

You should also spend some time establishing what different [Cloud hosting providers] will need you to handle. Each service supports several orchestration tools and interfaces with a variety of other services. If your firm relies heavily on certain services, ensure that the cloud provider you select has a simple method to interface with them.

Before making a final selection, you should assess how much time and effort it will take your team to handle various components of the cloud infrastructure.

5. Service Levels#

This aspect is critical when a company's availability, reaction time, capacity, and support requirements are stringent. Cloud Service Level Agreements (Cloud SLAs) are an essential consideration when selecting a provider. Legal considerations for the security of data hosted in the cloud service, particularly in light of GDPR rules, should also be given special consideration [(World Bank, 2022)]. You must be able to rely on your cloud service provider to do the correct thing, and you must have a legal agreement in place to protect you when something goes wrong.

6. Support#

Another factor that must be carefully considered is support. In certain circumstances, the only way to receive help is through a chat service or a contact center. You may or may not find this acceptable. In other circumstances, you may have access to a specialized resource, but there is a significant likelihood that time and access will be limited. Before selecting a Cloud Computing Services, inquire about the amount and type of assistance you will receive. The cloud providers in Singapore like NIFE provide excellent customer support.

7. Costs#

While cost should never be the sole or most essential consideration, there is no disputing that price will play a significant influence in determining which cloud service providers you use.

8. Container Capabilities#

If your company wants to move its virtual server workloads to containers, container orchestration, managed containers, and/or serverless architecture, you should thoroughly examine each Cloud hosting provider's container capabilities. The cloud providers in Singapore like NIFE use Docker Containers.

References#

Brandis, K., Dzombeta, S., Colomo-Palacios, R. and Stantchev, V. ([2019]). Governance, Risk, and Compliance in Cloud Scenarios. Applied Sciences, online 9(2), p.320. doi:10.3390/app9020320.

Kumar, R. and Goyal, R. ([2019]). On cloud security requirements, threats, vulnerabilities and countermeasures: A survey. Computer Science Review, 33, pp.1-48. doi:10.1016/j.cosrev.2019.05.002.

Narasayya, V. and Chaudhuri, S. ([2021]). Cloud Data Services: Workloads, Architectures and Multi-Tenancy. Foundations and Trends® in Databases, 10(1), pp.1-107. doi:10.1561/1900000060.

World Bank. ([2022]). Government Migration to Cloud Ecosystems: Multiple Options, Significant Benefits, Manageable Risks.

Wu, Y., Lei, L., Wang, Y., Sun, K. and Meng, J. ([2020]). Evaluation on the Security of Commercial Cloud Container Services. Lecture Notes in Computer Science, pp.160-177. doi:10.1007/978-3-030-62974-8_10.

DevOps is the answer if you want to produce better software quicker. This software development process invites everyone to the table to swiftly generate secure code. Through automation, collaboration, rapid feedback, and iterative improvement, DevOps principles enable software developers (Devs) and operations (Ops) teams to speed delivery.

What exactly is DevOps as a Service?#

Many mobile app development organisations across the world have adopted the DevOps as a Service mindset. It is a culture that every software development company should follow since it speeds up and eliminates risk in software development [(Agrawal and Rawat, 2019)].

The primary rationale for providing DevOps as a service to clients is to transition their existing applications to the cloud and make them more stable, efficient, and high-performing. The primary goal of DevOps as a service is to ensure that the modifications or activities performed during software delivery are trackable. Applying DevOps practices such as Continuous Integration and Continuous Delivery enables businesses to generate breakthrough results and outstanding commercial value from software [(Trihinas et al., 2018)].

As more organisations adopt DevOps and transfer their integrations to the cloud, the tools used in build, test, and deployment processes will also travel to the cloud, thereby turning continuous delivery into a managed cloud service.

DevOps as a Managed Cloud Service#

What exactly is DevOps in the cloud? It is essentially the migration of your continuous delivery tools and procedures to a hosted virtual platform. The delivery pipeline is reduced to a single site in which developers, testers, and operations specialists work together as a team, and as much of the deployment procedure as feasible is automated. Here are some of the most prominent commercial choices for cloud-based DevOps.

AWS Direct DevOps Tools and Services#

Amazon Web Services (AWS) has established a strong worldwide network to virtualize some of the world's most complicated IT settings [(Alalawi, Mohsin and Jassim, 2021)]. AWS Direct DevOps is a quick and relatively straightforward option to transfer your DevOps to the cloud, with fibre-connected data centres located all over the world and a payment schedule that measures exactly the services you use down to the millisecond of computing time. Even though AWS Direct DevOps provides a plethora of sophisticated interactive capabilities, three specific services are at the heart of continuous cloud delivery.

AWS CodeBuild: AWS CodeBuild is a completely managed service for generating code, automating quality assurance testing, and delivering deployment-ready software.

AWS CodePipeline: You define parameters and develop the model for your ideal deployment scenario using a beautiful graphic interface, and CodePipeline handles it from there.

AWS CodeDeploy: When a fresh build passes through CodePipeline, CodeDeploy distributes the functioning package to each instance based on the settings you specify.

Google Cloud DevOps Tools and Services#

The search engine giant boasts an unrivalled global network, user-friendly interfaces, and an ever-expanding set of features that make the Google Cloud DevOps option worthwhile to explore.

Google Cloud DevOps also offers comprehensive cloud development suites for a broad range of platforms, including Visual Studio, Android Studio, Eclipse, Powershell, and many more [(Jindal and Gerndt, 2021)]. In a cloud environment, use the development tools you already know and love.

Let's take a look at some of the most powerful StackDriver development tools available from Google.

Stackdriver Monitoring: Get a visual representation of your environment's health and pain areas.

Stackdriver Debugger: Zoom in on any code position to see how your programme reacts in real-time production.

Stackdriver Logging: Ingest, monitor, and respond to crucial log events.

StackDriver Trace: Locate, examine, and show latencies in the Google Cloud Console.

Microsoft Azure DevOps Tools and Services#

Microsoft Azure DevOps, Microsoft's cloud management platform, is bringing a powerful punch to DevOps as a managed service area. Azure, like AWS Direct DevOps and Google Cloud DevOps, provides a remarkable range of creative and compatible DevOps tools.

With so many enterprises already invested in Microsoft goods and services, Microsoft Azure DevOps may provide the simplest path to hybrid or full cloud environments. Microsoft's critical DevOps tools include the following:

Azure Application Service: Microsoft Azure DevOps App Service offers an infinite number of development alternatives.

Azure DevTest Labs: Azure DevTest Labs simplifies experimentation for your DevOps team.

Azure Stack: Azure Stack is a solution that allows you to integrate Azure services into your current data centre [(Soh et al., 2020)].

The Advantages of DevOps as a Service#

[DevOps as a Service] has several advantages. Some of the more notable advantages are listed below:

• Better collaboration
• More rapid testing and deployment
• Reduces complexity
• Product of the highest quality
• Internal DevOps coexists

Final thoughts#

Choosing DevOps as a service will allow you to develop your business faster and provide more value to your clients. Choosing DevOps as a service is your route to customer success, whether you're developing a new application or upgrading your legacy ones.

Are you curious about cloud development? You've come to the perfect location for answers.

In this Blog, we will discuss what is Cloud Development, Cloud Native Development, Cloud Native Application Development, Cloud Application Development, and Cloud Application Development Services. Let's get started.

What is Cloud Development?#

Cloud development is the process of creating, testing, delivering, and operating software services on the cloud. Cloud software refers to programmes developed in a cloud environment. Cloud development is often referred to as cloud-based or in-cloud development. Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, and others are well-known Cloud application development services. The widespread use of cloud services by businesses has resulted in numerous forms of cloud development based on their commercial viability.

Businesses can incorporate the most recent cloud technologies into their web apps and other Cloud application development services by utilising cloud such as multiple remote data centres, development tools, operating systems, and so on via a cloud platform as a service, software as a service, or infrastructure as a service. The Cloud application development services are based on speed, security, and resource and infrastructure flexibility. For business-driving results, cloud application development services employ cutting-edge technology and the finest of all private, public, and hybrid cloud services. Cloud application development services offer a high level of security and risk management.

Cloud Application Development#

Cloud application development is the process of creating a Cloud-based programme. It entails many stages of software development, each of which prepares your programme for launch and market acceptance. DevOps approaches and tools such as Kubernetes are used by the finest Cloud application development teams. When utilised effectively with software development processes, cloud application development on cloud infrastructure allows web and PWA development services to cut development costs, open up the potential of working with remote teams, and shorten project timeframes.

What is Cloud Native Development?#

Cloud Native development is designed to work seamlessly in the cloud. Developers create the architecture of Cloud Native application development from the start or heavily restructure existing code to function on the cloud utilising cloud-based technologies [(Gilbert, 2018)]. Developers can continually and effectively deploy new software services. Cloud Native Development includes features such as continuous integration/continuous development, containers, microservices, and so on.

Cloud Native Development is centred on breaking down large software programmes into smaller services that may be utilised wherever they are needed. This guarantees that Cloud Native application development is accessible, scalable, and flexible. Microservices, cloud platforms, containers, Kubernetes, immutable infrastructure, declarative APIs, and continuous delivery technologies are commonly used in Cloud Native application development, along with approaches such as DevOps and agile methodology.

Cloud-enabled Development#

The movement of traditional software to the cloud platform is known as cloud-enabled development. Cloud-enabled apps are created in a monolithic approach on on-premises hardware and resources. Cloud-enabled programmes are unable to achieve the optimum scalability and resource sharing that cloud applications provide.

Cloud-based Development#

Cloud-native application development is balanced with cloud-based software development. They provide the availability and scalability of cloud services without needing major application changes. This cloud development strategy enables enterprises to use cloud benefits in certain of their services without having to change the entire software application code.

What distinguishes cloud application development from traditional app development?#

Historically, software engineers would create software applications on local workstations before deploying them to the production environment. This technique increases the likelihood of software products not functioning as intended, as well as other compatibility difficulties.

Today, developers utilise agile and DevOps software development approaches, which allow for improved collaboration among development team members, allowing them to generate products effectively and follow user market expectations [(Fylaktopoulos et al., 2016)]. Cloud application development services such as Google App Engine, code repositories such as GitHub, and so on enable developers to test, restructure, and enhance codebases in a collaborative environment before immediately deploying them to the production environment.

The Advantages of Cloud Development#

Among the many advantages are:

• Cloud developers may automate several developments and testing activities.

• A cloud developer may quickly rework and enhance code without interfering with the production environment. It makes the development process more agile [(Odun-Ayo, Odede and Ahuja, 2018)].

• Containers and microservices enable cloud developers to create more scalable software solutions.

• DevOps development methodologies enable cloud app developers, IT employees, and clients to continually enhance the software product.

• When compared to on-premises software development, the entire process is more cost-effective, efficient, and secure.

Conclusion#

The cloud computing business is massive and likely to explode in the coming years. The reason for this is the cost-effectiveness, scalability, and flexibility it brings to business processes and products, especially for small and medium-sized enterprises. A cloud-native, cloud-based, or cloud-enabled development requires a capable team of software developers that understand cloud migration and integrate best practices.

As a developer, you're likely familiar with new technologies that promise to enhance software production speed and app robustness once deployed. Cloud computing technology is a prime example, offering immense promise. This article delves into multi-access edge computing and deployment in cloud computing, providing practical advice to help you with real-world application deployments on cloud infrastructure.

Why is Cloud Simplification Critical?#

Complex cloud infrastructure often results in higher costs. Working closely with cloud computing consulting firms to simplify your architecture can help reduce these expenses [(Asmus, Fattah, and Pavlovski, 2016)]. The complexity of cloud deployment increases with the number of platforms and service providers available.

The Role of Multi-access Edge Computing in Application Deployment#

[Multi-access Edge Computing] offers cloud computing capabilities and IT services at the network's edge, benefiting application developers and content providers with ultra-low latency, high bandwidth, and real-time access to radio network information. This creates a new ecosystem, allowing operators to expose their Radio Access Network (RAN) edge to third parties, thus offering new apps and services to mobile users, corporations, and various sectors in a flexible manner [(Cruz, Achir, and Viana, 2022)].

Choose Between IaaS, PaaS, or SaaS#

In cloud computing, the common deployment options are Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). PaaS is often the best choice for developers as it manages infrastructure, allowing you to focus on application code.

Scale Your Application#

PaaS typically supports scalability for most languages and runtimes. Developers should understand different scaling methods: vertical, horizontal, manual, and automatic [(Eivy and Weinman, 2017)]. Opt for a platform that supports both manual and automated horizontal scaling.

Consider the Application's State#

Cloud providers offering PaaS often prefer greenfield development, which involves new projects without constraints from previous work. Porting existing or legacy deployments can be challenging due to ephemeral file systems. For greenfield applications, create stateless apps. For legacy applications, choose a PaaS provider that supports both stateful and stateless applications.

Select a Database for Cloud-Based Apps#

If your application doesn't need to connect to an existing corporate database, your options are extensive. Place your database in the same geographic location as your application code but on separate containers or servers to facilitate independent scaling of the database [(Noghabi, Kolb, Bodik, and Cuervo, 2018)].

Consider Various Geographies#

Choose a cloud provider that enables you to build and scale your application infrastructure across multiple global locations, ensuring a responsive experience for your users.

Use REST-Based Web Services#

Deploying your application code in the cloud offers the flexibility to scale web and database tiers independently. This separation allows for exploring technologies you may not have considered before.

Implement Continuous Delivery and Integration#

Select a cloud provider that offers integrated continuous integration and continuous delivery (CI/CD) capabilities. The provider should support building systems or interacting with existing non-cloud systems [(Garg and Garg, 2019)].

Prevent Vendor Lock-In#

Avoid cloud providers that offer proprietary APIs that can lead to vendor lock-in, as they might limit your flexibility and increase dependency on a single provider.

References

Asmus, S., Fattah, A., & Pavlovski, C. ([2016]). Enterprise Cloud Deployment: Integration Patterns and Assessment Model. IEEE Cloud Computing, 3(1), pp.32-41. doi:10.1109/mcc.2016.11.

Cruz, P., Achir, N., & Viana, A.C. ([2022]). On the Edge of the Deployment: A Survey on Multi-Access Edge Computing. _ACM Computing Surveys (CSUR).

Eivy, A., & Weinman, J. ([2017]). Be Wary of the Economics of ‘Serverless' Cloud Computing. IEEE Cloud Computing, 4(2), pp.6-12. doi:10.1109/mcc.2017.32.

Garg, S., & Garg, S. ([2019]). Automated Cloud Infrastructure, Continuous Integration, and Continuous Delivery Using Docker with Robust Container Security. In 2019 IEEE Conference on Multimedia Information Processing and Retrieval (MIPR) (pp. 467-470). IEEE.

Noghabi, S.A., Kolb, J., Bodik, P., & Cuervo, E. ([2018]). Steel: Simplified Development and Deployment of Edge-Cloud Applications. In 10th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 18).

There are several definitions of DevOps, and many of them sufficiently explain one or more characteristics that are critical to finding flow in the delivery of IT services. Instead of attempting to provide a complete description, we want to emphasize DevOps principles that we believe are vital when adopting or shifting to a DevOps method of working.

What is DevOps?#

DevOps is a software development culture that integrates development, operations, and quality assurance into a continuous set of tasks (Leite et al., 2020). It is a logical extension of the Agile technique, facilitating cross-functional communication, end-to-end responsibility, and cooperation. Technical innovation is not required for the transition to DevOps as a service.

Principles of DevOps#

DevOps is a concept or mentality that includes teamwork, communication, sharing, transparency, and a holistic approach to software development. DevOps is based on a diverse range of methods and methodologies. They ensure that high-quality software is delivered on schedule. DevOps principles govern the service providers such as AWS Direct DevOps, Google Cloud DevOps, and Microsoft Azure DevOps ecosystems.

Principle 1 - Customer-Centric Action#

Short feedback loops with real consumers and end users are essential nowadays, and all activity in developing IT goods and services revolves around these clients.

To fulfill these consumers' needs, DevOps as a service must have : - the courage to operate as lean startups that continuously innovate, - pivot when an individual strategy is not working - consistently invest in products and services that will provide the highest degree of customer happiness.

AWS Direct DevOps, Google Cloud DevOps, and Microsoft Azure DevOps are customer-oriented DevOps.

Principle 2 - Create with the End in Mind.#

Organizations must abandon waterfall and process-oriented models in which each unit or employee is responsible exclusively for a certain role/function and is not responsible for the overall picture. They must operate as product firms, with an explicit focus on developing functional goods that are sold to real consumers, and all workers must share the engineering mentality necessary to imagine and realise those things (Erich, Amrit and Daneva, 2017).

Principle 3 - End-to-end Responsibility#

Whereas conventional firms build IT solutions and then pass them on to Operations to install and maintain, teams in a DevOps as a service are vertically structured and entirely accountable from idea to the grave. These stable organizations retain accountability for the IT products or services generated and provided by these teams. These teams also give performance support until the items reach end-of-life, which increases the sense of responsibility and the quality of the products designed.

Principle 4 - Autonomous Cross-Functional Teams#

Vertical, fully accountable teams in product organizations must be completely autonomous throughout the whole lifecycle. This necessitates a diverse range of abilities and emphasizes the need for team members with T-shaped all-around profiles rather than old-school IT experts who are exclusively informed or proficient in, say, testing, requirements analysis, or coding. These teams become a breeding ground for personal development and progress (Jabbari et al., 2018).

Principle 5 - Continuous Improvement#

End-to-end accountability also implies that enterprises must constantly adapt to changing conditions. A major emphasis is placed on continuous improvement in DevOps as a service to eliminate waste, optimize for speed, affordability, and simplicity of delivery, and continually enhance the products/services delivered. Experimentation is thus a vital activity to incorporate and build a method of learning from failures. In this regard, a good motto to live by is "If it hurts, do it more often."

Principle 6 - Automate everything you can#

Many firms must minimize waste to implement a continuous improvement culture with high cycle rates and to develop an IT department that receives fast input from end users or consumers. Consider automating not only the process of software development, but also the entire infrastructure landscape by constructing next-generation container-based cloud platforms like AWS Direct DevOps, Google Cloud DevOps, and Microsoft Azure DevOps that enable infrastructure to be versioned and treated as code (Senapathi, Buchan and Osman, 2018). Automation is connected with the desire to reinvent how the team provides its services.

Remember that a DevOps Culture Change necessitates a Unified Team.#

DevOps is just another buzzword unless key concepts at the foundation of DevOps are properly implemented. DevOps concentrates on certain technologies that assist teams in completing tasks. DevOps, on the other hand, is first and foremost a culture. Building a DevOps culture necessitates collaboration throughout a company, from development and operations to stakeholders and management. That is what distinguishes DevOps from other development strategies.

Remember that these concepts are not fixed in stone while shifting to DevOps as a service. DevOps Principles should be used by AWS Direct DevOps, Google Cloud DevOps, and Microsoft Azure DevOps according to their goals, processes, resources, and team skill sets.

Organizations continue to build new apps on the cloud or move current applications to the cloud. A company that adopts cloud technologies and/or selects cloud service providers (CSPs) and services or applications without first thoroughly understanding the hazards associated exposes itself to a slew of commercial, economic, technological, regulatory, and compliance hazards. In this blog, we will learn about the hazards of application deployment, Cloud Deployment, Deployment in Cloud Computing, and Cloud deployment models in cloud computing.

What is Cloud Deployment?#

Cloud computing is a network access model that enables ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or interaction from service providers [(Moravcik, Segec and Kontsek, 2018)].

Essential Characteristics:#

1. On-demand self-service
2. Broad network access
3. Resource pooling
4. Rapid elasticity
5. Measured service

Service Models:#

1. Software as a service (SaaS)
2. Platform as a service (PaaS)
3. Infrastructure as a service (IaaS)

Deployment Models:#

1. Private Cloud
2. Community cloud
3. Public cloud
4. Hybrid cloud

Hazards of Application Deployment on Clouds#

At a high level, cloud environments face the same hazards as traditional data centre settings; the threat landscape is the same. That is, deployment in cloud computing runs software, and software contains weaknesses that attackers aim to exploit.

1. Consumers now have less visibility and control.

When businesses move assets/operations to the cloud, they lose visibility and control over those assets/operations. When leveraging external cloud services, the CSP assumes responsibility for some rules and infrastructure in Cloud Deployment.

2. On-Demand Self-Service Makes Unauthorized Use Easier.

CSPs make it very simple to add Cloud deployment models in cloud computing. The cloud's on-demand self-service provisioning features enable an organization's people to deploy extra services from the agency's CSP without requiring IT approval. Shadow IT is the practice of employing software in an organisation that is not supported by the organization's IT department.

3. Management APIs that are accessible through the internet may be compromised.

Customers employ application programming interfaces (APIs) exposed by CSPs to control and interact with cloud services (also known as the management plane). These APIs are used by businesses to provide, manage, choreograph, and monitor their assets and people. CSP APIs, unlike management APIs for on-premises computing, are available through the Internet, making them more vulnerable to manipulation.

4. The separation of several tenants fails.

Exploiting system and software vulnerabilities in a CSP's infrastructure, platforms, or applications that allow multi-tenancy might fail to keep tenants separate. An attacker can use this failure to obtain access from one organization's resource to another user's or organization's assets or data.

5. Incomplete data deletion

Data deletion threats emerge because consumers have little insight into where their data is physically housed in the cloud and a limited capacity to verify the secure erasure of their data. This risk is significant since the data is dispersed across several storage devices inside the CSP's infrastructure in a multi-tenancy scenario.

6. Credentials have been stolen.

If an attacker acquires access to a user's cloud credentials, the attacker can utilise the CSP's services such as deployment in cloud computing to provide new resources (if the credentials allow provisioning) and target the organization's assets. An attacker who obtains a CSP administrator's cloud credentials may be able to use them to gain access to the agency's systems and data.

7. Moving to another CSP is complicated by vendor lock-in.

When a company contemplates shifting its deployment in cloud computing from one CSP to another, vendor lock-in becomes a concern. Because of variables such as non-standard data formats, non-standard APIs, and dependency on one CSP's proprietary tools and unique APIs, the company realises that the cost/effort/schedule time required for the transition is substantially more than previously estimated.

8. Increased complexity puts a strain on IT staff.

The transition to the cloud can complicate IT operations. To manage, integrate, and operate in Cloud deployment models in cloud computing, the agency's existing IT employees may need to learn a new paradigm. In addition to their present duties for on-premises IT, IT employees must have the ability and skill level to manage, integrate, and sustain the transfer of assets and data to the cloud.

Conclusion

It is critical to note that CSPs employ a shared responsibility security approach. Some features of security are accepted by the CSP. Other security concerns are shared by the CSP and the consumer. Finally, certain aspects of security remain solely the consumer's responsibility. Effective Cloud deployment models in cloud computing and cloud security are dependent on understanding and fulfilling all customs duties. The inability of consumers to understand or satisfy their duties is a major source of security issues in Cloud Deployment.

Cloud cost optimization is the process of finding underutilized resources, minimizing waste, obtaining more discounted capacity, and scaling the best cloud computing services to match the real necessary capacity—all to lower infrastructure as a service price [(Osypanka and Nawrocki, 2020)].

Nife is a Singapore-based Unified Public Cloud Edge best cloud computing platform for securely managing, deploying, and scaling any application globally using Auto Deployment from Git. It requires no DevOps, servers, or infrastructure management. There are currently many best cloud computing companies in Singapore and NIFE is one of the best cloud computing companies in Singapore.

What makes Nife the best Cloud Company in Singapore?#

Public cloud services are well-known for their pay-per-use pricing methods, which charge only for the resources that are used. However, in most circumstances, public cloud services charge cloud clients based on the resources allocated, even if those resources are never used. Monitoring and controlling cloud services is a critical component of cloud cost efficiency. This can be challenging since purchasing choices are often spread throughout a company, and people can install cloud services and commit to charges with little or no accountability [(Yahia et al., 2021)]. To plan, budget, and control expenses, a cloud cost management approach is required. Nife utilizes cloud optimization to its full extent thus making it one of the best cloud companies in Singapore.

What Factors Influence Your Cloud Costs?#

Several factors influence cloud expenses, and not all of them are visible at first.

Public cloud services typically provide four price models:

1. **Pay as you go:** Paying for resources utilized on an hourly, minutely, or secondary basis.

2. **Reserved instances:** Paying for a resource in advance, often for one or three years.

3. **Spot instances:** Buying the cloud provider's excess capacity at steep prices, but with no assurance of dependability [(Domanal and Reddy, 2018)].

4. **Plans for savings:** Some cloud providers provide volume discounts based on the overall amount of cloud services ordered by an enterprise.

What cost factors make Nife the best cloud computing platform?#

The cost factors which make Nife the best cloud computing platform are:

• Utilization of computes instances — with prices variable depending on the instance type and pricing strategy.

• Utilization of cloud storage services — with varying costs depending on the service, storage tier, storage space consumed, and data activities done.

• Database services are commonly used to run managed databases on the cloud, with costs for compute instances, storage, and the service itself [(Changchit and Chuchuen, 2016)].

• Most cloud providers charge for inbound and outgoing network traffic.

• Software licensing – even if the cost of a managed service is included in the per-hour price, the software still has a cost in the cloud.

• Support and consultancy – In addition to paying for support, the best cloud computing platforms may require extra professional services to implement and manage their cloud systems.

What are Nife's Cost Saving Strategies that make it the best cloud computing services provider?#

Here is the list of cost factors making NIFE the best cloud computing services provider:

Workload schedules

Schedules can be set to start and stop based on the needs of the task. There is no point to activate and pay for a resource if no one is utilising it.

Make use of Reserved Instances.

Businesses considering long-term cloud computing investments might consider reserved instances. Cloud companies such as NIFE offer savings of up to 75% for pledging to utilise cloud resources in advance.

Utilize Spot Instances

Spot instances have the potential to save much more than allocated instances. Spot instances are a spare capacity that is sold at a discount by the cloud provider [(Okita et al., 2018)]. They are back on the market and can be acquired at a discount of up to 90%.

Utilize Automation

Use cloud automation to deploy, set up, and administer Nife's best cloud computing services wherever possible. Automation operations like backup and storage, confidentiality and availability, software deployment, and configuration reduce the need for manual intervention. This lowers human mistakes and frees up IT employees to focus on more critical business operations.

Automation has two effects on cloud costs:

1. You obtain central control by automating activity. You may pick which resources to deploy and when at the department or enterprise level.

2. Automation also allows you to adjust capacity to meet current demand. Cloud providers give extensive features for sensing application load and usage and automatically scaling resources based on this data.

Keep track of storage use.

The basic cost of cloud storage services is determined by the storage volumes provisioned or consumed. Users often close projects or programs without removing the data storage. This not only wastes money but also raises worries about security. If data is rarely accessed but must be kept for compliance or analytics, it might be moved to archive storage.

The supply of continually updated information streaming at zero or low latency is referred to as real-time (data) monitoring [(Fatemi Moghaddam et al., 2015)]. IT monitoring entails routinely gathering data from all areas of an organization's IT system, such as on hardware, virtualized environments, networking, and security settings, as well as the application stack, including cloud-based applications, and software user interfaces in cloud computing companies. IT employees use this data to assess system performance, identify abnormalities, and fix issues. Real-time application monitoring raises the stakes by delivering a continuous low-latency stream of relevant and current data from which administrators may quickly spot major issues. Alerts can be delivered more rapidly to suitable personnel – or even to automated systems – for remediation. Cloud computing companies can disclose and forecast trends and performance by recording real-time monitoring data over time.

Nife Cloud Computing & Cloud-Native Development#

Nife is a serverless platform for developers that allows enterprises to efficiently manage, launch, and scale applications internationally. It runs your apps near your users and grows to compute in cities where your programme is most often used. Traditionally, programmes are placed on the cloud computing companies which are located far away from the end-user. When data moves between regions and places, it creates computational issues such as bandwidth, cost, and performance, to mention a few.

Nife architecture#

Cloud is constructed in the style of a Lego set. To build a multi-region architecture for your applications across constrained cloud regions, you must first understand each component: network, infrastructure, capacity, and computing resources [(Odun-Ayo et al., 2018)]. Manage and monitor the infrastructure as well. This still does not affect application performance.

Nife PaaS Platform enables you to deploy various types of services near the end-user, such as entire web apps, APIs, and event-driven serverless operations, without worrying about the underlying infrastructure. Nife includes rapid, continuous deployments as well as an integrated versioning mechanism for managing applications. To allow your apps to migrate across infrastructure globally, you may deploy normal Docker containers or plug your code straight from your git repositories. Applications may be deployed in many places spanning North America, Latin America, Europe, and the Asia Pacific. The Nife edge network includes an intelligent load balancer and geo-routing based on rules.

Nife Instantly deploy all applications

To install any application quickly and easily everywhere, NIFE provides on-demand infrastructure from a wide range of worldwide suppliers.

• Nife deploy your application in seconds by using Docker images or by connecting your git repository and simply deploying.

• Run internationally with a single click - Depending on your requirements, you may run your apps in any or all of our locations. With 500 Cloud, Edge, and Telco sites, you can go worldwide.

• Seamless auto-scaling- Any region, any position at the nearest endpoint at your fingertips [(Diaby and Bashari, 2017)].

• Anything may be run - NIFE are ready to power Telco Orchestration demands from MEC to MANO to ORAN beyond the edge cloud using Containers, Functions, and MicroVMs!

Nife's Edge Ecosystem

It is critical to stay current with the ecosystem to have a resilient, intelligent global infrastructure [(Kaur et al., 2020)]. NIFE collaborate with various cloud computing companies' supporters to establish an edge ecosystem, whether it be software, hardware, or the network.

• Flexible - Customers of NIFE have access to infrastructure distributions worldwide, in every corner and area, thanks to the Public Edge. NIFE can reach Billions of users and Trillions of devices using these.

• Unified - Nife's Global Public Edge is a network of edge computing resources that support numerous environments that are globally spread and deployable locally.

• Widely dispersed - Developers may distribute workloads to resources from public clouds, mobile networks, and other infrastructures via a single aggregated access.

How does Nife's real-time application monitoring function?#

Nife's real-time monitoring conveys an IT environment's active and continuing condition. It may be configured to focus on certain IT assets at the required granularity.

The following are examples of real-time data: CPU and memory usage; application response time; service availability; network latency; web server requests; and transaction times are all factors to consider.

Real-time application monitoring tools, in general, shows pertinent data on customised dashboards. Data packet categories and formats can be shown as numerical line graphs, bar graphs, pie charts, or percentages by admins. The data displays can be adjusted based on priorities and administrative choices.

The Nife's Real-Time Monitoring and Benefits of Cloud Computing#

Collecting real-time monitoring data allows IT administrators to analyse and respond to current occurrences in the IT environment in real time. Furthermore, cloud computing companies may store and analyse real-time data over time to uncover patterns and better notice irregularities that fall outside of the predefined system and application behaviour limits. This is referred to as trend monitoring and it's among the best benefits of cloud computing.

Reactive monitoring vs. proactive monitoring: Reactive monitoring has long been used in cloud computing companies and data centres as a troubleshooting tool [(Poniszewska-Maranda et al., 2019)]. The name of this technique reveals its distinguishing feature: It responds to triggers that indicate the occurrence of an event.

Cloud Cost Management refers to the idea of effectively controlling your cloud expenditures. It typically entails evaluating your cloud's expenses and reducing those that are unneeded in the best cloud computing platforms. There are no shortcuts when it comes to expense management. Make solid planning, get the fundamentals right, and include your teams so they realize the gravity of the problem. Cloud cost management has emerged as a critical subject for cloud computing technology and Multi-Access Edge Computing, as well as a new need for every software firm.

Cloud Cost Management Tools Used in the Best Cloud Computing Platforms#

Cloud Cost Optimization: Organizations frequently overspend with their cloud service providers and want to reduce expenses so that they only pay for whatever they need. They must reduce cloud-related expenses.

Transparency in Cloud Expenses: Cloud costs should be visible at all levels of the company, from executives to engineers. All participants must be able to grasp cloud costs in their situation.

Cloud Cost Governance: Guardrails should be put in place regarding cloud computing technologies expenses, basically building systems to guarantee costs are kept under control.

Best Practices for Cloud Cost Management#

You may apply the best practices for cloud cost management given below to create a cloud cost optimization plan that relates expenses to particular business activities such as Multi-Access Edge Computing and Cloud Computing Technology, allowing you to identify who, what, why, and how your cloud money would be spent.

Underutilized Resources Should Be Rightsized or Resized

Making sure your clusters are properly scaled is one of the most effective methods to cut costs on your cloud infrastructure. Implementing tips may assist you in optimizing costs and lowering your cloud expenditures. It can also suggest improvements to instance families. Continuous variables do more than just lower cloud expenses; it also assists in cloud optimization or making the most of the services you pay for.

Unused Resources Should Be Shut Down

A cloud management platform/tool may detect idle, unallocated, and underused virtual machines/resources. Idle resources are ones that were formerly operational but are now turned off, raising expenditures. Purchased but never used unallocated or underused virtual machines (VMs) [(Adhikari and Patil, 2013)]. You spend for what you order or buy, not what you utilize with any cloud platform.

Setup AutoStopping Rules

AutoStopping Rules are a strong and dynamic resource orchestrator for non-production demands. Some of the major benefits of implementing AutoStopping Rules into your cloud services are as follows:

• Detect idle moments automatically and shut down (on-demand) or terminate (spot) services.
• Allow workloads to execute on fully coordinated checks for signs while stressing over spot disruptions.
• Calculate idle times, especially throughout the working time.
• Stop cloud services without optimizing compute; just start/stop operations are supported.

Detect Cloud Cost Inconsistencies

A technique for detecting cloud cost anomalies in the best cloud computing platforms can be used to keep cloud expenses under control. Cost anomaly detection indicates what you should be looking for to keep your cloud expenses under control (save money). An alert is generated if your cloud costs significantly increase. This assists you in keeping track of potential waste and unanticipated expenditures. It also records repeating occurrences (seasonality) that occur on a daily, weekly, or monthly basis.

Set a Fixed Schedule for Uptime or Downtime

Configure your resources' uptime and downtime schedules. For that duration, you can set downtime for the specified resources. Your selected services will be unavailable during this time, allowing you to save money. This is especially useful when many teams are using/using the same resources as in Multi-Access Edge Computing.

Create Budgets and Thresholds for Teams and Projects

Make your budgets and get reminders when your expenses surpass (or are projected to exceed) your budget. You can also specify a budget percentage barrier based on actual or expected costs. Setting budgets and boundaries for various teams and business units can help to reduce cloud waste significantly.

Establish a Cloud Center of Excellence Team

A Cloud Center of Excellence (CCoE) is comprised of executives (CFO and CTO), an IT Manager, an Operations Manager, a System Architect, an Application Developer, a Network Engineer, and a Database Engineer [(AlKadi et al., 2019)]. This group may assist you in identifying opportunities for cloud cost minimization.

"Cost Impact of Cloud Computing Technology" Culture#

Every important feature should have a Cloud Cost Impact checkbox. This promotes a mindset and attitude among application developers and the cross-functional team that expenses are just another boundary condition to be optimized over time and make your platform the best cloud computing platform.

Conclusion#

Consider how your company is now working in the cloud. Is your company's Cloud Operating Model well-defined? Is your company using the best cloud computing platforms? Are you using Multi-Access Edge Computing? Cloud cost management does not have to be difficult, but it does need a disciplined strategy that instills strong rightsizing behaviors and consistently drives insights and action through analytics to reduce your cloud bill. And here is where Nife's cloud computing technology shines.

Presently, the success of a company entails engaging in digitalization to penetrate market opportunities, connect with consumers in unusual ways, and discover different methods and practices. This entails reversing the conventional corporate model—moving from one that would be compartmentalized and rigid to one that is interconnected and fluid.

Owing to enhanced digital ecosystems which thus offer all-new levels of economic development and return on investment, new types of digital business dialogue and integration (open interconnection) are now conceivable. Because, in the digital era, big players have the finest virtual connectivity, wherein they collect and administer the broadest ecosystem of brand and product suppliers [(Park, Chung and Shin, 2018)]. Digital Ecosystem Management (DEM) is a new business field that has arisen in reaction to digitalization and digital ecosystem connectivity.

Significance of digital ecosystems#

Networking impacts are introduced by [digital ecosystems]. Businesses that integrate with virtualization can create configurable business strategies comprised of adaptable programs and services that can be readily changed out when market demands and/or new technologies dictate [(Hoch and Brad, 2020)]. Implementation of change (like the worldwide COVID-19 epidemic) isn't any more the same as plotting a new path on a cruise liner. Businesses may now react instantly, more accurately, and at a cheaper price than it has ever been.

However, like with any radical transformation, appropriate execution is critical to gaining a competitive edge. Businesses must first select how they want to engage in any particular ecosystem. Instigators define the ecosystem's settings and optimize its worth. Contributors offer assistance through a wide range of commercial formats (service, channel, etc.) and create secondary interconnections. Irrespective of the purpose, each organization must understand its fundamental capabilities and enable other ecosystem participants to produce higher value than would be achievable all alone at mass.

A triad of digital ecosystems#

Every ecosystem contains a variety of people who play distinct yet interrelated and interdependent functions. Presently, there are three fundamental forms of digital ecosystems:

Platform ecosystem#

Businesses that manufacture and sell equipment comprise a platform ecosystem. Networking, memory, and computing are examples of digital fundamental building blocks, as are digital solutions and/or products.

Collaboration ecosystem#

A collaborative ecosystem is a group of businesses that focus on data, AI, machine learning, and the exchange of knowledge to create new businesses or solve complicated challenges [(Keselman et al., 2019)].

Services ecosystem#

A services ecosystem is one in which businesses supply certain business operations and make those activities accessible to other businesses as a service. This enables businesses to build new involved in supply chain models, improving their particular company's operations.

Emerging Digital ecosystem models#

The three unique digital ecosystems spanning multiple sectors include different marketplaces. Businesses from many sectors team up to engage in professional contact events, resulting in the formation of new ecosystem models. Independent retail, economic service, transportation, and logistics ecosystems, for example, are collaborating to establish a new digital ecosystem to generate more effective, value-added distribution networks [(Morgan-Thomas, Dessart and Veloutsou, 2020)].

Best practices in the digital ecosystem#

Businesses must stay adaptable when developing an integrated digital ecosystem. The goal of digital transformation is to remodel an organization's goods, processes, and strengths utilizing contemporary technology [(Gasser, 2015)]. This rethinking cannot take place unless the organization is ready to accept all of the prospective changes. Effective digital ecosystems have the following best practices:

• The business model is being rethought.
• Promoting an open, collaborative culture.
• Bringing together a varied group of partners.
• Create a large user base.
• Make a significant worldwide impact.
• Maintain your technological knowledge.

Gravity and network density of Digital Ecosystem#

Digital ecosystems have a gravitational pull and attract additional members. This increases network connectivity between interconnected ecosystems and data center customers. The removal of the range component eliminates or considerably reduces transmission delay, instability, and errors. Businesses may interface with partner organizations instantly and safely by employing one-to-many software-defined connectivity, such as Equinix FabricTM [(Marzuki and Newell, 2019)].

Interconnectivity changes the dynamics of information and correspondence time. It's the most effective way of getting enormous amounts of data and communication between an expanding number of participants—while maintaining the minimum delay, fastest bandwidth, highest dependability, and fastest connection delivery. And, because all of those linkages are private rather than public, as with the network, the likelihood of cybersecurity threats interrupting any specific ecosystem is much reduced.

Conclusion

Digital ecosystems are a crucial aspect of doing business in the current online market. The breadth of digital ecosystems is fluid, encompassing a wide variety of products, activities, infrastructures, and applications. As a business progresses from the adaptor to attacker, its effect and worth in the digital ecosystem expand from the business level to the ecosystem level. As with any management framework, businesses must change themself in the first phase before reforming their sector and ecosystem in the final phase.

Everyone is now heading to the Cloud World (AWS, GCP, Azure, PCF, VMC). A public cloud, a private cloud, or a hybrid cloud might be used. These cloud computing services offer on-demand computing capabilities to meet the demands of consumers. They provide options by keeping IT infrastructure open, from data to apps. The field of cloud-based services is wide, with several models. It might be difficult to sort through the abbreviations and comprehend the differences between the many sorts of services (Rajiv Chopra, 2018). New versions of cloud-based services emerge as technology advances. No two operations are alike, but they do have some qualities. Most crucially, they simultaneously exist in the very same space, available for individuals to use.

Infrastructure as a Service (IaaS)#

IaaS offers only a core infrastructure (VM, Application Define Connection, Backup connected). End-users must set up and administer the platform and environment, as well as deploy applications on it (Van et al., 2015).

Examples - Microsoft Azure (VM), AWS (EC2), Rackspace Technology, Digital Ocean Droplets, and GCP (CE)

Advantages of IaaS

• Decreasing the periodic maintenance for on-premise data centers.

• Hardware and setup expenditures are eliminated.

• Releasing resources to aid in scaling

• Accelerating the delivery of new apps and improving application performance

• Enhancing the core infrastructure's dependability.

• IaaS providers are responsible for infrastructure maintenance and troubleshooting.

During service failures, IaaS makes it simpler to access data or apps. Security is superior to in-house infrastructure choices.

Container as a Service (CaaS)#

CaaS is a type of container-based virtualization wherein customers receive container engines, management, and fundamental computing resources as a service from the cloud service provider (Smirnova et al., 2020).

Examples - are AWS (ECS), Pivotal (PKS), Google Container Engine (GKE), and Azure (ACS).

Advantages of CaaS

• Containerized applications have all the necessary to operate.

• Containers can accomplish all that VM could without the additional resource strain.

• Containers need lower requirements and do not require a separate OS.

• Containers are maintained isolated from each other despite both having the very same capabilities.

• The procedure of building and removing containers is rapid. This speeds up development or operations and reduces time to market.

Platform-as-a-Service (PaaS)#

It offers a framework for end-users to design, operate, and administer applications without having to worry about the complexities of developing and managing infrastructure (Singh et al., 2016).

Examples - Google App Engine, AWS (Beanstalk), Heroku, and CloudFoundry.

Advantages of PaaS

• Achieve a competitive edge by bringing their products to the marketplace sooner.

• Create and administer application programming interfaces (APIs).

• Data mining and analysis for business analytics

• A database is used to store, maintain, and administer information in a business.

• Build frameworks for creating bespoke cloud-based applications.

• Put new languages, OS, and database systems into the trial.

• Reduce programming time for platform tasks such as security.

Function as a Service (FaaS)#

FaaS offers a framework for clients to design, operate, and manage application features without having to worry about the complexities of developing and managing infrastructure (Rajan, 2020).

Examples - AWS (Lamda), IBM Cloud Functions, and Google Cloud Function

Advantages of FaaS

• Businesses can save money on upfront hardware and OS expenditures by using a pay-as-you-go strategy.

• As cloud providers deliver on-demand services, FaaS provides growth potential.

• FaaS platforms are simple to use and comprehend. You don't have to be a cloud specialist to achieve your goals.

• The FaaS paradigm makes it simple to update apps and add new features.

• FaaS infrastructure is already highly optimized.

Software as a Service (SaaS)#

SaaS is also known as "on-demand software" at times. Customers connect a thin client using a web browser (Sether, 2016). Vendors may handle everything in SaaS, including apps, services, information, interfaces, operating systems, virtualisation, servers, storage, and communication. End-users must utilize it.

Examples - Gmail, Adobe, MailChimp, Dropbox, and Slack.

Advantages of SaaS

• SaaS simplifies bug fixes and automates upgrades, relieving the pressure on in-house IT workers.

• Upgrades pose less risk to customers and have lower adoption costs.

• Users may launch applications without worrying about managing software or application. This reduces hardware and license expenses.

• Businesses can use APIs to combine SaaS apps with other software.

• SaaS providers are in charge of the app's security, performance, and availability to consumers.

• Users may modify their SaaS solutions to their organizational processes without having any impact according to their infrastructures.

Conclusion for Cloud Computing Services#

Cloud services provide several options for enterprises in various industries. And each of the main — PaaS, CaaS, FaaS, SaaS, and IaaS – has advantages and disadvantages. These services are available on a pay-as-you-go arrangement through the Internet. Rather than purchasing the software or even other computational resources, users rent them from a cloud computing solution (Rajiv Chopra, 2018). Cloud services provide the advantages of sophisticated IT infrastructure without the responsibility of ownership. Users pay, users gain access, and users utilise. It's as easy as that.

Containers are a type of virtualization for operating systems. A solitary container may host everything from little services or programming activities to a huge app. All compiled code, binary data, frameworks, and application settings are contained within a container. Containers, in contrast to host or device virtualization techniques, do not include OS copies. As a result, they are lighter and much more mobile, with significantly less expense. Several containers could well be installed for one or much more container groups in bigger commonly used software (Hussein, Mousa and Alqarni, 2019). A container scheduler, such as Kubernetes, may handle such groups.

Container as a Service (CaaS)#

Containers as a Service (CaaS) is a cloud-based option that enables app developers and IT organizations to use container-based virtualization to load, organize, execute, manage, and control containers. CaaS primarily refers to the automatic management and installation of container development tools. In CaaS, developers must install, operate, and manage the hardware on which containers operate. This architecture is a combination of cloud computers and networking traffic devices that must be overseen and managed by specialized DevOps employees.

CaaS allows developers to operate at the upper-level container stage rather than getting bogged down by lesser hardware maintenance [(Piraghaj et al., 2015)]. This provides a developer with greater clarity on the ultimate product, allowing for even more flexible performance and increased consumer experience.

CaaS Features and Benefits for DevOps#

CaaS solutions are used by companies and DevOps teams to:

• Increase the speed of software development.
• Develop creative cloud services at scale.

SDLC teams may deliver software platforms quicker while lowering the expenses, inefficiencies, and wasteful procedures that are common in technology design and delivery.

The benefits of CaaS are-

• CaaS enables it simpler to install and build application software, as well as to construct smaller services.
• Throughout programming, a container accumulation might manage various duties or programming settings (I Putu Agus Eka Pratama, 2021).
• A container network partnership is defined and bound to transport.
• CaaS guarantees that such specified and specialized container architectures may be swiftly installed in cloud computing.
• Assume a fictitious software system created using a microservice model, where the operation design is organized with a specific industry ID. Transactions, identification, and a checkout process are examples of service areas.
• Such software containers could be immediately deployed to a real-time framework using CaaS.
• Uploading programs deployed on the CaaS system allows program effectiveness via the use of tools like data incorporation and analysis.
• CaaS also incorporates automatic monitoring efficiency and coordination control integrated into.
• It helps team members to rapidly create clear views and decentralized applications for high reliability.
• Furthermore, CaaS empowers developers by providing quicker installation.
• Containers are utilized to avoid focused distribution; however, CaaS can save technical running expenses by lowering the number of DevOps people required to handle installations [(Saleh and Mashaly, 2019)].

Container as a Service (CaaS) drawbacks:

• The tech provided differs based on the supplier.
• It is risky to extract corporate information from the cloud.

CaaS Security Concerns#

• Containers are regarded as better than Windows Processes, although they do pose certain hazards.
• Containers, despite being easily configurable, use a very similar kernel to that of the OS.
• If indeed the containers are attacked, they are all in danger of becoming attacked [(Miller, Siems and Debroy, 2021)].
• When containers are installed within Cloud through CaaS, the hazards multiply dramatically.

Performance Restrictions#

• Containers are obvious sections that do not operate on physical hardware.
• Something is lacking with the additional level between both the physical hardware and the program containers and their contents [(Liagkou et al., 2021)].
• When these are combined with the container's system failures connected with the dedicated server, the consequence is a considerable decrease in performance.
• As a result, even with elevated equipment, enterprises must expect a significant decrease in container performance.

How Does CaaS Work?#

A container as just a service is a digital cloud that can be accessed and computed. Customers utilize the cloud infrastructure to distribute, build, maintain, and execute container-based apps. A GUI and API requests could be used to communicate with a cloud-based system (Zhang et al., 2019). The core of the CaaS system is an administration feature that allows complicated container architectures to be managed. Instrumentation technologies connect running containers and allow for automatic actions. The CaaS platform's current operator has a powerful effect on the services supplied by customers.

Why is CaaS Important?#

• Assists programmers in developing fully scalable containers and configuration management.
• It aids in the simplification of container management.
• Aids in the automation of essential IT operations such as Google Kubernetes and Docker.
• Increases team building speed, resulting in faster design and delivery.

Conclusion

And here is why several business owners love the containers. Containers' benefits greatly exceed any downsides. Its simplicity of use, resource efficiency, simplicity, and universality makes it a strong frontrunner among coders.

Gamers of all levels want programmers to employ new methods and future technologies to drive the gameplay adventure ahead, making games more realistic and demanding than ever before. The video game industry's globalisation and technical requirements are also expanding, with more powerful computer game visual effects demanding super strength processing capacity, increased displays, amazing adapters, and low latency networks. Several of today's most popular video games include racing or battle, which need a good response time and, as a consequence, a quick internet speed. These features are demanded by a large number of players, particularly enthusiasts and casual gamers. If any of the world's biggest gaming companies are to be believed, games' fate is sealed inside metal cages (Coward-Gibbs, 2019). It's placed on technological racks, blazing with little green lights, and computed within densely packed processors and shot out of remote servers over massive underground connections.

The Future of Hardware PC Gaming

Video games have already been offering amusement for both kids and adults for generations. They've come a long way since the early days of video games and the original Nintendo and Atari consoles. Video games have gotten more lifelike than ever before, with pixelated graphics and restricted acoustics becoming a distant past. Video games improve in tandem with technological advancements. The expense of developing a game for one of the operating systems has grown in tandem with the rising sophistication of video game development. It was previously inconceivable to spend millions on game production, but today's games may cost tens of millions if not hundreds of millions of dollars.

The video game industry is enormous. It is bigger than the film and music businesses together, and it's just becoming bigger. Though it does not receive the same level of attention as the film and music industries, there are over two billion players worldwide. This equates to 26% of the world's population.

Gamers are pushing the limits of computer hardware to get an advantage. People who purchase pricey GPU PCs that lead to better performance over other video game players appear to be the next occurrence. Consoles like the PS4 and Xbox are extremely common in the consumer market, but people who purchase pricey GPU PCs that give them an edge over other gamers appear to be the next occurrence (van Dreunen, 2020). The pull of consoles is still powerful. When it comes to giving an unrivalled gaming experience, nothing beats a gaming PC. It's wonderful to imagine that players will be able to play the latest FPS games at 60 frames per second or higher.

Cloud Service Providers Have Replaced Game Consoles#

The method video games and smartphone games are made, distributed, and performed has altered as a result of broad cloud use and availability. The duration has sped up dramatically. If a user has an online connection, they may now acquire different releases of games irrespective of where they are, cutting down on the time it takes to buy games, additional content, and add-ons. Cloud gaming, unlike video game systems such as consoles, shifts content delivery from the device to the cloud. Gamers broadcast games as reduced video frames, similar to how Netflix streams videos. The distinction is that if a key is pushed, the data is routed to a distant cloud server, which subsequently delivers the latest video frame. All of this occurs in a split second and seems to be identical to a game that has been downloaded into a device (Yates et al., 2017).

Microsoft, for example, has been migrating Xbox consoles to Xbox Cloud Computing services, which operate virtual Xbox controllers in its server farms and provide an experience similar to that of a home Xbox console. Microsoft is now updating to the Xbox Series X hardware, which offers faster load times, improved frame rates, and optimised games, as well as compatibility for streaming on bigger screen devices. Similarly, in October 2020, Amazon launched Luna, a cloud gaming service that offers unlimited game access. Luna makes use of a local gamepad controller that connects over a separate Wi-Fi connection to alleviate input latency in games.

Edge Gaming - The Gaming Attractiveness of Edge Computing#

The majority of game computation is now done on gadgets locally. While some computing may be done on a cloud server where a device can transmit data to be analysed and then delivered, these systems are often located far away in enormous data centres, which implies the time required for such data to be delivered will eventually diminish the gameplay experience.

Instead of a single huge remote server, mobile edge computing depends on multiple tiny data centres that are located in closer physical proximity. So because devices won't have to transfer data to a central computer, process it, and then deliver the information, users can preserve processing power on the device for a better, quicker gaming experience (Schmoll et al., 2018).

Conclusion#

The desire for additional gaming platforms and greater levels of involvement is growing, and game creators and businesses must take advantage of this. The player experience will alter radically as these new technologies become more common, and a new generation of hugely multiplayer modes will be introduced online, attracting new consumers. Gaming is taking over the media world. If you are unfamiliar with this information, please take a look around. While cloud gaming is still in its early stages, it demonstrates that computation can take place outside of the device. Developers should turn to edge gaming to create an experience wherein gamers can engage in a real-time multiplayer scenario since cloud gaming has always had physical difficulties (Paolo Ruffino, 2018).

Those who specialize in cyberspace and data security have been encouraging IT executives and internet providers to adapt to the challenges of a dynamic and fast-changing digital environment. With the operationalization of 5G networks, market expectations and the supply of new capabilities are rapidly increasing. For telecommunications companies, 5G represents a substantial opportunity to enhance consumer experiences and drive sales growth. Not only will 5G provide better internet connectivity, but it will also enable life-changing innovations that were once only imagined in sci-fi (Al-Dunainawi, Alhumaima, & Al-Raweshidy, 2018). While 5G connection speeds and accessibility have received much attention, understanding 5G's early prototype aspirations and its perception in network services is also crucial.

5G's Expectations Beyond Cloud Computing Companies#

The challenges of managing business development scenarios will be compounded by the complexities introduced by 5G. Some organizations may find themselves unprepared for these developments, facing challenges such as poor bandwidth and performance, especially if operating at frequencies below 6 gigahertz. However, true 5G promises capabilities that extend from utility and industrial grids to autonomous vehicles and retail applications, potentially transforming network edges (Jabagi, Park, & Kietzmann, 2020). For those unprepared, the ability to handle data could degrade significantly, leading to major latency issues and a compromised experience for both consumers and staff.

5G's Expectations Are Only the Beginning of the Challenge#

Implementing adequate protection to safeguard customers and crucial data could lead to congestion within systems. Ensuring that applications operate effectively at 5G speeds is one challenge; guaranteeing safety over an expanding network poses additional issues (Lee, 2019). Cloud computing companies face limitations in addressing these challenges.

It Will Be Necessary to Plan Carefully#

Cybersecurity professionals are considering two main approaches to address 5G issues: handling security procedures of the 5G base on the operator side or addressing edge protection where 5G acts as a fallback or gateway node, often as part of an SD-WAN implementation. Both strategies will require automation and artificial intelligence capabilities to keep up with conventional edge demands. Additional high-performance protection at the cloud edge will also be necessary (Ahamed & Faruque, 2021). Integrated systems must scale up with additional virtual machines and filters while scaling down by adding new elements to manage increased demand and ensure smooth, effective, and safe operations. As 5G accelerates commerce and applications, it will also speed up cyber-attacks.

Addressing 5G's Expectation Problems Is Not a Choice#

Currently, 5G generates around $5 billion in annual revenue for operators, expected to rise to $357 billion by 2025. This shift necessitates significant adjustments in the deployment and usage of 5G. Many businesses lack the expertise to meet these requirements. The pursuit of the best products and systems has led to complex, hard-to-implement systems. Under 5G's pressure, these systems may perform poorly (Guevara & Auat Cheein, 2020). Historically, cybersecurity aimed to balance safety with connectivity and efficiency. As internet providers and security groups face mounting challenges, the shift to 5G represents only the beginning of a current paradigm shift.

Five Approaches to Improve the 5G User Experience#

1. Close the knowledge gap to effectively teach and advertise the benefits of 5G.
2. Ensure high consistency in both indoor and outdoor services.
3. Accelerate the commercialization of new and existing application cases.
4. Address the network infrastructure demands driven by new internet services (Lee, 2019).
5. Consider customer desires to envision new applications.

Conclusion#

5G is driving the development of innovative application cases and commercial opportunities, such as mobile gaming, fixed wireless access, and enhanced consumer experiences. As 5G expands, it will dramatically impact data retrieval, causing significant latency issues and affecting the user experience (Ahn, 2021). The window of opportunity for solutions to meet 5G demands is closing. Companies must act swiftly to capitalize on this opportunity and prepare for the evolving demands of 5G and the imminent arrival of 6G.

More 5G-based cloud computing companies will emerge to meet the needs of the 5G environment.

Introduction#

5G has been substantially implemented, and network operators now have a huge opportunity to monetize new products and services for companies and customers. Network slicing is a critical tool for achieving customer service and assured reliability. Ericsson has created the most comprehensive network slicing platform, comprising 5G Radio Access Networks (RAN) slicing, enabling automatic and quick deployment of services of new and creative 5G use scenarios, using an edge strategy (Subedi et al., 2021). Ericsson 5G Radio Access Networks (RAN) Slicing has indeed been released, and telecom companies are enthusiastic about the possibilities of new 5G services. For mobile network operators, using system control to coordinate bespoke network slices in the personal and commercial market sectors can provide considerable income prospects. Ericsson provides unique procedures to ensure that speed and priority are maintained throughout the network slicing process. Not only do they have operational and business support systems (OSS/BSS), central, wireless, and transit systems in their portfolio, but they also have complete services like Network Support and Service Continuity (Debbabi, Jmal and Chaari Fourati, 2021).

What is 5G Radio Access Networks (RAN) Slicing?#

The concept of network slicing is incomplete without the cooperation of communication service providers. It assures that the 5G Radio Access Networks (RAN) Slicing-enabled services are both dependable and effective. Carriers can't ensure slice efficiency or meet service contracts unless they have network support and service continuity. Furthermore, if carriers fail to secure slice performance or meet the service-level agreement, they may face punishment and the dangers of losing clients (Mathew, 2020). Ericsson 5G Radio Access Networks (RAN) Slicing provides service operators with the unique and assured quality they have to make the most of their 5G resources. The novel approach was created to improve end-to-end network slicing capabilities for radio access network managing resources and coordination. As a consequence, it constantly optimizes radio resource allocation and priority throughout multiple slices to ensure service-level commitments are met. This software solution, which is based on Ericsson radio experience and has a flexible and adaptable design, will help service providers to satisfy expanding needs in sectors such as improved broadband access, network services, mission-critical connectivity, and crucial Internet of Things (IoT) (Li et al., 2017).

Ericsson Network Support#

Across complex ecosystems, such as cloud networks, Network Support enables data-driven fault isolation, which is also necessary to efficiently manage the complexity in [5G systems]. To properly manage the complexity of 5G networks, Ericsson Network Support offers data-driven fault isolation. This guarantees that system faults are quickly resolved and that networks are reliable and robust. Software, equipment, and replacement parts are divided into three categories in Network Support. By properly localizing defects and reducing catastrophic occurrences at the solution level, Ericsson can offer quick timeframes and fewer site visits. Ericsson also supports network slicing by handling multi-vendor ecosystem fault separation and resolving complications among domains (Zhang, 2019). Data-driven fault isolation from Ericsson guarantees the quick resolution of connection problems, as well as strong and effective networks, and includes the following innovative capabilities:

• Ericsson Network Support (Software) provides the carrier's software platform requirements across classic, automated, and cloud-based services in extremely sophisticated network settings. It prevents many mishaps by combining powerful data-driven support approaches with strong domain and networking experience.

• Ericsson Hardware Services provides network hardware support. Connected adds advanced technologies to remote activities, allowing for quicker problem identification and treatment. It integrates network data with past patterns to provide service personnel and network management with relevant real-time information. It is feasible to pinpoint errors with greater precision using remote scans and debugging.

• The Spare Components Management solution gives the operator's field engineers access to the parts they need to keep the network up and running (Subedi et al., 2021). Ericsson will use its broad network of logistical hubs and local parts depots to organize, warehouse, and transport the components.

Ericsson Service Continuity#

To accomplish 5G operational readiness, Service Continuity provides AI-powered, proactive assistance, backed by tight cooperation and Always-On service. Advanced analytical automation and reactive anticipatory insights provided by Ericsson Network Intelligence allow Service Continuity services. It focuses on crucial functionality to help customers reach specified business objectives while streamlining processes and ensuring service continuity (Katsalis et al., 2017). It is based on data-driven analysis and worldwide knowledge that is given directly and consists of two services:

• Ericsson Service Continuity for 5G: Enables the clients' networks to take remedial steps forward in time to prevent end-user disruption, allowing them to move from responsive to proactively network services.

• Ericsson Service Continuity for Private Networks is a smart KPI-based support product for Industry 4.0 systems and services that is targeted to the unique use of Private Networks where excellent performance is critical (Mathew, 2020).

Conclusion for 5G Network Slicing

Network slicing will be one of the most important innovations in the 5G network area, transforming the telecommunications sector. The 5G future necessitates a network that can accommodate a diverse variety of equipment and end customers. Communication service providers must act quickly as the massive network-slicing economic potential emerges (Da Silva et al., 2016). However, deciding where to begin or where to engage is difficult. Ericsson's comprehensive portfolio and end-to-end strategy include Network Support and Service Continuity services. Communication service providers across the world would then "walk the talk" for Network Slicing in the 5G age after incorporating them into their network operations plan.

References#

• Da Silva, I.L., Mildh, G., Saily, M. and Hailu, S. (2016). A novel state model for 5G Radio Access Networks. 2016 IEEE International Conference on Communications Workshops (ICC).
• Debbabi, F., Jmal, R. and Chaari Fourati, L. (2021). 5G network slicing: Fundamental concepts, architectures, algorithmics, project practices, and open issues. Concurrency and Computation: Practice and Experience, 33(20).
• Katsalis, K., Nikaein, N., Schiller, E., Ksentini, A. and Braun, T. (2017). Network Slices toward 5G Communications: Slicing the LTE Network. IEEE Communications Magazine, 55(8), pp.146–154.
• Li, X., Samaka, M., Chan, H.A., Bhamare, D., Gupta, L., Guo, C. and Jain, R. (2017). Network Slicing for 5G: Challenges and Opportunities. IEEE Internet Computing, 21(5), pp.20–27.
• Mathew, A., 2020, March. Network slicing in 5G and the security concerns. In 2020 Fourth International Conference on Computing Methodologies and Communication (ICCMC) (pp. 75-78). IEEE.
• Subedi, P., Alsadoon, A., Prasad, P.W.C., Rehman, S., Giweli, N., Imran, M. and Arif, S. (2021). Network slicing: a next-generation 5G perspective. EURASIP Journal on Wireless Communications and Networking, 2021(1).
• Zhang, S. (2019). An Overview of Network Slicing for 5G. IEEE Wireless Communications, [online] 26(3), pp.111–117.

Introduction#

Machine Learning-Based Techniques for observation and administration are especially suitable for sophisticated network infrastructure operations. Assume a machine learning (ML) program designed to predict mobile service disruptions. Whenever a network administrator obtains an alert about a possible imminent interruption, they can take bold measures to address bad behaviour before something affects users. The machine learning group, which constructs the underlying data processors that receive raw flows of network performance measurements and store them into such a Machine Learning (ML)-optimized databases, assisted in the development of the platform. The preliminary data analysis, feature engineering, Machine Learning (ML) modeling, and hyperparameter tuning are all done by the research team. They collaborate to build a Machine Learning (ML) service that is ready for deployment (Chen et al., 2020). Customers are satisfied because forecasts are made with the anticipated reliability, network operators can promptly repair network faults, and forecasts are produced with the anticipated precision.

What is Machine Learning (ML) Lifecycle?#

The data analyst and database administrators obtain multiple procedures (Pipeline growth, Training stage, and Inference stage) to establish, prepare, and start serving the designs using the massive amounts of data that are engaged in different apps so that the organisation can take full favor of artificial intelligence and Machine Learning (ML) methodologies to generate functional value creation (Ashmore, Calinescu and Paterson, 2021).

Monitoring allows us to understand performance concerns#

Machine Learning (ML) models are based on numbers, and they tacitly presume that the learning and interpretation data have the same probability model. Basic variables of a Machine Learning (ML) model are tuned during learning to maximise predicted efficiency on the training sample. As a result, Machine Learning (ML) models' efficiency may be sub-optimal when compared to databases with diverse properties. It is common for data ranges to alter over time considering the dynamic environment in which Machine Learning (ML) models work. This transition in cellular networks might take weeks to mature as new facility units are constructed and updated (Polyzotis et al., 2018). The datasets that ML models consume from multiple data sources and data warehouses, which are frequently developed and managed by other groups, must be regularly watched for unanticipated issues that might affect ML model results. Additionally, meaningful records of input and model versions are required to guarantee that faults may be rapidly detected and remedied.

Data monitoring can help prevent machine learning errors#

Machine Learning (ML) models have stringent data format requirements because they rely on input data. Whenever new postal codes are discovered, a model trained on data sets, such as a collection of postcodes, may not give valid forecasts. Likewise, if the source data is provided in Fahrenheit, a model trained on temperature readings in Celsius may generate inaccurate forecasts (Yang et al., 2021). These small data changes typically go unnoticed, resulting in performance loss. As a result, extra ML-specific model verification is recommended.

Variations between probability models are measured#

The steady divergence between the learning and interpretation data sets, known as idea drift, is a typical cause of efficiency degradation. This might manifest itself as a change in the mean and standard deviation of quantitative characteristics. As an area grows more crowded, the frequency of login attempts to a base transceiver station may rise. The Kolmogorov-Smirnov (KS) test is used to determine if two probability ranges are equivalent (Chen et al., 2020).

Preventing Machine Learning-Based Techniques for system engineering problems#

The danger of ML efficiency deterioration might be reduced by developing a machine learning system that specifically integrates data management and model quantitative measurement tools. Tasks including data management and [ML-specific verification] are performed at the data pipeline stage. To help with these duties, the programming group has created several public data information version control solutions. Activities for monitoring and enrolling multiple variations of ML models, as well as the facilities for having to serve them to end-users, are found at the ML model phase (Souza et al., 2019). Such activities are all part of a bigger computer science facility that includes automation supervisors, docker containers tools, VMs, as well as other cloud management software.

Data and machine learning models versioning and tracking for Machine Learning-Based Techniques#

The corporate data pipelines can be diverse and tedious, with separate elements controlled by multiple teams, each with their objectives and commitments, accurate data versioning and traceability are critical for quick debugging and root cause investigation (Jennings, Wu and Terpenny, 2016). If sudden events to data schemas, unusual variations to function production, or failures in intermediate feature transition phases are causing ML quality issues, past and present records can help pin down when the problem first showed up, what data is impacted, or which implication outcomes it may have affected.

Using current infrastructure to integrate machine learning systems#

Ultimately, the machine learning system must be adequately incorporated into the current technological framework and corporate environment. To achieve high reliability and resilience, ML-oriented datasets and content providers may need to be set up for ML-optimized inquiries, and load-managing tools may be required. Microservice frameworks, based on containers and virtual machines, are increasingly widely used to run machine learning models (Ashmore, Calinescu, and Paterson, 2021).

Conclusion for Machine Learning-Based Techniques#

The use of Machine Learning-Based Techniques could be quite common in future communication designs. At this scale, vast amounts of data streams might be recorded and stored, and traditional techniques for assessing better data and dispersion drift could become operationally inefficient. The fundamental techniques and procedures may need to be changed. Moreover, future designs are anticipated to see an expansion in the transfer of computing away from a central approach and onto the edge, closer to the final users (Hwang, Kesselheim and Vokinger, 2019). Decreased lags and Netflow are achieved at the expense of a more complicated framework that introduces new technical problems and issues. In such cases, based on regional federal regulations, data gathering and sharing may be restricted, demanding more cautious ways to programs that prepare ML models in a safe, distributed way.

References#

• Ashmore, R., Calinescu, R. and Paterson, C. (2021). Assuring the Machine Learning Lifecycle. ACM Computing Surveys, 54(5), pp.1–39.
• Chen, A., Chow, A., Davidson, A., DCunha, A., Ghodsi, A., Hong, S.A., Konwinski, A., Mewald, C., Murching, S., Nykodym, T., Ogilvie, P., Parkhe, M., Singh, A., Xie, F., Zaharia, M., Zang, R., Zheng, J. and Zumar, C. (2020). Developments in MLflow. Proceedings of the Fourth International Workshop on Data Management for End-to-End Machine Learning.
• Hwang, T.J., Kesselheim, A.S. and Vokinger, K.N. (2019). Lifecycle Regulation of Artificial Intelligence– and Machine Learning–Based Software Devices in Medicine. JAMA, 322(23), p.2285.
• Jennings, C., Wu, D. and Terpenny, J. (2016). Forecasting Obsolescence Risk and Product Life Cycle With Machine Learning. IEEE Transactions on Components, Packaging and Manufacturing Technology, 6(9), pp.1428–1439.
• Polyzotis, N., Roy, S., Whang, S.E. and Zinkevich, M. (2018). Data Lifecycle Challenges in Production Machine Learning. ACM SIGMOD Record, 47(2), pp.17–28.
• Souza, R., Azevedo, L., Lourenco, V., Soares, E., Thiago, R., Brandao, R., Civitarese, D., Brazil, E., Moreno, M., Valduriez, P., Mattoso, M., Cerqueira, R. and Netto, M.A.S. (2019).
• Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering. 2019 IEEE/ACM Workflows in Support of Large-Scale Science (WORKS).
• Yang, C., Wang, W., Zhang, Y., Zhang, Z., Shen, L., Li, Y. and See, J. (2021). MLife: a lite framework for machine learning lifecycle initialization. Machine Learning.

Introduction#

In the field of healthcare technology, we are at the start of a high-tech era. AI technology, cloud-based services, the Internet of Things, and big data have all become popular topics of conversation among healthcare professionals as a way to provide high-quality services to patients while cutting costs. Due to ambitions for global application, the fifth generation of cellular technology, or 5G, has gotten a lot of interest. While the majority of media attention has centered on the promise of "the internet of things," the ramifications of 5G-enabled technologies in health care are yet to be addressed (Zhang and Pickwell-Macpherson, 2019). The adoption of 5G in healthcare is one of the elements that is expected to have a significant impact on patient value. 5G, or fifth-generation wireless communications, would not only provide much more capacity but also be extremely responsive owing to its low latency. 5G opens up a slew of possibilities for healthcare, including remote diagnostics, surgery, real-time surveillance, and extended telemedicine (Thayananthan, 2019). This article examines the influence of 5G technology on healthcare delivery and quality, as well as possible areas of concern with this latest tech.

What is 5G?#

The fifth generation of wireless communication technology is known as 5G. Like the preceding fourth generation, the core focus of 5G is speed. Every successive generation of wireless networks improves on the previous one in terms of speed and capability. 5G networks can deliver data at speeds of up to 10 terabytes per second. Similarly, while older networks generally have a delay of 50 milliseconds, 5G networks have a latency of 1–3 milliseconds. With super-fast connection, ultra-low latency, and extensive coverage, 5G marks yet another step ahead (Carlson, 2020). From 2021 to 2026, the worldwide 5G technology market is predicted to grow at a CAGR of 122.3 percent, reaching $667.90 billion. These distinguishing characteristics of 5G enable the possible change in health care as outlined below.

5G's Importance in Healthcare#

Patient value has been steadily declining, resulting in rising healthcare spending. In addition, there is rising concern over medical resource imbalances, ineffective healthcare management, and uncomfortable medical encounters. To address these issues, technologies such as the Internet of Things (IoT), cloud technology, advanced analytics, and artificial intelligence are being developed to enhance customer care and healthcare efficiency while lowering total healthcare costs (Li, 2019). The healthcare business is likely to see the largest improvements as a result of 5G's large bandwidth, reduced latency, and low-power-low-cost. Healthcare professionals investigated and developed several connected-care use cases, but widespread adoption was hampered by the limits of available telecommunications. High-speed and dependable connections will be critical as healthcare systems migrate to a cloud-native design. High data transfer rates, super-low latency, connection and capacity, bandwidth efficiency, and durability per unit area are some of the distinctive properties of 5G technology that have the potential to assist tackle these difficulties (Soldani et al., 2017). Healthcare stakeholders may reorganize, transition to comprehensive data-driven individualized care, improve medical resource use, provide care delivery convenience, and boost patient value thanks to 5G.

5 ways that 5G will change healthcare#

• Large image files must be sent quickly.
• Expanding the use of telemedicine.
• Improving augmented reality, virtual reality, and spatial computing.
• Remote monitoring that is reliable and real-time.
• Artificial Intelligence

Healthcare systems may enhance the quality of treatment and patient satisfaction, reduce the cost of care, and more by connecting all of these technologies over 5G networks (Att.com, 2017). 5G networks can enable providers to deliver more tailored and preventative treatment, rather than just responding to patients' illnesses, which is why many healthcare workers joined providers during the first round.

Challenges#

As with other advances, many industry professionals are cautious about 5G technology's worldwide acceptance in healthcare, as evidenced by the following significant challenges:

• Concerns about privacy and security - The network providers must adhere to the health - care industry's stringent privacy regulations and maintain end-to-end data protection across mobile, IoT, and connected devices.
• Compatibility of Devices - The current generation of 4G/LTE smartphones and gadgets are incompatible with the upcoming 5G networks. As a result, manufacturers have begun to release 5G-enabled smartphones and other products.
• Coverage and Deployment - The current generation of 4G/LTE smartphones and gadgets are incompatible with the upcoming 5G networks. The present 4G network uses certain frequencies on the radio frequency band, often around 6 GHz; however, such systems are available exclusively in a few nations' metro/urban regions, and telecom carriers must create considerable equipment to overcome this difficulty (Chen et al., 2017).
• Infrastructure - As part of the 5G network needs, healthcare facilities, clinics, and other healthcare providers/organizations will need to upgrade and refresh their infrastructure, apps, technologies, and equipment.

Conclusion#

5G has the potential to revolutionize healthcare as we know it. As we saw during the last epidemic, the healthcare business needs tools that can serve people from all socioeconomic backgrounds. Future improvements and gadgets based on new 5G devices and computers can stimulate healthcare transformation, expand consumer access to high-quality treatment, and help close global healthcare inequities (Thuemmler et al., 2017). For enhanced healthcare results, 5G offers network stability, speed, and scalability for telemedicine, as well as catalyzing broad adoption of cutting-edge technologies like artificial intelligence, data science, augmented reality, and the IoT. Healthcare organizations must develop, test, and deploy apps that make use of 5G's key capabilities, such as ultra-high bandwidth, ultra-reliability, ultra-low latency, and huge machine connections.

References#

• Att.com. (2017). 5 Ways 5G will Transform Healthcare | AT&T Business. [online] Available at: https://www.business.att.com/learn/updates/how-5g-will-transform-the-healthcare-industry.html.
• Carlson, E.K. (2020). What Will 5G Bring? Engineering.
• Chen, M., Yang, J., Hao, Y., Mao, S. and Hwang, K. (2017). A 5G Cognitive System for Healthcare. Big Data and Cognitive Computing, 1(1), p.2.
• Li, D. (2019). 5G and Intelligence Medicine—How the Next Generation of Wireless Technology Will Reconstruct Healthcare? Precision Clinical Medicine, 2(4).
• Soldani, D., Fadini, F., Rasanen, H., Duran, J., Niemela, T., Chandramouli, D., Hoglund, T., Doppler, K., Himanen, T., Laiho, J. and Nanavaty, N. (2017). 5G Mobile Systems for Healthcare. 2017 IEEE 85th Vehicular Technology Conference (VTC Spring).
• Thayananthan, V. (2019). Healthcare Management using ICT and IoT-based 5G. International Journal of Advanced Computer Science and Applications, 10(4).
• Thuemmler, C., Gavras, A. and Roa, L.M. (2017). Impact of 5G on Healthcare. 5G Mobile and Wireless Communications Technology, pp. 593-613.
• Zhang, M. and Pickwell-Macpherson, E. (2019). The future of 5G Technologies in healthcare. 5G Radio Technologies Seminar.

Introduction#

Consumers want quicker, better, more convenient, and revolutionary data speeds in this internet age. Many people are eager to watch movies on their smartphones while also downloading music and controlling many IoT devices. They anticipate a 5G connection, which will provide 100 times quicker speeds, 10 times more capacity, and 10 times reduced latency. The transition to 5G necessitates significant expenditures from service providers. To support new income streams and enable better, more productive, and cost-effective processes and exchanges, BSS must advance in tandem with 5G network installations (Pablo Collufio, 2019). Let's get ready to face the challenges of 5G monetization.

Why 5G monetization?#

The appropriate 5G monetization solutions may be a superpower, allowing CSPs to execute on 5G's potential from the start. The commercialization of 5G is a hot topic. "Harnessing the 5G consumer potential" and "5G and the Enterprise Opportunity" are two studies that go through the various market prospects. They illustrate that, in the long term, there is a tremendous new income opportunity for providers at various implementation rates, accessible marketplaces, and industry specializations. “Getting creative with 5G business models” highlights how AR/VR gameplay, FWA (Fixed Wireless Access), and 3D video encounters could be offered through B2C, B2B, and B2B2X engagement models in a variety of use scenarios. To meet the 5G commitments of increased network speeds and spectrum, lower latency, assured service quality, connectivity, and adaptable offers, service suppliers must discuss their BSS evolution alongside their 5G installations, or risk being unable to monetize those new use cases when they become a real thing (Munoz et al., 2020). One of the abilities that will enable providers to execute on their 5G promises from day one is 5G monetization. CSPs must update their business support systems (BSS) in tandem with their 5G deployment to meet 5G use scenarios and provide the full promise of 5G, or risk slipping behind in the 5G race for lucrative 5G services (Rao and Prasad, 2018).

Development of the BSS architecture#

To fully realize the benefits of 5G monetization, service providers must consider the growth of their telecom BSS from a variety of angles:

• Integrations with the network - The new 5G Basic standards specify a 5G Convergent Charging System (CCS) with a 5G Charging Function (CHF) that enables merged charging and consumption limit restrictions in the new service-based architecture that 5G Core introduces.
• Service orchestration - The emergence of distributed systems and more business services need more complicated and stricter service coordination and fulfillment to ensure that goods, packages, ordeals, including own and third-party products, are negotiated, purchased, and activated as soon as clients require them.
• Expose - Other BSS apps, surrounding levels such as OSS and Central networks, or 3rd parties and collaborators who extend 5G services with their abilities might all be consumers of BSS APIs (Mor Israel, 2021).
• Cloud architecture - The speed, reliability, flexibility, and robustness required by 5G networks and services necessitate a new software architecture that takes into consideration BSS deployments in the cloud, whether private, public, or mixed.

Challenges to 5G Monetization#

Even though monetizing 5G networks appears to be a profitable prospect for telecommunications, it is not without flaws. The following are the major challenges:

• Massive upfront investments in IT infrastructure, network load, and a radio access system, among other things.
• To get optimal ROI, telecommunications companies must establish viable monetization alternatives (Bega et al., 2019).
• The commercialization of 5G necessitates a change in telecom operations.

Case of Augmented Reality Games and Intelligent Operations#

With the 5G Core, BSS, and OSS in place, it's time to bring on a new partner: a cloud gaming firm that wants to deliver augmented reality monetization strategies to the operator's users (Feng et al., 2020). For gaming traffic, they want a specific network slice with assured service quality. Through a digital platform, a member in a smart, completely automated network may request their network slice and specify their SLAs. BSS decomposes this order into multiple sub-orders, such as the construction and provisioning of the particular portion through the OSS, once it receives it. The operator additionally uses their catalog-driven design to describe the item offered that its customers will acquire to get onboard new on the partner's network slice all in one location. This deal is immediately disseminated to all relevant systems, including online charging, CRM, and digital platforms, and may be generally consumed.

Conclusion#

5G can impact practically every industry and society. Even though there is a lot of ambiguity around 5G and a lot of technical concerns that need to be resolved, one thing is certain: 5G is the next big thing. Finally, whenever a user buys a new plan, he or she is automatically onboarded in the particular portion, often without affecting the system. The partnership will be able to monitor the network health and quality of various types of services for each customer in real time and will be able to take immediate decisions or conduct promotions based on this data (Bangerter et al., 2014). New platforms may adapt to changes based on factual resource use thanks to the BSS cloud architecture. All information regarding purchases, items, network usage, and profitability, among other things, is given back into circulation and utilized as feeds for infrastructure and catalog design in a closed-loop method.

References#

• Bangerter, B., Talwar, S., Arefi, R., and Stewart, K. (2014). Networks and devices for the 5G era. IEEE Communications Magazine, 52(2), pp.90–96.
• Bega, D., Gramaglia, M., Banchs, A., Sciancalepore, V. and Costa-Perez, X. (2019). A Machine Learning approach to 5G Infrastructure Market optimization. IEEE Transactions on Mobile Computing, pp.1–1.
• Feng, S., Niyato, D., Lu, X., Wang, P. and Kim, D.I. (2020). Dynamic Game and Pricing for Data Sponsored 5G Systems With Memory Effect. IEEE Journal on Selected Areas in Communications, 38(4), pp.750–765.
• Mor Israel (2021). How BSS can enable and empower 5G monetization. online Available at: https://www.ericsson.com/en/blog/2021/4/how-bss-can-enable-and-empower-5g-monetization.
• Munoz, P., Adamuz-Hinojosa, O., Navarro-Ortiz, J., Sallent, O. and Perez-Romero, J. (2020). Radio Access Network Slicing Strategies at Spectrum Planning Level in 5G and Beyond. IEEE Access, 8, pp.79604–79618.
• Pablo Collufio, D. (2019). 5G: Where is the Money? e-archivo.uc3m.es. online.
• Rao, S.K. and Prasad, R. (2018). Telecom Operators’ Business Model Innovation in a 5G World. Journal of Multi Business Model Innovation and Technology, 4(3), pp.149–178.

Learn more about Edge Computing and its usage in different fields. Keep reading our blogs.

Edge VMs And Edge Containers are nothing but VMs and Containers used in Edge Locations, or are they different? This topic gives a brief insight into it.

Introduction

If you have just recently begun learning about virtualization techniques, you could be wondering what the distinctions between containers and VMs. The issue over virtual machines vs. containers is at the centre of a discussion over conventional IT architecture vs. modern DevOps approaches. Containers have emerged as a formidable presence in cloud-based programming, thus it's critical to know what they are and isn't. While containers and virtual machines have their own set of features, they are comparable in that they both increase IT productivity, application portability, and DevOps and the software design cycle (Zhang et al., 2018). The majority of businesses have adopted cloud computing, and it has shown to be a success, with significantly faster workload launches, simpler scalability and flexibility, and fewer hours invested on underlying traditional data centre equipment. Traditional cloud technology, on the other hand, isn't ideal in every case.

Microsoft Azure, Amazon AWS, and Google Cloud Platform (GCP) are all traditional cloud providers with data centres all around the world. Whereas each company's data centre count is continually growing, these data centres are not near enough to consumers when an app requires optimal speed and low lag (Li and Kanso, 2015). Edge computing is useful when speed is important or produced data has to be kept near to the consumers.

What is the benefit of Edge Computing?#

Edge computing is a collection of localized mini data centres that relieve the cloud of some of its responsibilities, acting as a form of "regional office" for local computing chores rather than transmitting them to a central data centre thousands of miles away. It's not meant to be a replacement for cloud services, but rather a supplement. Instead of sending sensitive data to a central data centre, edge computing enables you to analyse it at its origin (Khan et al., 2019). Minimal sensitive data is sent across devices and the cloud, which means greater security for both you and your users. Most IoT initiatives may also be completed at a lower cost by decreasing data transit and storage space using traditional techniques.

What are Edge VMs?#

Edge virtual machines (Edge VMs) are technological advancements of standard VM in which the storage and computation capabilities that support the VM are physically closer to the end-users. Each VM is a self-contained entity with its OS, capable of handling almost any program burden (Millhouse, 2018). The flexibility, adaptability, and optimum availability of such tasks are significantly improved by VM designs. Patching, upgrades, and care of the virtual machine's operating system are required regularly. Monitoring is essential for ensuring the virtual machine instances' and underpinning physical hardware infrastructure's stability. Backup and data recovery activities must also be considered. All of this adds up to a lot of time spent on repair and supervision.

What are Edge Containers?#

Edge containers are decentralized computing capabilities that are placed as near to the end customer as feasible in an attempt to decrease delay, conserve data, and improve the overall user experiences. A container is a sandboxed, isolated version of a component of a programme. Containers still enable flexibility and adaptability, although usually isn't for every container in an application framework, only for the one that needs expanding (Pahl and Lee, 2015). It's simple to reboot multiple copies of a container image and bandwidth allocation between them once you've constructed one.

What's the difference Between VMs and Containers even without the context Edge?#

Containers are perfect where your programme supports a microservices design, which allows application programs to function and scale freely. Containers may operate anywhere as long as your public cloud or edge computing platform has a Docker engine (Sharma et al., 2016). Also, there is a reduction in operational and administrative costs. But when your application requires particular operating system integration that is not accessible in a container, VM is still suggested when you need access to the entire OS. VMs are required if you want or need additional control over the software architecture, or if you want or need to execute many apps on the same host.

Next Moves#

Edge computing is a viable solution for applications that require high performance and low latency communication. Gaming, broadcasting, and production are all common options. You may deliver streams of data from near to the user or retain data close to the source, which is more convenient than using open cloud data centres (Sonmez, Ozgovde and Ersoy, 2018). You can pick what is suitable for your needs now that you know more about edge computing, including the differences between edge VMs and edge containers.

Learn more about Edge Computing and its usage in different fields - Nife Blogs

Introduction#

The gaming business, which was formerly considered a specialized sector, has grown to become a giant $120 billion dollar industry in the latest years (Scholz, 2019). The gaming business has long attempted to capitalize on new possibilities and inventive methods to offer gaming adventures, as it has always been the leading result of technology. The emergence of cloud gaming services is one of the most exciting advances in cloud computing technology in recent years. To succeed, today's gamers speed up connections. Fast connectivity contributes to improved gameplay. Gamers may livestream a collection of games on their smartphone, TV, platform, PC, or laptop for a monthly cost ranging from $10 to $35 (Beattie, 2020).

Reasons to buy a gaming computer:

• The gameplay experience is second to none.
• Make your gaming platform future-proof.
• They're prepared for VR.
• Modified versions of your favourite games are available to play.
• More control and better aim.

Why is Hardware PC gaming becoming more popular?#

Gamers are stretching computer hardware to its boundaries to get an edge. Consoles like the PlayStation and Xbox are commonplace in the marketplace, but customers purchasing pricey gaming-specific PCs that give a competitive advantage over the other gamers appear to be the next phenomenon. While the pull of consoles remains strong, computer gaming is getting more and more popular. It was no longer only for the die-hards who enjoy spending a weekend deconstructing their computer. A gaming PC is unrivalled when it comes to providing an unrivalled gaming experience. It's incredible to think that gamers could play the newest FPS games at 60fps or greater. Steam is a global online computer gaming platform with 125 million members, compared to 48 million for Xbox Live (Galehantomo P.S, 2015). Gaming computers may start around $500 and soon grow to $1500 or more, which is one of the most significant drawbacks of purchasing gaming PCs.

The majority of games are now downloadable and played directly on cell phones, video game consoles, and personal computers. With over 3 billion gamers on the planet, the possibility and effect might be enormous (Wahab et al., 2021). Cloud gaming might do away with the need for dedicated platforms, allowing players to play virtually any game on practically any platform. Users' profiles, in-game transactions, and social features are all supported by connectivity, but the videogames themselves are played on the gamers' devices. Gaming has already been growing into the cloud in this way for quite some time. Every big gaming and tech firm seems to have introduced a cloud gaming service in the last two years, like Project xCloud by Microsoft, PlayStation Now by Sony, and Stadia by Google.

Cloud Computing's Advantages in the Gaming World:

• Security
• Compatibility
• Cost-effective
• Accessibility
• No piracy
• Dynamic support

What are Cloud Gaming Services, and how do they work?#

Cloud gaming shifts the processing of content from the user's device to the cloud. The game's perspective is broadcast to the person's devices through content delivery networks with local stations near population centres, similar to how different channels distribute the material. Size does matter, just like it does with video. A modest cell phone screen can show a good gaming feed with far fewer bits than a 55" 4K HDTV. In 2018, digital downloads accounted for more than 80% of all video game sales. A bigger stream requires more data, putting additional strain on the user's internet connection. Cloud streaming services must automatically change the bandwidth to offer the lowest amount of bits required for the best service on a specific device to control bandwidth (Cai et al., 2016).

Edge Gaming - The appeal of Edge Computing in Gaming#

Revenue from mobile gaming is growing more sociable, engaging, and dynamic. As games become more collaborative, realistic, and engaging, mobile gaming revenue is predicted to top $95 billion worth by 2022 (Choy et al., 2014). With this growth comes the difficulty of meeting consumers' desire for ultra-fast, low-latency connectivity, which traditional data centres are straining to achieve. Edge computing refers to smaller data centres that provide cloud-based computational services and resources closer to customers or at the network's edge. In smartphone games, even just a fraction of a millisecond of latency would be enough to completely ruin the gameplay. Edge technology and 5G connection assist in meeting low-latency, high-bandwidth needs by bringing high cloud computing power directly to consumers and equipment while also delivering the capacity necessary for high, multi-player gameplay.

Issues with Cloud Gaming#

Cloud technology isn't only the future of gaming it's also the future of hybridized multi-clouds and edge architecture as a contemporary internet infrastructure for businesses. However, this cutting-edge technology faces a few obstacles. Lag, also known as latency, is a delay caused by the time required for a packet of data to move from one place in a network to another. It's the misery of every online gamer's existence. Streaming video sputters, freezes, and fragments due to high latency networks (Soliman et al., 2013). While this might be frustrating when it comes to video material, it can be catastrophic when it comes to cloud gaming services.

Developers are Ready for the Change#

Gaming is sweeping the media landscape. Please have a look around if you are unaware of this information. Although cloud gameplay is still in its infancy, it serves as proof that processing can be done outside of the device. I hope that cloud gaming is treated as the proving point that it is. Because cloud gameplay always has physical issues, we should look to edge gaming to deliver an experience where gamers can participate in a real-time multiplayer setting.

References#

• https://www.investopedia.com/articles/investing/053115/how-video-game-industry-changing.asp
• Beattie, A. (2020). How the Video Game Industry Is Changing. [online] Investopedia. Available at:
• Cai, W., Shea, R., Huang, C.-Y., Chen, K.-T., Liu, J., Leung, V.C.M. and Hsu, C.-H. (2016). The Future of Cloud Gaming . Proceedings of the IEEE, 104(4), pp.687-691.
• Choy, S., Wong, B., Simon, G. and Rosenberg, C. (2014). A hybrid edge-cloud architecture for reducing on-demand gaming latency. Multimedia Systems, 20(5), pp.503-519.
• Galehantomo P.S, G. (2015). Platform Comparison Between Games Console, Mobile Games And PC Games. SISFORMA, 2(1), p.23.
• Soliman, O., Rezgui, A., Soliman, H. and Manea, N. (2013). Mobile Cloud Gaming: Issues and Challenges. Mobile Web Information Systems, pp.121-128.
• Scholz, T.M. (2019). eSports is Business Management in the World of Competitive Gaming. Cham Springer International Publishing.
• Wahab, A., Ahmad, N., Martini, M.G. and Schormans, J. (2021). Subjective Quality Assessment for Cloud Gaming. J, 4(3), pp.404-419.

Nife started off as an edge computing deployment platform but has moved away to multi-cloud- a hybrid cloud setup

Collated below is some news about Nife and the Platform

• Read about the story of Nife, how it all started and the future months https://yourstory.com/herstory/2021/10/woman-entrepreneur-cloud-edge-computing-nife-labs/amp
• Read about the story of edge computing with Nife and what is in store in the next few months. https://yourstory.com/2021/06/nifes-founder-share-businesses-must-take-note-edge-computing/amp
• Learnings from Pandemic and more - Antler startups talk about https://www.antler.co/blog/the-good-the-bad-and-the-unexpected-what-entrepreneurs
• Nife is a startup showcasing at the Antler Demo Dayhttps://kr-asia.com/these-are-the-14-startups-ready-for-antlers-southeast-asia-demo-day
• Know how Virtualization and AI Acceleration on cloud and we effectively used Edge in robotics https://link.springer.com/chapter/10.1007/978-981-16-2937-2_10
• 5G offers a unique opportunity for advertisers to serve contextual advertisements in ways never seen before. Read this article to know more about this topic to design your advertisement more efficiently https://wiprotechblogs.medium.com/contextual-ads-winning-in-a-5g-world-94dee05b871d

• Developing Pagemark for Edge Computing. The value of edge computing comes from the data and technologies that adapt to evolving needs.
• https://tecknexus.com/5g-network/developing-pagerank-for-edge-computing/
• https://yourstory.com/2021/06/nifes-founder-share-businesses-must-take-note-edge-computing/amp

• Finalists of Qualcomm Wommen Entrepreneur India Network (QWEIN) 2021 [Nife] Labs was one of the finalists out of the 12 Startups listed https://yourstory.com/2021/08/qualcomm-women-entrepreneur-india-finalists/amp
• The 5G smart Railway Hackathon Won by 'Nife Labs'Featured in Yourstory about Why Businesses Must Take Note of Edge Computing https://www.startupleadership.com/blog/rec1283/
• Quotes on Digital Transformation https://startupnewsxp.blogspot.com/2021/07/when-ecosystems-become-digital-there.html
• 5G Smart Railway Hackathon. This Hackathon program was part of the 5g Railway Lab in Barcelona and it was fully designed and facilitated by the WorldStratup Lab Unit
• Nife at NetApp Demo Day announcement https://yourstory.com/2021/09/netapp-excellerators-demo-day-unrestrained-startups-spirit/amp
• Nife joins the 8th Cohort of NetApp Excellarator - https://yourstory.com/2021/05/netapp-excellerator-cohort-8-8-startups-using-data-cloud/amp

Learn more about different use cases on edge computing- Nife Blogs

Are you familiar with the differences between edge computing and cloud computing? Is edge computing a type of branding for a cloud computing resource, or is it something new altogether? Let us find out!

The speed with which data is being added to the cloud is immense. This is because the growing number of devices in the cloud are centralized, so it must transact the information from where the cloud servers are, hence data needs to travel from one location to another so the speed of data travel is slow. If this transaction starts locally, then the data travels at a shorter distance, making it faster. Therefore, cloud suppliers have combined Internet of Things strategies and technology stacks with edge computing for the best usage and efficiency.

In the following article, we will understand the differences between cloud and edge computing. Let us see what this is and how this technology works.

EDGE COMPUTING#

Edge Computing is a varied approach to the cloud. It is the processing of real-time data close to the data source at the edge of any network. This means applications close to the data generated instead of processing all data in a centralized cloud or a data center. It increases efficiency and decreases cost. It brings the storage and power closer to the device where it is most needed. This distribution eliminates lag and saves a scope for various other operations.

It is a networking system, within which data servers and data processing are closer to the computing process so that the latency and bandwidth problems can be reduced.

Now that we know what the basics of edge computing are, let's dive in a little deeper for a better understanding of terms commonly associated with edge computing:

Latency#

Latency is the delay in contacting in real-time from a remotely located data center or cloud. If you are loading an image over the internet, the time to show up completely is called the latency time.

Bandwidth#

The frequency of the maximum amount of data sent over an Internet connection at a time is called Bandwidth. We refer to the speed of sent and received data over a network that is calculated in megabits per second or MBPS as bandwidth.

Leaving latency and bandwidth aside, we choose edge computing over cloud computing in hard-to-reach locations, where there is limited or no connectivity to a central unit or location. These remote locations need local computing, and edge computing provides the perfect solution for it.

Edge computing also benefits from specialized and altered device functions. While these devices are like personal computers, they are not regular computing devices and perform multiple functions benefiting the edge platform. These specialized computing devices are intelligent and respond to machines specifically.

Benefits of Edge Computing#

• Gathering data, analyzing, and processing is done locally on host devices on the edge of the network, which has the caliber to be completed within a fraction of a second.

• It brings analytical capabilities comparatively closer to the user devices and enhances the overall performance.

• Edge computing is a cheaper alternative to the cloud as data transfer is a lengthy and expensive process. It also decreases the risk involved in transferring sensitive user information.

• Increased use of edge computing methods has transformed the use of artificial intelligence in autonomous driving. Artificial Intelligence-powered and self-driving cars and other vehicles require massive data presets from their surroundings to function perfectly in time. If we use cloud computing in such a case, it would be a dangerous application because of the lag.

• The majority of OTT platforms and streaming service providers like Netflix, Amazon Prime, Hulu, and Disney+ to name a few, create a heavy load on cloud network infrastructure. When popular content is cached closer to the end-users in storage facilities for easier and quicker access. These companies make use of the nearby storage units close to the end-user to deliver and stream content with no lag if one has a stable network connection.

The process of edge computing varies from cloud computing as the latter takes considerably more time. Sometimes it takes up to a couple of seconds to channel the information to the data centers, ultimately resulting in delays in crucial decision-making. The signal latency can translate to huge losses for any organization. So, organizations prefer edge computing to cloud computing which eliminates the latency issue and results in the tasks being completed in fractions of a second.

CLOUD COMPUTING#

A cloud is an information technology environment that abstracts, pools, and shares its resources across a network of devices. Cloud computing revolves around centralized servers stored in data centers in large numbers to fulfill the ever-increasing demand for cloud storage. Once user data is created on an end device, its data travels to the centralized server for further processing. It becomes tiresome for processes that require intensive computations repeatedly, as higher latency hinders the experience.

Benefits of Cloud Computing#

• Cloud computing gives companies the option to start with small clouds and increase in size rapidly and efficiently as needed.

• The more cloud-based resources a company has, the more reliable its data backup becomes, as the cloud infrastructure can be replicated in case of any mishap.

• There is little to no service cost involved with cloud computing as the service providers conduct system maintenance on their own from time to time.

• Cloud enables companies to help cut expenses in operational activities and enables mobile accessibility and user engagement framework to a higher degree.

• Many mainstream technology companies have benefited from cloud computing as a resourceful platform. Slack, an American cloud-based software as a service, has hugely benefited from adopting cloud servers for its application of business-to-business and business-to-consumer commerce solutions.

• Another largely known technology giant, Microsoft has its subscription-based product line ‘Microsoft 365' which is centrally based on cloud servers that provide easy access to its office suite.

• Dropbox, infrastructure as a service provider, provides a service- cloud-based storage and sharing system that runs solely on cloud-based servers, combined with an online-only application.

KEY DIFFERENCES#

• The main difference between edge computing and cloud computing is in data processing within the case of cloud computing, data travel is long, which causes data processing to be slower but in contrast edge computing reduces the time difference in the data processing. It's essential to have a thorough understanding of the working of cloud and edge computing.

• Edge computing is based on processing sensitive information and data, while cloud computing processes data that is not time constrained and uses a lesser storage value. To carry out this type of hybrid solution that involves both edge and cloud computing, identifying one's needs and comparing them against monetary values must be the first step in assessing what works best for you. These computing methods vary completely and comprise technological advances unique to each type and cannot replace each other.

• The centralized locations for edge computing need local storage, like a mini data center. Whereas, in the case of cloud computing, the data can be stored in one location. Even when used as part of manufacturing, processing, or shipping operations, it is hard to co-exist without IoT. This is because everyday physical objects that collect and transfer data or dictate actions like controlling switches, locks, motors, or robots are the sources and destinations that edge devices process and activate without depending upon a centralized cloud.

With the Internet of Things gaining popularity and pace, more processing power and data resources are being generated on computer networks. Such data generated by IoT platforms is transferred to the network server, which is set up in a centralized location.

The big data applications that benefit from aggregating data from everywhere and running it through analytics and machine learning to prove to be economically efficient, and hyper-scale data centers will stay in the cloud. We chose edge computing over cloud computing in hard-to-reach locations, where there is limited connectivity to a cloud-based centralized location setup.

CONCLUSION#

The edge computing and cloud computing issue does not conclude that deducing one is better than the other. Edge computing fills the gaps and provides solutions that cloud computing does not have the technological advancements to conduct. When there is a need to retrieve chunks of data and resource-consuming applications need a real-time and effective solution, edge computing offers greater flexibility and brings the data closer to the end user. This enables the creation of a faster, more reliable, and much more efficient computing solution.

Therefore, both edge computing and cloud computing complement each other in providing an effective response system that is foolproof and has no disruptions. Both computing methods work efficiently and in certain applications, edge computing fills and fixes the shortcomings of cloud computing with high latency, fast performance, data privacy, and geographical flexibility of operations.

Functions that are best managed by computing between the end-user devices and local networks are managed by the edge, while the data applications benefit from outsourcing data from everywhere and processing it through AI and ML algorithms. The system architects who have learned to use all these options together have the best advantage of the overall system of edge computing and cloud computing.

Learn more about different use cases on edge computing-

Condition-based monitoring - An Asset to equipment manufacturers (nife.io)

Large-scale manufacturing units, especially industrial setups, have complicated equipment. Condition-based monitoring at the edge is unprecedented. Can this cost be reduced?

Learn More!

Background#

The world is leaning toward the Industrial 4.0 transformation, and so are the manufacturers. The manufacturers are moving towards providing services rather than selling one-off products. Edge computing in manufacturing is used to collect data, manage the data, and run the analytics. It becomes essential to monitor assets, check for any faults, and predict any issues with the devices. Real-time data analysis of assets detects faults so we can carry out maintenance before the failure of the system occurs. We can recognize all the faulty problems with the equipment. Hence, we need condition-based monitoring.

Why Edge Computing for Condition-Based Monitoring?#

Edge computing is used to collect data and then label it, further manage the data, and run the system's analytics. Then, we can send alerts to the end enterprise customer and the OEM to notify them when maintenance service is required. Using network edge helps eliminate the pain of collecting data from many disparate systems or machines.

The device located close to the plants or at the edge of the network provides condition-based monitoring, preempts early detection, and correction of designs, ensuring greater productivity for the plant.

Key Challenges and Drivers of Condition-Based Monitoring at Edge#

• Device Compatibility
• Flexibility in Service
• Light Device Support
• Extractive Industries

Solution#

To detect machinery failures, the equipment has a layer of sensors. These sensors pick up the information from the devices and pass it to a central processing unit.

Here, edge computing plays a crucial part in collecting and monitoring via sensors. The data from the sensors help the OEM and the system administrators monitor the exact device conditions, reducing the load on the end device itself. This way, administrators can monitor multiple sensors together. With the generation of the events, failure on one device can be collated with another device.

Edge also allows processing regardless of where the end device is located or if the asset moves. The same application can be extended to other locations. Alternatively, using edge helps remove the pain of collecting data from many disparate systems/machines in terms of battery.

The edge computing system based on conditions is used to collect statistics, manage the data, and run the analytics without any software hindrance. A system administrator can relax as real-time data analysis detects faults to carry out maintenance before any failure occurs.

Condition-based monitoring can be used in engineering and construction to monitor the equipment. Administrators can use edge computing industrial manufacturing for alerts and analytics.

On-Prem vs. Network Edge#

Given that the on-prem edge is lightweight, it's easy to place anywhere on the location. On the other hand, installing a device is overridden if the manufacturing unit decides to go with the network edge; hence, flexibility is automatically achieved.

How Does Nife Help with Condition-Based Monitoring at Edge?#

Use Nife as a network edge device to compute and deploy applications close to the industries.

Nife works on collecting sensor information, collating it, and providing immediate response time.

Benefits and Results#

• No difference in application performance (70% improvement from Cloud)
• Reduce the overall price of the Robots (40% Cost Reduction)
• Manage and monitor all applications in a single pane of glass
• Seamlessly deploy and manage navigation functionality (5 min to deploy, 3 min to scale)

Edge computing is an asset to different industries, especially device manufacturers, helping them reduce costs, improve productivity, and ensure that administrators can predict device failures.

You might like to read through this interesting topic of Edge Gaming!