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.

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In today's fast-paced tech world, cloud computing has become an integral part of the business landscape. Proper management and utilisation of cloud resources have never been so important. This is where cloud management platforms come into the picture to oversee your cloud deployments. So what are cloud management platforms?

Imagine you have multiple cloud platforms like Google Cloud Platform, Microsoft Azure, and AWS for managing your cloud resources. It would become challenging to handle each platform with its interface and APIs. This is where cloud management platforms come into the picture. Cl

These platforms provide businesses with a unified control centre for managing cloud resources.

These platforms allow businesses to optimize cloud usage, enhance performance, and ensure security and compliance. The question is, how can businesses choose a cloud management platform that meets all their needs? This is where Gartner and its magic quadrant come into play. Garnet Magic quadrant provides businesses with valuable insights on different cloud management platforms so they can make informed decisions.

In this article, we will explore the methodology behind Gartner's Magic Quadrant, the significance it holds in the market, and the crucial role cloud management platforms play in the ever-evolving technology landscape. Additionally, we examine the implications of the newly public Magic Quadrants and their impact on both vendors and buyers in the cloud management platform market. We will also explore Nife Labs and how it can help developers manage scale and deploy applications on the cloud.

Overview of Gartner's Magic Quadrant for Cloud Management Platforms#

Gartner is a research and advisory firm that publishes reports on technology to help businesses make informed decisions. Magic Quadrant is one of the most popular and useful tools by Gartner. Gartner's analysts conduct extensive research on cloud platforms to identify key players. They gather information from vendor briefings, customer feedback, and product demonstrations. Gartner evaluates a platform based on many factors including scalability, ease of use, features, security, performance, market presence, and integration with other services. Gartner also takes into account other important metrics like pricing models, customer satisfaction, and vendor support.

After evaluation, cloud management platform vendors are divided into 4 categories based on their execution and completeness of vision. These categories are leaders, challengers, visionaries, and niche players. Being positioned as a leader in Gartner Magic Quadrant is like receiving an award. It signifies that the vendor has a clear vision and ability to execute it. Magic Quadrant guides businesses in their quest of finding a suitable cloud management platform for their business.

Current Landscape and Market Trends#

The CMP market is growing as more and more organizations are leveraging multiple cloud platforms for the benefit of different services. According to a report by Valuates, the global market of cloud management platforms is expected to reach USD 23,896.08 Million by 2028.

The CMP market is evolving rapidly with the emergence of new technologies and trends that enhance the capabilities and performance of CMPs. The technologies and trends include artificial intelligence(AI), machine learning (ML), Edge Computing, automation, and containerization. All these latest technologies and trends help vendors improve their performance and increase customer satisfaction.

Analysis of the Newly Public Magic Quadrants#

Magic Quadrant publishes more than 100 reports every year on different technologies, evaluating hundreds of vendors. Most of these reports are only available for premium members but some are made public for free. These reports give valuable insights into technology providers in a specific market.

In this section, we will analyze the newly public magic quadrant report on cloud management platforms. We will discuss the changes and updates in the new public report. We will also discuss the implication for businesses and vendors in the market.

Changes and Updates in the Magic Quadrant#

The newly public magic quadrant report on cloud management platforms is the 3rd edition in the series. Several important changes have been made in this new report. These changes reflect changing market needs. One of the important changes in this new report is the change of evaluation criteria for cloud management platforms. Gartner has increased emphasis on multi-cloud support, automation, and governance capabilities. Gartner's revised evaluation criteria reflect the sentiment of the market. Organizations need CMPs that provide consistent management across different platforms and provide automation and governance capabilities to reduce complexity and risk.

Another important change in the report is the inclusion of emerging technologies and trends. Gartner has included important technologies like artificial intelligence (AI) and machine learning (ML). These technologies improve the functionality of cloud management platforms by providing features like bug detection, root cause analysis, and analytics.

Key findings and insights from the latest Magic Quadrant#

The newly public Magic Quadrant report on CMPs features 11 vendors. This report gives valuable insight into the market. VMware, IBM, Microsoft, and BMC Software are named Leaders. These vendors have strong vision and execution capabilities. These vendors have multi-cloud integration, automation, and governance capabilities. These vendors have a large market share and high customer satisfaction. These vendors have the ability to influence the direction and standards of the market.

Cisco and Flexera are named challengers. These vendors have strong execution capabilities but lack vision. They provide limited CMP solutions that focus on specific sections of the market. Their market share and customer base are moderate. These vendors are reliable for standard multi-cloud scenarios. These solutions can compete with Leaders by working on their vision.

Morpheus Data, Scalr, and Embotics are named Visionaries. These vendors have strong vision and innovation capabilities but lack execution capabilities. They provide unique CMP solutions that address emerging needs. These vendors have a small market share but high customer satisfaction. These platforms are suitable for complex multi-cloud scenarios. The vendors can become leaders by improving their execution and increasing their market presence.

CloudBolt Software and HyperGrid are named Niche players. These vendors provide CMP solutions for specific niche needs. These vendors have a small market share and moderate customer satisfaction. These platforms are suitable for niche multi-cloud scenarios. These vendors can improve their market position by expanding their functionality.

Implications for Vendors and Buyers#

The changes and updates in the latest version of the Magic Quadrant for CMPs have implications for both vendors and buyers.

Due to the inclusion of emerging technologies and trends, there have been some shifts in the positioning of various vendors in the magic quadrant. Some vendors have completely dropped out from the magic quadrant while others have improved their positioning. Microsoft Azure, for instance, has improved its position from challenger to leader in the quadrant while Embotics has slipped from leader quadrant to visionary over the years due to a lack of adaptability. Microsoft has a clear vision and has the ability to deliver on its vision. Moreover, it supports multi-cloud and has automation and governance capabilities. These changes in vendor positioning indicate the importance of adapting to changing market needs.

The latest Magic Quadrant report identifies Leaders, Challengers, Visionaries, and Niche Players in the cloud management platform market. Leaders demonstrate strong execution and a comprehensive vision, offering robust multi-cloud management capabilities. Challengers and Visionaries excel in either execution or vision, while Niche Players provide specialized solutions for specific use cases. These findings help organizations understand vendor positions, strengths, and market trends, aiding them in selecting the right cloud management platform for their needs.

Introducing Nife Labs: A Cloud Computing Platform#

Nife Labs is a global edge application platform that empowers enterprises and developers to rapidly launch their applications on any infrastructure. It is a cloud computing platform designed to facilitate faster deployment, effective scaling, and ease of management. Here are some key features of the platform.

Rapid Application Deployment:

Nife Labs simplifies the process of deploying applications by providing a streamlined interface. Enterprises and developers can quickly launch their applications on any infrastructure, regardless of the underlying cloud platform.

Effective Scaling:

With Nife Labs, businesses can seamlessly scale their applications based on demand. The platform supports efficient scaling across multiple regions, taking into consideration factors such as network routing and quick application instantiation. This ensures optimal performance and availability, even in geographically distributed environments.

Ease of Management:

Nife Labs offers user-friendly management capabilities, making it easier for enterprises to oversee and control their cloud applications. The platform provides tools for monitoring application performance, generating reports, and setting up alerts. This enables organizations to proactively identify issues, optimize performance, and ensure smooth operations.

Business Advantages of Nife Labs:#

Faster Deployment and Time-to-Market:

Nife Labs enables rapid deployment of applications, allowing businesses to bring their products and services to market more quickly. By automating key tasks and providing a simplified deployment process, Nife Labs reduces the time and effort required for application deployment, giving enterprises a competitive edge.

Cost Optimization:

Nife Labs offers a cost-effective solution for application deployment and management. By leveraging the platform's capabilities, businesses can avoid excessive infrastructure costs and reduce the need for extensive manual intervention. This results in cost savings and improved resource allocation.

Cloud Management Platform for Nife:#

While Nife Labs is not a cloud management platform itself, it can be effectively managed through a cloud management platform. By integrating Nife Labs with a cloud management platform, enterprises can benefit from centralized management, resource allocation, and control over their cloud computing infrastructure. This integration allows businesses to leverage the advanced capabilities of Nife Labs while benefiting from the comprehensive management features provided by a cloud management platform.

Try Nife Labs for seamless cloud application deployment and management.

Conclusion:#

In conclusion, Gartner's Magic Quadrant holds significant influence and guidance for both vendors and buyers in the cloud management platform market. It provides valuable insights into the competitive landscape and helps organizations make informed decisions. As the market evolves, the newly public Magic Quadrants bring updated criteria and considerations, reflecting emerging technologies and trends. Cloud management platforms play a crucial role in managing and optimizing cloud infrastructure, and Gartner's Magic Quadrant serves as a compass for navigating this ever-changing landscape. Future developments in the Magic Quadrant will continue to shape the industry and drive innovation.

Build Automation Software and Cloud Platform#

In recent years there has been a rise in startup culture. We are seeing startups with innovative products everywhere. A few years ago launching a startup was quite difficult and expensive. But cloud platforms have emerged as superheroes. These superheroes have immense powers that can make or break a startup's success.

Cloud computing provides a lot of benefits that can elevate your business to new heights. It provides scalability, flexibility, cost-effectiveness, and security. As a startup every penny counts and demand can be sometimes unpredictable. This is where the cloud platforms swoop in to save the day. Cloud platforms save startups from the upfront and maintenance costs of infrastructure.

The advantages of cloud computing for startups can not be denied. But there are certain guidelines every startup should follow when launching a product on the cloud. In this article, we will explore the top 10 guidelines for startups when launching a product on the cloud.

We will also highlight the role of Nife Labs, a powerful cloud computing platform, in facilitating a successful product launch. By following these guidelines and leveraging the capabilities of Nife Labs, organizations can set themselves up for a seamless and impactful product launch on the cloud.

Pre-launch Preparation#

The first step when launching a product on the cloud is to set a clear goal in mind. You need to identify and highlight the features of your products. Identify problems your product can solve. Once you have completely analyzed your product it is time to find out your target audience and their pain points. Based on your audience's pain points you can create effective strategies for your product.

Conduct Market Research#

Another important part of pre-launch preparation is to analyze your competitors. Analyzing them will help you find market gaps that you can fill with your product. Moreover, you can learn from their failures and mistakes. Analyze all the strengths and weaknesses of your competition's product. Researching different build automation software tools available in the market

Researching various cloud management platforms and their offerings. Evaluating the scalability, reliability, and security features of each platform. Evaluate different aspects like cost, and performance and seek feedback from other startups or industry professionals who have used the platforms. Select the most suitable cloud management platform that aligns with the startup's needs and requirements.

Establish A Budget#

As a startup, you have limited resources which you need to distribute wisely. Consider the costs associated with cloud infrastructure, development tools, marketing, and personnel. Create a well-defined budget to allocate resources.

Selecting the Right Cloud Platform#

To navigate through the waters of cloud technology, startups need a trustworthy companion. This is where Nife Labs stands out as a valuable choice. Nife Labs offers a comprehensive suite of cloud computing services and tools that can greatly facilitate the product launch process. Here's why Nife Labs is a useful platform:

Scalability: Nife Labs provides scalable infrastructure and resources, allowing businesses to easily accommodate varying levels of demand. This ensures that the product can handle increased user traffic and scale seamlessly as the user base grows.

Security: Security is a top priority, and Nife Labs offers robust security measures to protect sensitive data and infrastructure. With advanced security features such as encryption, access controls, and threat detection, Nife Labs helps mitigate risks and ensures the product is secure.

Cost-efficiency: Nife Labs offers cost-effective cloud solutions, enabling businesses to optimize their budget and resource allocation. With flexible pricing models and pay-as-you-go options, organizations can scale their usage and control costs effectively.

Integration and compatibility: Nife Labs integrates well with other cloud services, enabling seamless integration with existing systems and tools. This ensures a smooth transition and minimizes disruptions during the product launch process.

Nife Labs acts as a reliable foundation, empowering organizations to focus on their product development and user experience while ensuring a successful launch on the cloud. Supercharge your product launch on the cloud with Nife. Experience rapid deployment, effortless scaling, and simplified management.

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Build Automation Software#

Startups should build automation software to automate different tasks on the cloud. Automation is like having a team of invisible employees who work efficiently 24/7. Most startups are short-staffed and low-budget, automating routine tasks enables them to focus their time and energy on more important things.

Startups need to identify areas where they can get the most benefit out of automation. For example, automation can be used in CI/CD to automate the build, test, deployment cycles, and DevOps automation. This will reduce the time from development to delivery. Automating infrastructure provisioning allows for faster response time to market.

DevOps automation also plays an important role in launching products on the cloud. It increases collaboration between development and operation teams breaking traditional silos and fostering a relationship of collaboration. DevOps automation enables faster and more frequent releases and empowers businesses to monitor and optimize their product's performance.

Ensuring Log Monitoring and Analysis#

Log monitoring is an important aspect to consider when launching a product on the cloud. It involves collecting information from various components of the product which include application, server, database, and storage. Log information provides valuable insight into the performance, behavior, and security of the product. Log monitoring helps identify and mitigate real-time issues in the product.

Nife Labs offers powerful log monitoring and analysis capabilities to ensure optimal product performance. With Nife Labs, businesses can set up centralized logging and real-time monitoring, gaining insights into system behavior. Startups should utilize the log monitoring capabilities of platforms like Nife to streamline their workflow.

Implementing **DevOps Automation**#

DevOps automation is a game-changer for startups looking to launch their product on the cloud. Combining development and operations teams streamlines the software delivery process and boosts productivity. Through continuous integration and deployment, DevOps automation enables startups to rapidly iterate and release their product, gaining a competitive advantage. It provides scalability and flexibility, allowing startups to dynamically adjust their infrastructure based on user demands.

With automated infrastructure provisioning and configuration management, startups can ensure stability and reliability, minimizing the risk of errors. DevOps automation empowers startups to achieve faster time-to-market, improved efficiency, and enhanced overall quality in their cloud product launches.

Security and Compliance Considerations#

When launching a product on the cloud, it is crucial to prioritize security from the outset. Incorporating security measures into the product architecture helps safeguard data, protect against threats, and maintain the trust of users. Startups should consider the following security measures:

Secure authentication and authorization#

Startups should implement authentication and authorization mechanisms. They can use multi-factor authentication, strong passwords, and access control to safeguard their product.

Utilize Log Monitoring Software#

Utilize log monitoring software for streamlined system management. Visualize and search logs for actionable insights. Ensure compliance with auditing capabilities and generate detailed reports. Enhance security and mitigate risks during product launch on the cloud.

Encryption#

Encryption provides an extra layer of security. It makes your data unreadable to unauthorized people without the encryption key. Startups should leverage encryption to secure their data at rest and in transit. Startups should also encrypt their communication channels.

Secure coding practices#

Follow secure coding practices to mitigate common vulnerabilities like cross-site scripting (XSS), SQL injection, and cross-site request forgery (CSRF). Conduct security tests and code reviews regularly to identify and fix any security flaws.

Explore Secure Cloud Management Platforms#

Explore cloud management platforms with built-in security features for efficient system management. Ensure data security at rest and in transit. Implement measures for compliance with industry regulations. Leverage advanced security capabilities such as encryption and access controls.

Secure APIs#

If your product exposes APIs, ensure they are designed with security in mind. Implement authentication and authorization mechanisms, input validation, and rate limiting, and consider using API gateways or security frameworks for additional protection.

Performance Testing and Optimization#

Performance testing and optimization is another important step for startups to ensure products launched on the cloud meet customer expectations. Performance testing involves the measurement of various metrics under different conditions to ensure the responsiveness, stability, and scalability of the product. Here are key steps startups can follow:

Identify Performance Objective: Identify performance goals you want your product to achieve such as response time and resource utilization. This will help you understand what you want from your product.

Utilize Log Monitoring Software: Incorporate log monitoring software for real-time performance insights. Monitor system and application logs to identify performance bottlenecks, errors, or anomalies. Analyze log data to optimize resource utilization and enhance system performance.

Create realistic test scenarios: Create real-world test scenarios to get accurate performance results. Test your product under different situations, and consider factors like concurrency, data volume, and transaction rates to create realistic workload profiles.

Explore Cloud Management Platforms:Explore cloud management platforms with performance optimization features. Leverage tools for auto-scaling, load balancing, and resource optimization. Ensure high availability and scalability for the product launch.

Once you have identified underlying performance problems with your product. Take necessary actions to solve those problems. Make sure your product is responsive and scalable.

User Experience and Feedback#

User experience goes a long way in the success of a product launch on the cloud. Startups should prioritize user experience by conducting user research, simplifying product design, and ensuring consistency. Startups should introduce updates more often to cope with changing customer needs.

Nife Labs plays a significant role in prioritizing user experience and gathering valuable feedback for product improvement. Through Nife Labs, businesses can implement user-centric updates and enhancements based on real-time feedback.

By prioritizing user experience and actively seeking and incorporating user feedback, organizations can create products that truly meet the needs of their target audience and drive user engagement and loyalty.

Post-launch Evaluation and Iteration#

To make a product launch successful on the cloud, startups need to analyze real-time performance and user adoption of their product. This will help them evaluate the effectiveness of their launch strategy. Startups can identify areas where they need improvements by comparing the real-time metrics of a product with anticipated metrics.

Startups need to develop a plan for ongoing maintenance, updates, and support. This includes bug fixes, security patches, feature enhancements, and addressing user feedback to ensure the product remains relevant and competitive in the long term.

Utilize log monitoring software for post-launch analysis. Analyze logs to gather valuable insights into user feedback and system performance. Identify areas for improvement based on data-driven decisions. Continuously enhance the product to ensure customer satisfaction and success in the cloud.

Startups can leverage build automation software for efficient product updates and enhancements. Startups can automate the deployment of code changes and new features, reducing manual effort and minimizing errors. Startups can also streamline the iteration and optimization process based on user feedback and metrics.

By continuously evaluating and iterating the product post-launch, organizations can adapt to user needs, address any issues or shortcomings, and ensure the product's continued success in the market.

Conclusion:#

In conclusion, launching a product on the cloud requires careful planning and execution. By following the guidelines outlined in this article and leveraging the capabilities of Nife Labs, businesses can maximize their chances of success.

From implementing automation to ensuring security, and prioritizing user experience, Nife Labs offers valuable features that streamline the product launch process. By embracing these guidelines and utilizing the Nife cloud computing platform, organizations can achieve a successful and efficient product launch on the cloud.

A cloud disaster recovery plan is vital for Startups and SMEs, as it safeguards critical data, minimizing the risk of permanent loss during unexpected events or system failures.

In today's digital age, companies of all sizes depend on technology for everyday operations. The introduction of cloud computing has completely altered how companies manage their data. The flexibility and cheap fixed costs of cloud computing make it particularly attractive for startups and SMEs. However, the danger of data loss and downtime due to system failures, cyber-attacks, or unforeseen events has grown, along with the rising dependency on technology. Here's when your disaster recovery and business continuity strategies come in handy.

What is Cloud Computing and why a Cloud Disaster Recovery Plan is required?#

Let us first have a recap of what Cloud Computing means...

"Cloud computing" refers to delivering data center resources such as servers, storage, databases, software, analytics, and intelligence to users remotely through the internet.

It allows companies to get these services on demand without buying expensive servers and other software. Infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) are just some of the services from cloud computing companies.

Many businesses implement disaster recovery in cloud computing to ensure the safety of data in any incident.

Let us now have a detailed look at the benefits provided by cloud computing and how startups and SMEs can leverage it.

Benefits of Cloud Computing for Startups and SMEs#

The use of cloud computing has several advantages for small and medium-sized businesses. Also, business continuity and disaster recovery in cloud computing are necessary which we will discuss further.

• Cost-effectiveness:

  The use of cloud computing has helped small and medium-sized businesses (SMBs) by removing the financial burden of purchasing and installing costly hardware and software infrastructure.

• Scalability:

  Small and medium-sized businesses (SMEs) may easily modify or expand their operations as needed.

• Accessibility:

  Cloud computing allows organizations to access their data and apps from any location with an internet connection.

• Data Security:

  Cloud service providers secure their customers' data from hackers and other online threats using advanced security protocols, including encryption and firewalls.

What is Business Continuity Planning?#

Business continuity planning is a process that includes finding possible threats to a business's operations and making a plan that minimizes the effect of these threats on the business. This process usually involves figuring out the most important business functions, coming up with plans to make sure these functions can keep going even if there is a breakdown, and trying these plans to ensure they work.

A solid cloud disaster recovery plan is essential for company continuity and minimizing downtime during unexpected interruptions.

Why Startups and SMEs Need Business Continuity#

Compared to bigger companies, startups, and SMEs often need more resources and infrastructure to deal effectively with disruptions. These companies may take a major impact in the form of financial loss, damaged image, and even bankruptcy if they experience a single downfall. Some examples of why small and medium-sized businesses (SMEs) require business continuity:

1. To Ensure Business Survival
2. To Mitigate Risks
3. To Protect Reputations

Disaster Recovery Plan#

Disaster recovery in cloud computing is an essential component of business continuity planning. A business's disaster recovery plan is an in-depth plan outlining the steps that must be taken in the case of catastrophic events to restore the company's essential IT infrastructure, software, and data.

Whether natural (such as floods, hurricanes, and earthquakes) or man-made (such as cyber-attacks and system failures), incidents may strike at any moment and for various reasons. Organizations need to have a disaster recovery in cloud computing to guarantee that they can swiftly and easily restore their mission-critical information technology (IT) infrastructure and data in the event of a catastrophe, therefore mitigating the damage to their operations, reputation, and bottom line.

A disaster recovery plan typically includes the following components:

1. Risk Assessment:#

A comprehensive evaluation of the potential hazards that may lead to interruptions in the organization's IT infrastructure and information.

2. Recovery Time Objective (RTO):#

Determining the duration the organization can tolerate the unavailability of its essential IT systems and information.

3. Recovery Point Objective (RPO):#

A well-defined establishment of the timeframe within which the organization must restore its data, ensuring that the information is as current as feasible.

4. Backup Strategy:#

A comprehensive strategy for routinely backing up essential IT systems, applications, and data, guaranteeing a swift and efficient recovery of the information in case of a catastrophe.

5. Recovery Strategy:#

A comprehensive plan describes the measures and protocols the organization must adhere to recover its essential IT systems and information in the event of a calamity.

6. Communication Plan:#

A strategy for effectively communicating with stakeholders, including employees and customers, during and after a catastrophe.

7. Testing and Maintenance:#

A strategy for periodically testing and maintaining the disaster recovery plan to ensure that it is current and efficient.

8. DRaas:#

Disaster recovery as a service (DRaaS) is essential for business as it provides a flexible and cost-effective solution to the business. Disaster recovery as a service enables automated backup, replication, and recovery of essential systems and data to ensure business continuity.

Benefits of a Cloud Disaster Recovery Plan#

As expected, a cloud disaster recovery plan lays out potential outcomes to minimize interruptions in service and quickly restart normal operations following an unfortunate event. Data loss prevention and adequate IT recovery should be prioritized as part of its design because of their critical role in the business continuity strategy.

The most obvious advantage of having a cloud disaster recovery plan is that it ensures the firm's operations will continue regardless of the conditions.

• Cost-efficiency

  Disaster recovery in cloud computing includes several components that can enhance cost-effectivenesses, such as prevention, detection, and correction. Organizations can reduce the risks associated with artificial disasters by implementing preventative measures. Detection measures enable rapid identification of issues when they occur, while corrective measures facilitate the restoration of lost data and a prompt resumption of operations.

  Regular maintenance of IT systems and comprehensive analysis of potential threats are essential to achieve cost-efficiency objectives. Innovative cybersecurity solutions should also be implemented. Ensuring that software is up-to-date and systems are optimally maintained saves time and reduces costs.

  In addition, incorporating cloud-based data management into a disaster recovery plan can further decrease the costs of backups and maintenance.

• Increased productivity

  To enhance the effectiveness and productivity of your team in disaster recovery planning, it is crucial to assign specific roles and responsibilities and establish accountability. This approach also guarantees redundancy in personnel for critical tasks, which improves productivity in case of sick days and minimizes turnover costs.

• Improved customer retention

  In the competitive market, customers have high expectations and are less likely to forgive an organization for failures or downtime, particularly if it results in losing sensitive data. Planning Business continuity and disaster recovery in cloud computing is crucial to meet and maintain a high standard of service in all circumstances.

  By minimizing the risks of data loss and downtime for your customers, you can ensure that they receive superior service during and after a disaster, strengthening their loyalty to your organization.

• Compliance

  Enterprises, financial markets, healthcare patients, and government entities heavily depend on critical organizations' availability, uptime, and disaster recovery plans. Moreover, these organizations rely on disaster recovery plans to comply with industry regulations such as HIPAA and FINRA.

• Scalability

  Disaster recovery planning helps businesses to discover innovative solutions to minimize the expenses associated with archive maintenance, backups, and recovery. Implementing cloud-based data storage and related technologies simplifies and improves the process, providing additional flexibility and scalability. Moreover, the disaster recovery planning process helps reduce the risk of human error, eliminates unnecessary hardware, and streamlines the entire IT process.

  Also, business continuity and disaster recovery in cloud computing become an advantage of disaster recovery planning by optimizing the business operations and making them more resilient and profitable, even before any disaster occurs.

Conclusion#

The small business owners need business continuity and disaster recovery plans to secure their data from unforeseen circumstances. Companies may protect their essential data, reduce the damage caused by interruptions, and maintain business operations by using a cloud-based disaster recovery strategy. The cloud's scalability, cost-efficiency, and ease of use make it a great option for small and medium-sized enterprises (SMEs) wishing to implement disaster recovery plans.

A disaster recovery plan may ensure that companies can continue running even if a disaster disrupts their regular operations. Having a robust disaster recovery plan that includes risk assessment, backup, and recovery plans, and communication protocols, ensures a company can continue operating even in unforeseen circumstances. If you are a startup or SME, cloud disaster recovery plan solutions offer advantages such as cost-efficiency, enhanced security, increased productivity, improved customer retention, and regulatory compliance.

FAQs#

1. What is a disaster recovery plan, and why is it essential for businesses?

A disaster recovery plan outlines a business's approach to recovering IT infrastructure, applications, and data after an incident like a natural disaster or cyberattack. It is essential for minimizing downtime, protecting data, and ensuring business continuity.

2. How does cloud computing benefit startups and SMEs in disaster recovery?

Cloud computing offers cost-effective, scalable, and accessible solutions that enhance disaster recovery capabilities. It provides robust data security, regular backups, and quick recovery options, making it ideal for startups and SMEs with limited resources.

3. What are the key components of a disaster recovery plan?

Key components include risk assessment, recovery time and point objectives, backup strategy, recovery strategy, communication plan, testing and maintenance, and, if applicable, Disaster Recovery as a Service (DRaaS).

4. How can a cloud disaster recovery plan improve customer retention?

By ensuring minimal downtime and maintaining data security during a disaster, businesses can provide consistent and reliable services, thereby improving customer trust and retention.

5. Why is regular testing and maintenance important for a disaster recovery plan?

Regular testing and maintenance ensure the disaster recovery plan remains effective and up-to-date, addressing any new risks and ensuring all components function as intended during an actual disaster.

Discover more on how our innovative solutions can provide peace of mind and enhance your business continuity planning. Contact us today to learn more about our cloud disaster recovery plans tailored for startups and SMEs.

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.

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Efficient cloud storage pricing is crucial for businesses, enabling cost savings and scalability, and ensuring seamless data management in today's competitive digital landscape.

Cloud computing has become an essential technology for developers. It provides developers with all the necessary tools to build, test, and deploy applications with ease. With all these benefits it has one disadvantage. Cloud computing for developers can become quite expensive if the resources are not managed properly.

The cost of different cloud services including cloud storage pricing and other services can become a financial burden on organizations. That is why developers need to optimize cloud costs. In this article, we'll explore some tips and tricks to optimize cloud costs. Let's dive into the article.

Cloud Cost Optimisation and Cloud Computing for Developers#

Ways you can optimize your Cloud Costs#

(a) Understanding Cloud Costs#

As a cloud software engineer or a developer leveraging the cloud for cloud computing software development. You need to understand cloud pricing models to make informed decisions.

Cloud storage pricing is a very important part of cloud costs. Cloud providers offer different storage options with different pricing. You need to understand your needs and select one that suits you best.

Moreover, with the pricing model, you also need to compare the services of different cloud providers. For instance, let's take Google Cloud and iCloud as examples. Both are prominent names in the industry. Both have different pricing models and services designed for developers.

Google Cloud Pricing is flexible, it provides developers with a wide range of tools and scalability options. While iCloud pricing is designed for both individuals and businesses, it works seamlessly with Apple devices.

As a cloud software engineer or developer, it is your responsibility to find the balance between resource provisioning and cost efficiency. To achieve this balance follow the tips and tricks given in the proceeding sections.

(b) Monitor Resource Usage#

Monitoring resource usage is an essential practice for optimizing cloud costs. Continuous monitoring of cloud resources helps you identify the highs and lows of your resource consumption. You can identify overused and underused resources. If these resources are left unchecked you will be left with a huge bill.

Almost all cloud services provide their users with robust monitoring and analytic tools. You can utilize these tools to closely monitor resource usage. These tools provide real-time information about all the different aspects of the cloud like CPU usage, storage consumption, network traffic, etc. You can utilize this information to make informed decisions.

As a cloud software engineer or a developer, you can use this information to set a threshold for resource consumption and set up alarms, auto-scale to deal with traffic, and set event-driven functions. All of these practices will help you optimize your cloud cost.

(c) Set Up Alerts#

Setting up alerts is another important step in cloud computing for developers for optimizing cloud costs. It alerts you whenever there is a sudden increase in usage so you can investigate and take proactive measures. Alerts help you stay within your budget. Here are some useful practices for setting up alerts to optimize cloud costs.

• Always set a threshold based on your project budget.
• Choose a suitable medium for receiving alerts.
• Select alert triggers like CPU usage, storage consumption, or network traffic.

By following all these practices you can effectively optimize your cloud costs.

(d) Leverage Cost Calculators and Budgeting Tools#

In cloud computing software development cost calculators and budgeting tools are very powerful tools for optimizing cloud costs. These tools provide valuable information related to cloud expenditures. These tools enable you to estimate, track and control your cloud spending.

1. Cost Calculators#

Cost calculators are online tools in cloud computing for developers that help you estimate your cloud spending before deployment. You can make informed decisions about projects using these tools. You can identify projects exceeding your expected budget and take necessary actions to avoid overspending.

Benefits:#

• Cost calculators allow developers to compare pricing options of different services from different providers. For example, they can compare cloud storage pricing to choose the best.
• You can add and compare different configurations and services to choose the most cost-effective solution for your application.

2. Budgeting Tools#

Budgeting tools help you monitor the real-time expenses of your cloud resources. These tools are provided by your cloud providers. With the help of these tools, you can assign budgets to different projects and departments. You also get alerts from these tools whenever the cost of resources exceeds a certain threshold. You can utilize these tools to effectively optimize your cloud costs.

Introducing Nife: A Cost-Effective Cloud Platform#

In recent years developers have faced many problems regarding cloud computing, cost optimization being one of them. While there are many tips and tricks to optimize cloud costs, you need a cloud computing platform that can do it all.

Nife is a cloud computing platform that provides developers with all the necessary tools for cost optimization while maintaining the reliability and high performance of cloud applications. Its pricing is flexible as compared to google cloud pricing or iCloud pricing.

Nife, the global edge application platform, offers developers a cost-effective solution for optimizing cloud expenses. Traditional infrastructure and practices often lead to complex deployments, excessive manpower requirements, and slow system configurations, resulting in higher costs.

However, Nife Labs simplifies cloud computing, 5G, and edge computing, making application deployment and scaling easier and more affordable.

With Nife, developers can deploy their applications rapidly on any infrastructure without worrying about the underlying infrastructure. The platform allows for easy application monitoring, generating reports and alerts based on specific needs. So why not give Nife a try and see how it optimizes cloud costs? and Visit Nife to leverage Cost Efficient Cloud Platform

Conclusion#

In conclusion, optimizing cloud costs is essential for developers working with cloud computing. By following the tips and tricks discussed in this article, developers can effectively monitor resource usage, set up alerts, and utilize cost calculators and budgeting tools.

However, there is a cloud platform that provides developers with all the means to optimize cloud costs, Nife, a cloud computing platform, provides a cost-effective solution for developers by simplifying cloud computing, reducing infrastructure costs, automating key tasks, and enabling rapid application deployment. Nife optimizes cloud expenses and delivers significant cost savings for businesses and enterprises.

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 solutions are becoming a very important part of our daily life. It has many valuable applications in various fields from facial recognition to self-driving vehicles and medical imaging. It has applications everywhere. It allows machines to analyze images and identify people and objects with great accuracy and precision.

No doubt the technology is very powerful, but its capabilities are being limited by traditional cloud infrastructure. This is where cloud edge computing steps in. Cloud edge computing has provided the necessary speed and infrastructure to utilize computer vision applications at their best.

The importance of Cloud edge computing in providing efficient deployment of computer vision applications can not be overstated. Cloud Edge infrastructure processes the data of users at the edge of the network, where it is being generated. It provides low latency and real-time processing power, making it ideal for various computer vision applications.

In this article, we will explore the challenges as well as strategies for efficiently deploying computer vision solutions with edge computing. Read the full article for complete insights.

Computer Vision and Edge Computing#

Before jumping into the topic let's explore cloud vision technology and edge computing in detail.

What is Computer Vision?#

Computer Vision is a field of AI (Artificial Intelligence) that enables machines to interpret and analyze visual data (images and videos) intelligently. It uses different algorithms, machine learning, and deep neural networks for that.

In the last few years, it has improved very much in capabilities. It has various applications in different fields. Some computer vision applications are facial recognition, object detection, and self-driving vehicles.

What is Edge Computing?#

Edge computing is a type of cloud computing that uses IoT devices to process data closer to the source of its generation. It provides many benefits including low latency, high bandwidth, high speed, reliability, and security. It reduces the dependence on a centralized cloud solution.

Relationship#

Computer vision applications need to process large amounts of data. Edge computing enables the processing of a large amount of visual data in real-time. Which allows machines to make informed decisions at a higher speed.

Their relationship can significantly improve different fields including manufacturing, retail, healthcare, and more.

Challenges in Deploying Computer Vision Solutions with Edge Computing#

The advantages of deploying computer vision solutions with edge computing can not be denied. But there are also some challenges and concerns that need to be addressed. These challenges include security and privacy concerns, power constraints, latency and bandwidth issues, and security.

Latency and Bandwidth Issues#

One of the important challenges in the deployment of computer vision solutions with edge computing is latency and bandwidth issues. Data is processed at the edge of the network, close to the source in edge computing. The processing capabilities of edge devices are limited and computer vision applications usually require a large amount of processing power.

This may increase the latency of the speed and affect the real-time decision-making capabilities. However, this problem can be resolved by selectively sending data to the cloud for low latency.

Security and Privacy Concerns#

Edge computing infrastructure involves the deployment of multiple connected devices. These devices are deployed in an unsafe environment and are always vulnerable to cyber attacks. Important data collected by these devices can be compromised. These security and privacy concerns can be addressed by using encryptions and access controls.

Power Constraints#

Edge devices usually have limited battery capacities. These batteries can dry up pretty quickly during the processing of vast amounts of data. In that case, it can create operational challenges. It is important to take necessary actions to avoid these types of problems.

Scalability#

Another big challenge in the deployment of computer vision applications is scalability. As processing requirements of computer vision applications are huge. To fulfill these processing requirements, a large number of edge devices are required. It can be difficult to manage these large numbers of devices which can eventually create scalability challenges.

Strategies for Efficient Deployment of Computer Vision Solutions with Edge Computing#

Efficient deployment of computer vision solutions with edge computing can be done by implementing some useful strategies. Here are some of the strategies that can be used to improve efficiency.

Edge Device Selection#

Choosing edge devices is a very important strategy in deploying computer vision solutions. Edge devices need to be selected based on capabilities such as processing power, battery, memory, connectivity, and reliability. Computer vision deployment requires the processing of vast amounts and latency for real-time decision-making. That is why it is crucial to select devices carefully.

Machine Learning Models and Algorithms#

Machine learning models and algorithms play a crucial role in the efficient deployment of computer vision solutions. Edge devices are not capable of processing these language models and algorithms. Therefore lightweight language models and algorithms can be used for speed and accuracy. These lightweight models deliver without compromising quality.

Cloud Edge Hybrid Solutions#

Another important strategy for the deployment of Computer Vision solutions with edge computing is the use of hybrid solutions. Computer vision applications require large storage and processing power. By implementing hybrid solutions these needs can be addressed efficiently. Organizations can use cloud resources for important data while day-to-day processing edge devices can be used. Hybrid infrastructure provides security, reliability, and speed.

Use Cases:#

Here are some of the applications of efficient deployment of computer vision solutions with edge computing.

Smart Cities and Traffic Management#

Computer vision combined with edge computing can be used in smart cities for surveillance and traffic management. Edge camera devices with censors utilizing computer vision algorithms can be used to control traffic flow. These devices can analyze real-time data and adjust traffic effectively by making informed decisions. In this way, accidents can be avoided and a proper traffic flow can be maintained.

Healthcare#

Another important application of computer vision and edge computing is healthcare. Edge devices enable remote diagnosis of patients. Edge devices with sensors allow patients to detect diabetes, heart diseases, and respiratory illnesses from their homes. These are some diseases that need regular checkups. Edge devices allow patients to transfer their medical history to their hospitals. Moreover, edge devices also allow patients to consult doctors from their homes using cameras and get their diagnosis.

Manufacturing#

Efficient deployment of computer vision solutions with edge computing can be used to improve the efficiency of manufacturing plants. Edge devices with computer vision technology can be used to monitor product lines, inventory, and manufacturing processes. Edge devices can be used to make real-time adjustments in the manufacturing process.

Agriculture#

Another important application of computer vision with edge computers is agriculture. Edge devices with computer vision technology can provide many benefits to farmers. These devices can automatically detect water levels in crops and give water whenever required. These devices are also capable of detecting pesticides and diseases in crops.

There are many more applications of edge computing and computer vision in agriculture fields. With proper deployment, these applications can provide many benefits to farmers.

Conclusion:#

Efficient deployment of computer vision solutions with edge computing can provide many benefits in different industries, from healthcare and automotive to manufacturing and agriculture.

Edge computing combined with computer vision allows room for efficiency, accuracy, scalability, and cost-effective solutions.

There are some challenges associated with the technology which can be addressed through proper planning. Overall the potential of edge computing and computer vision is limitless. With more innovations in the field, the applications are expected to grow.

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.

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.

In recent years cloud computing has become an important part of the financial industry. It has completely changed the way these financial organizations operate. Financial institutes are adopting cloud computing on a very large scale. According to a recent report, around 80% of global financial institutions have adopted hybrid cloud infrastructure.

Hybrid cloud technology in banking is being adopted worldwide because it helps organizations control scalability, flexibility, security, and cost. By adopting cloud infrastructure in finance, organizations benefit from both on-premise and cloud infrastructure.

In this article, we will cover the benefits of hybrid cloud infrastructure for the financial services sector. Read the full article for complete insights on the topic.

Hybrid Infrastructure for Financial Services#

Hybrid cloud infrastructure has become very popular among financial organizations. It has gained so much popularity among financial organizations because hybrid cloud computing in finance provides features of both public and private clouds.

The public cloud provides on-demand services like storage, tools, and processing for a large number of users. While private clouds provided resources to a single organization. The hybrid infrastructure allows organizations to achieve flexibility, scalability, and cost-effectiveness while also retaining reliability and security.

Advantages of Hybrid Infrastructure#

Here are the advantages of hybrid infrastructure for financial services that we have mentioned earlier.

Flexibility#

One of the major advantages of hybrid cloud computing in finance industry is its flexibility. It allows banks and financial services to quickly respond to changing customer needs and market trends. Financial institutes can scale up automatically when their service demand is at its peak and can quickly scale down after that period.

Hybrid infrastructure also allows organizations to release new services quickly. For example, banks can quickly roll out new applications by testing and deploying them on the cloud. This saves them time and money.

Scalability#

Another important benefit of hybrid cloud computing in finance is improved scalability. Hybrid Infrastructure allows financial services and banks to scale up and down anytime. Organizations can scale up their operations quickly when the workload is at its peak without having to install on-premise infrastructure.

In hybrid infrastructure, organizations only pay for what they use. They can avoid spending money on the maintenance of large on-premise IT infrastructure.

Cost Effective#

Another benefit of hybrid cloud computing in finance is cost-effectiveness. It allows organizations to automate repeated tasks like data entry, storage cleanup, and updates. This allows organizations to concentrate on important projects. It also provides insight into all the ongoing projects of different departments. This helps financial institutes suspend low-performing projects and save their resources.

A hybrid cloud provides financial institutions with the tools to predict market trends based on old data. This helps financial institutes maximize their profits and avoid risky investments.

Security#

Security is a major concern for every financial institute. Hybrid Cloud technology in banking allows organizations to store sensitive users' data on-premises. While the cloud can be utilized for less sensitive data. Furthermore, hybrid infrastructure also allows organizations to comply with regulatory requirements. As many regulatory bodies require users' data to be in certain regions.

This cloud infrastructure also provides security against cyber threats using firewalls, access controls, encryption, and authentication.

Benefits of Hybrid Infrastructure for Financial Services#

Here are some benefits of Hybrid infrastructure for financial services:

Enhances Security#

One of the important benefits of hybrid cloud technology in banking is enhanced security. It allows organizations to utilize the benefits of both public and private clouds. Financial organizations can keep sensitive user data on the premises. All the other data can be kept online.

A hybrid cloud provides high levels of security through encryptions, firewalls, access control, and authentication. Moreover, it allows banks and financial institutions to comply with the regulations of government bodies by keeping data on-premises.

Improved Customer Experience#

Another benefit of hybrid cloud technology in banking is enhanced customer experience. Financial organizations process a large number of transactions every day. Hybrid cloud computing allows these organizations to process transactions efficiently in real time.

Hybrid cloud infrastructure services in finance also allow these organizations to diversify their data across different cloud platforms. This helps organizations to continue their operations in case of any downtime. It is also very secure and reliable.

Increased Agility#

Hybrid cloud technology in banking provides more agility. It means financial institutions can respond to changing market trends and customers' needs quickly. It allows them to scale up and down quickly without having to upgrade their on-premise infrastructure.

The hybrid infrastructure allows organizations to release new services quickly. With cloud infrastructure organizations can develop, test, and deploy services more efficiently. This helps organizations cope with changing technology and customer needs.

Better Data Management#

The banking and financial services industry is a data-driven industry. A hybrid infrastructure allows financial organizations to manage their data effectively. It provides organizations with total control over their data. Organizations can manage their data by using both cloud and on-premise infrastructure. In this way, sensitive data can be kept on the premises while less sensitive on the cloud.

Cloud infrastructure services provide organizations with data analytics tools. These tools can be used to get actionable insights into customer behavior and operational data.

Case Study: JP Morgan Chase#

JP Morgan Chase is a global financial services organization that has adopted hybrid cloud infrastructure successfully. They have been able to improve their scalability, availability, cost-effectiveness, security, and reliability. They have also utilized cloud infrastructure services to improve operations and online banking services.

With a combination of public and private cloud JP Morgan Chase has improved its efficiency and customer experience while maintaining security and regulatory compliance.

Challenges faced by JP Morgan Chase#

Before the adoption of Hybrid Cloud Infrastructure, the organization relied on physical IT infrastructure. Due to their reliance on on-prem infrastructure the company faced challenges of scalability and downtime. These problems affected the company's operations and customer experience negatively.

Benefits Achieved#

After the adoption of hybrid cloud infrastructure JP Morgan Chase improved its performance significantly. They have improved their scalability and reliability. They have utilized the cloud to scale up during peak workload. Hybrid infrastructure also allowed JPMorgan Chase to improve their day-to-day operations and data management.

Cloud infrastructure services allowed them to get useful insights about their customers. They have been able to roll out online banking services and products to improve their customer experience.

Conclusion#

Cloud infrastructure services have revolutionized the banking industry. Companies avoiding cloud adoption are leaving behind. Hybrid cloud infrastructure has become popular among financial institutions due to the combined benefits of public and private clouds. It allows organizations to improve scalability, flexibility, security, cost-effectiveness, and reliability. Companies like JPMorgan Chase adopted hybrid cloud infrastructure and improved their performance significantly.

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.

Risk management is a crucial aspect of cloud-based banking systems to ensure the security and stability of these financial institutions. Cloud-based financial systems rely on cloud computing services and tools for day-to-day financial transactions and other operations. These cloud computing services, on one hand, provide benefits like scalability, cost-effectiveness, and flexibility. But, on the other hand, they also introduce some serious risks.

These risks need to be identified and managed for the proper functionality of banking operations. In this article, we will discuss the potential risks of a cloud-based banking system, the risk management process, and best practices for risk management in the cloud. Read the full article to get insights into risk management in cloud banking systems.

Types of Risks in Cloud Banking Systems#

There are different types of risks associated with banking systems, especially when a cloud-based system is involved. As financial institutions store sensitive data related to the financial and personal information of users, these risks need to be identified and necessary actions should be taken for financial institutions to have smooth operations. Here are the types of risks institutions may face in cloud-based banking systems.

Operational Risks#

Important types of risks in a cloud banking system are operational risks. Operational risks refer to problems that occur in the cloud due to internal system failures, human errors, or external cyber-attacks.

IT Failures#

Cloud-based banking systems are dependent on cloud services for their day-to-day operations. That is why a strong IT infrastructure is needed to support operations all the time. Strong IT infrastructure does not guarantee smooth operations. There is always room for risks like outages, low network latency, or any other technical problems. All of these IT failures result in huge financial losses and sometimes inefficient operations.

Cyber Attacks#

According to a survey, more than 2200 cyber-attacks happen every day. The majority of the targets of these attacks are financial institutions like banks. A cloud-based banking system makes the system and information available on it more vulnerable to cyberattacks. Even a failed cyber attack can disrupt the operations of a financial institution. Despite continuous system upgrades, there is always a risk of a potential cyberattack which can lead to financial losses, data breaches, and disrupted operations.

Human Errors#

Human error is an important factor in operational risk. Employees may cause operational risks by giving control to unauthorized personnel, incorrect data entry in the cloud, etc. All of these human errors can cause operational risk in a cloud-based banking system.

Compliance Risks#

Cloud-based banking systems can also pose compliance risks. All financial institutions are required to fulfill some regulations by different government bodies to ensure the privacy of customers and continuous operations. These regulations include General Data Protection Regulation (GDPR), Federal Risk and Authorization Management Program (FedRAMP), SEC, etc.

Cloud-based banking systems make it difficult for banks to comply with all these regulations by different bodies. This difficulty poses a compliance risk that can cost banks fines and restrictions. Continuous fines and restrictions from different government bodies and organizations cause financial loss and less trust among customers.

Reputation Risks#

Reputational risks refer to the harm to the reputation a bank may face due to data breaches, system failures, compliance issues, service disruptions, etc. All of these reputation risks are multiplied in cloud-based banking systems. Since the likelihood of cloud-based services being disrupted is higher than an on-premise infrastructure, it poses more reputation risks.

All of the above risks can be controlled by proper risk management systems and by implementing best risk management practices.

Risk Management Process in Cloud Banking Systems#

Risk management is an important process in cloud banking systems. It involves the identification of risks, evaluation of risks, implementation, and monitoring of risks to improve the security of data and transaction details of users.

This risk management process helps FinTech institutions like cloud-based banking systems to ensure the security and confidentiality of sensitive financial information of their users.

Following are the phases of the risk management process in a cloud-based banking system:

Identification of Risks#

The very first step in a risk management process is to identify the potential risks. Extensive research should be conducted to identify different types of risks in the cloud banking system. This includes thorough research of the cloud to identify types of tools and data stored. Once potential cloud risks have been identified, the next step is to calculate their impact.

Evaluation of Risk#

The next step after the identification of potential risks is risk assessment. This step includes the evaluation of all the potential risks identified in the previous step. Once all the potential risks have been evaluated, it's time to prioritize these risks based on their impact on the banks and customers. Risks largely affecting the security of financial institutions and their customers should be of high priority.

Implementation of Risk Mitigation Measures#

After prioritizing the risks based on their impact, it is time to tackle them one by one. These risks cannot be eradicated but can be minimized by implementing risk management techniques. This includes setting firewalls to increase protection from external threats, allowing only authorized personnel to access sensitive areas of the cloud, setting encryptions, having a disaster recovery plan, etc.

All of these risk management measures can ensure smooth operations in a cloud-based banking system.

Monitoring and Review#

This risk management process should always be in motion. This will help banks maintain smooth operations without any disruptions. This risk management should always be monitored and reviewed for effectiveness because technology is constantly evolving. It is important to evolve a risk management plan in accordance with changing technology to ensure security and smooth operations.

Best Practices for Risk Management in Cloud Banking Systems#

Best practices for risk management help ensure the security, flexibility, and availability of sensitive financial information required for operations in banks. These practices minimize the effects of adverse incidents on the cloud.

Strong Access Controls#

Strong access control should be practiced by every bank, whether it has on-premises infrastructure or is cloud-based. Strong access controls are critical to ensure that only authorized personnel access personal and financial information of banks and customers.

This can be ensured by implementing two-step authentication, access numbers, and codes. Also, access for employees who are fired or suspended from the bank should be revoked to prevent any data or identity theft incidents.

Regular Security Assessments#

Regular security assessments are also a good practice for cloud-based banking systems for risk management. These assessments help financial organizations identify and eliminate vulnerabilities in their system. This assessment includes testing technology, processes, and data for vulnerabilities. This security assessment is usually divided into four steps: identifying the risks, assessing each risk, prioritizing risks, and mitigation.

These regular security assessments help financial organizations safeguard the financial and personal information of customers by eliminating any threat before it does any harm.

Data Encryption#

Implementing strong security measures is a crucial part of risk management. Using encryption for data on the cloud and shared data is very important. It can help financial institutions prevent any significant loss and theft. Apart from encryption, a two-step authentication system should also be introduced to allow the use of the cloud by authorized personnel only.

Apart from encryption, firewalls are also important for the networks to prevent any network interception. Most of the time, data breaches happen due to weak network security measures, and firewalls will ensure network security.

Regular Software Updates and Patches#

Regular software updates and patches are an important aspect of risk management. Regular updates provide developers with the opportunity to eliminate vulnerabilities, fix bugs, and enhance the performance of the cloud. These updates and patches are vital for the security of a cloud-based system. These updates allow developers to make their systems up to date according to changing technology.

Compliance with Regulatory Requirements#

The financial service sector is regulated by different government bodies due to its sensitivity and importance. Sometimes it can be hard to comply with all the regulatory requirements. But by implementing practices like regular security audits, real-time data sharing between organizations, and choosing a reputable vendor, all these regulatory requirements can be fulfilled without any worries.

Therefore, financial service organizations should comply with the regulations to avoid fines and penalties and maintain their reputation in the market.

Disaster Recovery Plan#

Disaster recovery planning is also important for cloud-based banking systems to recover quickly from any disaster or disruption. This planning should include the processes to follow during a disaster, contact information, resources, backup plans, etc.

This disaster recovery plan will help banks recover quickly and ensure the continuation of their operations without any significant loss.

Conclusion#

Risk management is a crucial aspect of cloud-based banking systems to ensure smooth operations and protect sensitive information from various risks. Cloud-based systems have a lot of advantages but can also introduce new types of risks, including operational, compliance, and reputational risks. By identifying, evaluating, and mitigating these risks, financial institutions can manage their operations efficiently and securely.

Proper implementation of best practices for risk management helps banks maintain their operations without disruption. These best practices include strong access controls, regular security assessments, data encryption, regular software updates, compliance with regulatory requirements, and a well-documented disaster recovery plan. All of these practices ensure the security and smooth functioning of cloud-based banking systems.

Risk management in cloud-based banking systems is an ongoing process that requires constant monitoring and updating to adapt to evolving technology and potential risks. Adopting these practices will help ensure the safety, security, and effectiveness of financial operations in the cloud environment.

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.

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.

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.

Modern tech in customer support, assistance, and business is generating a lot of buzz. The majority of new technology will only assist customer-facing workers to accomplish their tasks more efficiently. Cloud computing technology, cloud-native application development, Edge Computing for Enterprises, multimedia, real-time messaging, chatbots, and artificial intelligence (AI), cryptocurrency, and even self-service, itself all have the potential to deliver a world-class customer experience.

How Cloud computing technology is Transforming Customer Experience?

Retail, healthcare, finance, and manufacturing are all industries that generate massive volumes of data daily. To truly exploit this data, you must first store and analyse it, something traditional data solutions are incapable of doing owing to their fragmented nature.

Cloud computing technologies are a means to many goals that each organisation must identify as part of a unified cloud strategy. There are several ways that Cloud computing technology may have a real-world influence across industries for companies aiming to change the customer experience. The banking, insurance, and healthcare industries all generate massive amounts of data, have regulatory compliance requirements, and have high client demand for services and goods [(Deb, Jain and Deb, 2018)]. They require strategies to provide, track, expand, and enhance such services while also meeting consumers' financial and healthcare demands.

Cloud computing technology is critical to reaching this aim since it provides:

Analytics and data processing#

Compliance with regulatory data protection requirements#

Detection of Fraud#

Elimination of mainframe technological debt through cloud-native app integration#

Loan processing and underwriting examination#

New banking and financial planning goods and services#

Inventory control#

What Edge Computing for Enterprises means for the Customer Experience?

Processing data at the source rather than a centralized or cloud-based server may appear to be a technical problem, but Edge computing for enterprises only benefits marketers. Marketers can participate in the following activities with data processing occurring closer to the source:

Real-time marketing:#

Because data is analyzed at the source, marketers may create automated systems that respond promptly to customer inputs by using Edge computing for enterprises

Offline experiences:#

Edge computing for enterprises isn't entirely dependent on a connection between an IoT device and a centralized server, actions can be carried out even when no internet connection is available [(Noghabi et al., 2020)].

Personalization and interactive experiences:#

Edge computing for enterprises will be able to react quickly to consumer involvement, resulting in a hyper-personalized experience defined and controlled by the end user.

Cloud-native Software Development for customer experience

To survive the upheaval, businesses need to have access to highly qualified workers, a strong infrastructure, and the flexibility to create high-quality apps. Organizations must embrace new technologies such as DevOps, Agile, microservices, containers, Agile, and platform-as-a-service to implement contemporary techniques such as provisioning, automated testing, and cloud-native application development to thrive in today's digital edge [(Kosińska and Zieliński, 2020)].

Today's businesses rely heavily on software to differentiate their service and product offerings. Businesses are shifting to design such apps for the best performance in the cloud to take advantage of the flexibility and speed of the cloud. As a result, an early user of cloud-native apps has enjoyed exceptional business velocity and growth. Cloud-native Software Development enables companies to fully realize the promise of cloud-native capabilities to achieve maximum speed, agility, and DevOps efficiency and fully embrace the true benefits of Cloud-native Software Development.

How can the latest technologies assist businesses in improving the customer experience?

Understanding customer behaviour is critical for any corporation seeking to become a market leader in today's volatile business environment. Customer experience management may be time-consuming and costly, and it generally necessitates uniformity across channels, such as closed-loop procedures, customer service centre encounters, SMS, website engagement, and so on [(Gellweiler, and Krishnamurthi, 2020)].

Companies are focused on automation and uncovering an organization's latent potential with the assistance of Cloud computing technology, Cloud-native Software Development, and Edge computing for enterprises in the following ways to further simplify these operations and have a direct influence on customers:

Effective business strategy optimization#

In today's fast-paced business world, tapping into uncharted territory might be one of the things that firms can use to ensure long-term success.

Data gathering and review generation#

Businesses must be agile and responsive in their procedures to adapt to today's fast-paced business climate.

Recommendations customized to you.#

With the use of AI and sophisticated data analytics in the business domain, predictive analytics tools may assist businesses in producing informed forecasts by providing wiser ideas and intelligent recommendations for future data-driven strategy creation [(Rekettye and Rekettye, 2019)].

Technology that brings customers closer together.#

AI is the market's next big thing and for all the right reasons. Or perhaps technology has already become an important part of our life without our recognizing it. With a fantastic customer-centric strategy, any firm hopes to generate revenue at the end of the day.

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.

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).

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.

What is the hybrid cloud architecture?#

Individually managing public and private cloud resources is preferable to uniformly managing cloud environments because it reduces the likelihood of process redundancy. By limiting the exposure of private data to the public cloud, a hybrid cloud architecture can eliminate many security risks. A hybrid cloud deployment infrastructure typically consists of a public infrastructure as a service (IaaS) platform, a private cloud or data centre, and network access. Many hybrid cloud deployment models make use of both local area networks (LAN) and wide area networks (WAN).

What is the purpose of a hybrid cloud?#

[Hybrid clouds] can also be used to create multi-cloud environments, giving businesses more options for where they want their data stored and how they want it accessed. By allowing businesses to back up data in both public and private clouds, a hybrid cloud deployment environment can be beneficial for disaster recovery.

What are the benefits of hybrid cloud deployment?#

Governance of applications that works: A hybrid cloud method allows you to choose where your application will run and where hybrid computing will take place [(Kaviani, Wohlstadter and Lea, 2014)]. This can assist to increase privacy while also ensuring compliance for your regulated apps.

Enhanced speed and decreased latency: A hybrid cloud solution might sometimes assist dispersed programmes in faraway regions. Hybrid computing occurs near the end consumers for applications with low latency needs.

Flexible operations: Hybrid computing allows you to function in an environment that is ideal for you. You may, for example, construct portable apps and simply migrate between public and private clouds by creating using containers.

Better ROI: You may increase your cloud computing capacity without raising your data centre costs by adding a public cloud provider to your existing on-premises architecture.

Hybrid Cloud Deployment Models#

Hybrid cloud deployment models are classified into three types:

Hybrid cloud deployment model architecture with a phased migration

You migrate applications or workloads from an on-premises data centre to the architecture of a public cloud service provider. This can be done gradually or all at once. This paradigm has the advantage of allowing you to use only what you need, assigning as much or as little as needed for each application or transaction. The negative is that it may not provide you as much control over how things work as if they were on using a private cloud deployment model [(Biswas and Verma, 2020)].

Hybrid cloud deployment model with apps that are only partially integrated

This concept entails migrating some but not all apps or transactions to the public cloud while maintaining others on-premises. If your organisation has apps that can operate in private cloud deployment model settings or public clouds like AWS or Azure, this is a terrific solution. Based on performance requirements or financial limits, you may determine which ones are a better fit for each case.

Hybrid cloud deployment model with integrated apps

The hybrid cloud strategy with integrated apps entails integrating applications running a private cloud deployment model and in the public cloud utilising PaaS software on the public cloud. The applications on the private cloud deployment model are installed using IaaS software and then integrated into the public cloud using PaaS software.

Is Hybrid Cloud the Best Option for Me?#

Hybrid cloud deployments are a popular choice for businesses that want to take advantage of cloud computing's flexibility and cost benefits while keeping control over their data and applications. To accomplish the intended business objective, hybrid cloud deployment often employs private, public, and third-party resources.

Hybrid Cloud Deployment Environment#

The following approaches can be used to deploy hybrid clouds:

Non-critical workloads should be outsourced to a public cloud: You can outsource a mission-critical system that does not require quick response times, such as a human resources application, to a public cloud provider [(Sturrus and Kulikova, 2014)]. This allows you to host and maintain applications on the public cloud while maintaining control over your data.

Use a virtual private cloud to deploy mission-critical workloads: The alternative is to host important workloads in a virtual private cloud (VPC). It is also the most widely used hybrid cloud deployment option since it mixes on-premises infrastructure with public cloud resources.

Dedicated hardware should be used to host the private cloud: Instead of depending entirely on public or private clouds, you host your private infrastructure on the private cloud deployment model's hardware under this architecture.

Cloud computing is exploding across a multitude of businesses, particularly with the rise of remote employment. Although it is a time-consuming procedure, the cloud may deliver significant financial benefits such as budget savings and better workplace efficiency. Many firms profit from hosting workloads on the cloud, but this cloud infrastructure services paradigm is not sustainable if your cloud expenses are out of control. Cloud computing companies must carefully consider the costs of cloud services. Cloud expenses soar for a variety of reasons, including overprovisioned resources, superfluous capacity, and a lack of insight into the environment. Cost optimization also assists businesses in striking a balance between cloud performance and expense. The best cloud computing platforms in the USA are Microsoft Azure, AWS, Google Cloud, and others.

Private Clouds vs Public Clouds#

Private clouds are hosted by the cloud computing companies that store their data in the cloud such as some of the cloud computing platforms in the USA. These clouds contain no data from other organisations, which is sometimes necessary for enterprises in highly regulated sectors to fulfill compliance norms. Because each cloud environment has only one organisation, the cost is frequently greater than with public clouds. This also implies that the organisation is in charge of upkeep.

Public clouds are hosted by cloud computing companies such as NIFE Cloud Computing, Amazon, and Google, and each can host several organisations. Although the data is separated to make it orderly and safe, multitenancy keeps pricing low. Furthermore, the seller maintains public clouds, lowering operational expenses for the organisation acquiring cloud space.

Reduces the Amount of Hardware Required

The reduction in hardware expenses is one advantage of public cloud computing. Instead of acquiring in-house equipment, hardware requirements are outsourced to a vendor (Chen, Xie and Li, 2018). New hardware may be enormous, costly, and difficult for firms that are fast expanding. Cloud computing solves these problems by making resources available fast and easily like those used by the best cloud computing platforms in the USA. Furthermore, the expense of maintaining or replacing equipment is passed on to the suppliers. In addition to purchasing prices, off-site hardware reduces internal power costs and saves space. Large data centres may consume valuable office space and generate a lot of heat.

Less demanding work and upkeep

Cloud solutions can also result in significant savings in labour and maintenance expenses. Because vendor-owned gear is housed in off-site locations, there is less requirement for in-house IT professionals. If servers or other gear require repairs or updates, this is the vendor's duty and does not cost your firm any time or money. By eliminating regular maintenance, your IT personnel will be able to focus on essential projects and development. In certain circumstances, this may even imply a reduction in workforce size. The cloud will enable organisations such as those among the best cloud computing platforms in the USA who do not have the means to hire an in-house IT team to reduce costly third-party hardware maintenance fees (Chen et al., 2017).

Increased output

Aside from direct labour savings, cloud computing may be incredibly cost-effective for businesses due to increased staff efficiency. Cloud software deployment is far faster than a traditional installation. Instead of taking weeks or months to complete a traditional cloud computing companies-wide installation, cloud software deployment may be completed in a matter of hours. Employees may now spend less time waiting and more time working (Masdari et al., 2016).

Lower initial capital outlay

Cloud solutions are often provided on a pay-as-you-go basis (Zhang et al., 2020). This format offers savings and flexibility in a variety of ways and is used by the best cloud computing platforms in the USA. First and foremost, your cloud computing company does not have to pay for software that is not being used. Unlike a one-time fee for a licence, cloud software is often charged on a per-user basis. Furthermore, pay-as-you-go software can be terminated at any moment, lowering the financial risk of any product that does not function properly.

Switch to NIFE Cloud Computing & Cloud-Native Development to save your Cloud Budget#

Nife Cloud Computing platform which is a Unified Public Cloud Edge Platform for securely managing, deploying, and scaling any application globally using Auto Deployment from Git. It requires no DevOps, servers, or cloud infrastructure services management. Nife collaborates with a wide range of new-generation technology businesses working on data centre infrastructure, cloud infrastructure services, and stateless microservices architectures to assist engineers and customers in making the deployment, administration, and scaling of their technology simpler. When compared to conventional cloud infrastructure services, applications on Nife can have latencies ranging from 20 to 250 milliseconds and total cost savings of up to 20%. Nife moves and deploys applications near clients' end-users, reducing application latencies.

Overall, Nife eliminates the requirement for bespoke DevOps, CloudOps, InfraOps, and cloud infrastructure services compliances - Security and Privacy. As a member of the Nife Grid, Nife has access to over 500 areas worldwide to assist clients in scaling. Nife Launchpad offers internal apps that can be launched with a single click to help startups develop functionality quicker. NIFE also has GIT integrations and is on the GIT marketplace, and our customer base includes some of the world's largest corporations, as well as numerous developers and engineers.

Introduction#

The notion of 'Interconnection Oriented Architecture (IOA)' might feel complex for a network system, but it's a simpler approach that relies on what's previously established inside the technological base. IOA, or Interconnection Oriented Architecture, is a corporate network approach that uses WAN, LAN, and cloud technology to accelerate data transport over long distances whilst maintaining clients' security and compatibility in every way [(Chadha, 2018)]. It supports a dynamic corporate network that increases digital participation and digital transition throughout the organisation.

Function of IOA

An IOA exists at the crossroads of virtual and [physical networking] systems; it connects Lan and WAN networks to enable digital interaction at any site and place in your organisation. IOA is capable of creating a value approach that fits your company's demands and therefore can respond more swiftly in the future by leveraging most of your current communications infrastructure. Interconnection Architecture is a multi-layered networking strategy that consists of a linked set of nodes, each having its type of communication [(Wrabetz and Weaver, 2018)]. The edge nodes are constructed from four separate layers:

What distinguishes IOA from SOA?#

As a technologically knowledgeable professional, you've certainly heard of business architecture concepts such as SOA. But what distinguishes SOA from IOA?

SOA is a software design method in which elements get resources via networking connectivity protocols. It is similar to a self BlackBox for a certain functional area. SOA in action is demonstrated through REST or representational data transfer [(Kasparick et al., 2018)]. Whereas IOA is an infrastructure development method based on Equinix colocation hub deployments. It addresses various key business issues that affect information and communication distribution.

Importance of IOA to businesses#

Networking is essential for effective corporate administration and consumer interaction. But why is IOA superior or more significant for your organisation than some other network technologies?

In reality, IOA solves numerous essential business difficulties and offers some unique advantages that can assist your company in adapting to and embracing the digital revolution. IOA connectivity depends on the location of the user instead of the network operator; it is vastly more extensible and adaptable than typical legacy networks [(Chauhan et al., 2019)]. This is a novel approach to addressing frequent business concerns or issues confronting your IT team.

Advantages of 'Interconnection-Oriented Architecture (IOA)#

Solving essential business challenges using IOA provides your company with a slew of new advantages, ranging from reduced latency to higher efficiency and everything else in between [(Sony, 2017)]. Whereas the advantages of IOA do not stop there, and here's a greater glance at what you may anticipate upon making the shift:

What kind of enterprises should use IOA?#

Whilst the IOA is useful to any business, it is most suitable for scattered or distant companies with an in-house IT team and a distinct requirement for enterprise-wide digital communication. These businesses frequently have a large amount of critical data flowing backward and forward over the networks, necessitating greater information leak prevention and GDPR conformity [(Stocker et al., 2017)]. In reality, the deployment of an IOA will assist all departments in the organization:

Sales Division - Interact with local sales staff and interact with potential customers throughout the engagement.

Marketing Division - Coordination of marketing and material distribution with the in-site and offsite personnel in various regions.

IT Division - Ease location configuration and activation while easily managing and maintaining data security and integrity throughout the enterprise.

Human Capital - Worker conformity with regulatory authorities should be evaluated and maintained.

C-Suite - Receive real-time information and views into key performance indicators (KPIs) to communicate with shareholders and investors [(Demchenko et al., 2015)].

How does IOA fit within your current infrastructure?#

IOA integrates LAN and WAN for improved networking connectivity; therefore, whether you're currently utilising SD-WAN or hybrid cloud computing services, it is an incredible asset to your infrastructure. IOA may be pushed out one area at a time to guarantee ease of acceptance and to track and handle any problems in the process, simplifying your deployment plan.

Conclusion#

Your company's connection is critical. Obtaining the best of all worlds is not a huge burden for your IT staff, and neither would it have to mean sacrificing business solutions. Return control over the business connectivity to your IT team by going ahead with an IOA.

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.

Introduction#

Edge computing, which is appropriate for serverless apps and other new ways of computing, is becoming more popular among developers. Edge computation moves development services and data directly to end-users by locating the computing functionality on the network's perimeter instead of in a centralised centre [(Cao et al., 2020)]. Many businesses have centralised their operations within massive data centres as a result of cloud technology. But, emerging end-user experiences, such as the Internet of Things (IoT), necessitate service delivery nearer to the network's "edges," where actual objects reside.

What is Edge Compute?#

Edge computing is the process of operating programs at the network's edge instead of on centralised equipment in a data centre or the cloud [(Premsankar, Di Francesco and Taleb, 2018)]. Nowadays, this implies virtualized computing, while various kinds of edge computing have existed in the past. The word also encompasses the whole set of technology, resources, and procedures that enable the capacity. This involves having an edge runtime environment, a programmer platform that is aligned with edge computing, an edge code deployment method, and so on.

What is an Edge device?#

Edge devices are pieces of physical machine positioned at the network's edge that have sufficient storage, processing capabilities, and computational capabilities to gather data, analyse it, and operate on it in near real-time with only little assistance from other sections of the network [(Gomes et al., 2015)]. Edge devices required network access to enable back-and-forth connectivity between both the machine and a centralised server. The data is gathered and analysed at the edge device.

When is Edge Computing useful?#

Edge computing is an attractive computing solution for a wide range of applications. It is not, though, a substitute for data centres or the cloud. Instead, the edge is indeed an extra location for code to execute. When target customers could gain through edge computing, it represents the largest value. For several reasons, developers seek to place computing near the edge when an online platform demands the lowest feasible amount of delay, and executing application programs closer to the people will achieve this aim [(Satyanarayanan, 2017)].

What are the typical use cases of edge computing?#

Edge computing can supplement a hybrid computing architecture in situations where centralised computing is employed, such as:

• Computation-intensive workloads
• Data collection and storage
• Machine learning/artificial intelligence
• Vehicles that drive themselves
• Augmented and Virtual Reality
• Smart Cities

Edge computing could also aid in the resolution of issues at the source of data in real-time. In general, there is indeed a use case for edge computing if decreased delay and/or real-time surveillance can serve business objectives.

The Internet of Things (IoT) - There may be several network stages in getting and processing a response for an IoT device. The greater the computing capability accessible on the machine physically, or near this in the network, the greater the customer experience.

5G - 5G is a use case for edge computing that also supports additional edge use cases.

Mobile technologies - When concerns develop in mobile computing, issues frequently focus on delay and disruption of services. By lowering data transmission delays, it can assist solve for strict latency limitations.

Telecommunications - As network operators update their networks, workload, and operations are being moved from the network infrastructure (datacentres) to the network's edge: surrounding stations and main locations [(Moura and Hutchison, 2019)].

What are the benefits of Edge Compute?#

Edge computing has several benefits for programmers and developers. The key beneficial effect, which leads to better end-user experiences, is low latency, although it is far from the only one. Putting computation at the edge promotes innovation. It moves to control and trust choices to the edge, allowing for more real-time apps and experiences with little personal data transit. Edge computing allows programmers to "simply code" without having to handle the difficulties of procuring computing resources and distributing code just at the edge with the correct tooling [(Cao et al., 2020)].

Why do IoT and edge computing have to collaborate?#

IoT generates a tremendous volume of data, which must be handled and evaluated before use. Edge computing brings computer resources closer to the edge or source of data, including an IoT system. Edge computing is indeed a localized resource of storage and processing for IoT device information and processing requirements, reducing communication latency between IoT systems and the main IT network to which they are linked [(Ai, Peng and Zhang, 2018)].

Final Thought#

Edge computing is a valuable resource and technique in today's data centre. Many telecommunication businesses are prioritizing edge as they update their network and explore new revenue streams. Many network operators, in particular, are shifting workloads and services out from the network infrastructure (in cloud data centres) and toward the network's edge, to global locations and main offices.

The vast majority of service providers now implement cloud services, and it has shown to be a success, with increased speed capacity installations, easier expandability and versatility, and much fewer hours invested on multiple hardware data center equipment. Conventional cloud technology, on the opposite side, isn't suitable in every situation. Azure by Microsoft, Google Cloud Platform (GCP), and AWS by Amazon are all conventional cloud providers with data centers all over the globe. Although each supplier's data center capacity is continually growing, such cloud services providers are not near enough to clients whenever a program requires the best performance and low delay. Consider how aggravating it is to enjoy a multiplayer game and have the frame rate decrease, or to stream a video and have the visual or sound connection delay. Edge computing is useful whenever speed is important or produced data has to be kept near to the consumers (Shi et al., 2016). This article evaluates two approaches to edge computing: 'Edge virtual machines (VMs)' and 'Edge containers', and helps developers determine which would be ideal for business.

What is Edge Computing?#

There are just a few data center areas available from the main cloud service providers. Despite their remarkable computing processing capability, the three top cloud service providers have only roughly 150 areas, most of which are in a similar region. These only cover a limited portion of the globe. Edge computing is powered by a considerably higher number of tiny data centers all over the globe. It employs a point of presence (PoP), which is often placed near wherever data is accessed or created. These PoPs operate on strong equipment and have rapid, dependable network access (Shi and Dustdar, 2016). It isn't an "either-or" situation when it comes to choosing between standard cloud and edge computing. Conventional cloud providers' data centers are supplemented or enhanced by edge computing.

[Edge computing] ought to be the primary supplier in several situations such as:

Streaming - Instead of downloading, customers are increasingly opting to stream anything. They anticipate streams to start right away, creating this a perfect application for edge computing.

Gaming - Ultra-low lag is beneficial to high scores in games and online gameplay.

Manufacturing - In manufacturing, the Internet of Things (IoT) and operational technology (OT) offer exciting new ways to improve monitoring systems and administration as well as run machines.

Edge Virtual Machines (Edge VMs)#

In a nutshell, virtual machines are virtual machines regardless of wherever they operate. Beginning with the hardware layer, termed as a bare-metal host server, virtual machines depend on a hypervisor such as VMware or Hyper-V to distribute computational resources across distinct virtual machine cases. Every virtual machine is a self-contained entity with its OS, capable of handling almost any program burden. The flexibility, adaptability, and optimum durability of these operations are significantly improved by virtual machine designs. Patching, upgrades, and improvement of the virtual machine's OS are required on a routine basis. Surveillance is essential for ensuring the virtual machine instances' and underpinning physical hardware infrastructure's stability (Zhao et al., 2017). Backup and data restoration activities must also be considered. All this amounts to a lot of time spent on inspection and management.

Virtual machines (VMs) are great for running several apps on the very same computer. This might be advantageous based on the demand. Assume users wish to run many domains using various Tomcat or .NET platforms. Users can operate them simultaneously without interfering with some other operations. Current apps may also be simply ported to the edge using VMs. If users utilize an on-premises VM or public cloud infrastructure, users could practically transfer the VM to an edge server using a lifting and shifting strategy, wherein users do not even affect the configuration of the app configuration or the OS.

Edge Containers#

A container is a virtualized, separated version of a component of a programme. Containers can enable flexibility and adaptability, although usually isn't for all containers inside an application framework, only for the one that needs expanding. It's simple to spin up multiple versions of a container image and bandwidth allocation among them after developers constructed one. Edge containers, like the containers developers have already seen, aren't fully virtualized PCs. Edge containers only have userspace, and they share the kernel with other containers on the same computer (Pires, Simão, and Veiga, 2021). It is often misinterpreted as meaning that physical machines provide less separation than virtual ones. Containers operating on the very same server, for instance, utilize the very same virtualization layer and also have recourse to a certain OS. Even though this seldom creates issues, it can be a stumbling barrier for services that run on the kernel for extensive accessibility to OS capabilities.

Difference Between VMs and Edge Containers#

Edge containers are appropriate whenever a developer's software supports a microservice-based design, which enables software systems to operate and scale individually. There is also a reduction in administrative and technical costs. Since the application needs specific OS integration that is not accessible in a container, VM is preferred when developers need access to a full OS. VM is required for increased capabilities over the technology stack, or if needed to execute many programs on the very same host (Doan et al., 2019).

Conclusion#

Edge computing is a realistic alternative for applications that require high-quality and low-delay access. Conventional systems, such as those found in data centers and public clouds, are built on VMs and Edge containers, with little change. The only significant distinction would be that edge computing improves users' internet access by allowing them to access quicker (Satyanarayanan, 2017). Developers may pick what's suitable for their requirements now that they understand further about edge computing, such as the differences between edge VMs and edge containers.

In this age of the internet, customers seek faster, stronger, better accessible, and more innovative data rates. Most users want to view videos on their phones as well as download files and operate a variety of IoT devices. They expect a 5G connection to deliver 100 times faster speeds, ten times greater capacity, and ten times lower latency. The shift to 5G requires considerable expenditures from telecommunications companies (Ahokangas et al., 2019). To provide new income streams and enable better effects and cost-effective processes, BSS should advance in tandem with 5Generation network installations. So get ready to face the difficulties of 5G monetization.

What is 5G Monetization?#

The commercialization of 5G is a hot topic. "Utilising the 5G customer possibility" and "5G, as well as the Business Potential" are two studies that go through the various market prospects. It illustrates that, in the long term, there is still a tremendous new income opportunity for carriers at multiple solution rates, targeted regions, and industrial control. "Taking liberties with 5G commercial patterns" highlights what AR/VR entertainment, Fixed Wireless Access (FWA), and 3D graphics experience might be supplied via B2C, B2B, and B2B2X interaction designs. Network operators should analyse their BSS progression along with their 5G facilities to fulfil the 5G obligations of greater network rate of speed and frequency band, ultra-low latency, fully convinced quality of service, communication, and flexibility. Operators must take the chance or risk missing out on some of these potential applications when they become a reality (Dramitinos, Stamoulis, and Lonsethagen, 2017). 5G monetization is among the capabilities that will allow companies to deliver on their 5G commitments right away. To satisfy 5G use cases and deliver the full potential of 5G, CSPs must upgrade their BSS in parallel with their 5G rollout, or face falling behind in the 5G competition for profitable technology.

Addressing the Development of the BSS Architecture#

To effectively understand the benefits of 5G monetization, network operators must consider the growth of their telecommunication BSS from a range of viewpoints:

• 5G Convergent Charging System (CCS): These latest 5G Basic specifications define a CCS, which includes a 5G Charging Function (CHF), that enables merged charges and expenditure limitation management in the modern business design. The CHF is triggered by both physical and digital activities and either triggers the OCS (online charging system) for internet grading or generates an uncensored EDR (event data record) for offline grading (Stojanović, Radenković, and Bogdanović, 2021).

• Orchestration, Completion, and Guarantee of Service: As more distributed systems and commercial services arise, service synchronization and fulfilment must become more difficult and stringent to guarantee that commodities, bundles, and trials, involving own and third-party items, are discussed, acquired, and engaged as soon as customers demand them.

• Exposure: As the 5G network connects new business opportunities and sectors, distributors must ensure that existing BSS features are available to anyone who wants to safely use those via standardized TMF Open APIs. Additional BSS apps, adjacent layers including OSS and Core network, or third parties and collaborators who extend 5G products with their own capabilities might all be consumers of BSS APIs.

• Cloud Architecture: The productivity, efficiency, versatility, and robustness required by 5G systems and services necessitate a new software design that considers BSS installations in the cloud, whether private, public, or hybrid.

Network operators are unlikely to entirely alter current BSS in all of these sectors at the very same time. Future 5G earnings won't all be available right away; they'll arrive in waves as various markets and sectors mature. To determine when business development will begin or how this process or path will appear, carriers must consider their unique scenario, success in the market, desired place in the 5G supply chain, and evolutionary competence (Yeh et al., 2020).

The AR Gaming Use Case and Intelligent Operations#

The 5G Core along with BSS and OSS all in place will bring along a potential partner: a cloud gaming provider that intends to promote [AR gaming] to the carrier's subscribers. For such gaming data, companies want a specific network segment with an assured level of service. Each collaborator can demand their network connection and establish their SLAs using distribution platforms in a smart, fully automated network. BSS breaks down this ordering into multiple sub-orders, like the construction and deployment of the particular portion via the OSS, when it receives it. All specified SLAs are simply assigned in the particular portion at the very same time, and verification begins monitoring the defined indications immediately. There is no human interference in any of this.

The operator additionally uses its archive design to describe the service offering that its customers will acquire in addition to being implemented on the partner's particular portion all in one location (Smith and Ugolini, 2021). This promotion is immediately disseminated to all relevant systems, including online charging, CRM, and digital platforms, and may be consumed immediately. It's also accessible to partners via an API, who may combine it with additional perks while offering it to customers. The operators can utilize smart suggestions to target individual customers with the new offer depending on their consumption habits and behavior.

Conclusion for 5G Monetization#

Ultimately, whenever a customer decides to buy a package, they automatically implement it in the network segment, often without touching the system. The partners would be able to monitor the networking health-related level of performance details for every customer instantaneously and will also be ready to obtain immediate decisions or conduct offers based on this data. New platforms can adapt to changes based on factual capacity because of the BSS cloud architecture (Peterson and Sunay, 2020). Every detail relating to transactions, items, network bandwidth, and profitability goals, along with other factors, is given back into circulation and utilized as parameters for networking and inventory development in a confined manner.

Multi-access edge computing (MEC) has evolved as a viable option to enable mobile platforms to cope with computational complexity and lag-sensitive programs, thanks to the fast growth of the Internet of Things (IoT) and 5G connectivity. Computing workstations, on the other hand, are often incorporated in stationary access points (APs) or base stations (BSs), which has some drawbacks. Thanks to drones' portability, adaptability, and maneuverability, a new approach to drone-enabled airborne computing has lately received much interest (Busacca, Galluccio, and Palazzo, 2020). Drones can be immediately dispatched to defined regions to address emergency and/or unanticipated needs when the computer servers included in APs/BSs are overwhelmed or inaccessible. Furthermore, relative to land computation, drone computing may considerably reduce work latency and communication power usage by making use of the line-of-sight qualities of air-ground linkages. Drone computing, for example, can be useful in disaster zones, emergencies, and conflicts when grounded equipment is scarce.

Drones as the Next-Generation Flying IoT#

Drones will use a new low-power design to power the applications while remaining aloft, allowing them to monitor users and make deliveries. Drones with human-like intelligence will soon be able to recognize and record sportsmen in action, follow offenders, and carry things directly to the home. But, like with any efficient system, machine learning may consume energy, thus research on how to transfer a drone's computing workloads to a detector design to keep battery use low to keep drones flying for very much longer is necessary. Drones are a new type of IoT gadget that flies through the air with complete network communication capabilities (Yazid et al., 2021). Smart drones with deep learning skills must be able to detect and follow things automatically to relieve users of the arduous chore of controlling them, all while operating inside the power constraints of Li-Po batteries.

Drone-assisted Edge Computing#

The 5G will result in a significant shift in communications technologies. 5G will be required to handle a huge amount of customers and networking equipment with a wide range of applications and efficiency needs (Hayat et al., 2021). A wide range of use instances will be implemented and back, with the Internet of Things (IoT) becoming one of the most important due to its requirement to communicate a large number of devices that collect and transmit information in numerous different applications such as smart buildings, smart manufacturing, and smart farming, and so on. Drones could be used to generate drone cells, which also discusses the requirement for combining increasing pressure of IoT with appropriate consumption of network resources, or perhaps to establish drones to deliver data transmission and computer processing skills to mobile users, in the incident of high and unusual provisional incidents generating difficult and diverse data-traffic volume.

How AI at the Edge Benefits Drone-Based Solutions#

AI is making inroads into smart gadgets. The edge AI equipment industry is growing at a quicker rate due to the flexibility of content operations at the edge. Data accumulation is possible with edge technology. Drones, retail, and business drones are rising in popularity as edge equipment that creates data that has to be processed. Drones with Edge AI are better for construction or manufacturing, transportation surveillance, and mapping (Messous et al., 2020). Drones are a form of edge technology that may be used for a variety of tasks. Visual scanning, picture identification, object identification, and tracking are all used in their work. Drones using artificial intelligence (AI) can recognize objects, things, and people in the same manner that humans can. Edge AI enables effective analysis of the data and output production based on data acquired and delivered to the edge network by drones, and aids in the achievement of the following goals:

• Object monitoring and identification in real-time. For security and safety purposes, drones can monitor cars and vehicular traffic.
• Infrastructure that is aging requires proactive upkeep. Bridges, roads, and buildings degrade with time, putting millions of people in danger.
• Drone-assisted surveillance can help guarantee that necessary repairs are completed on time.
• Face recognition is a technique for recognizing someone's face whereas this prospect sparks arguments about the technology's morality and validity, AI drones with face recognition can be beneficial in many situations.

Drones may be used by marketing teams to track brand visibility or gather data to evaluate the true influence of brand symbol installation.

Challenges in Drone-Assisted Edge Computing#

Drone computing has its own set of challenges such as:

• Drone computing differs greatly from ground computation due to the extreme movement of drones. Wireless connectivity to/from a drone, in particular, changes dramatically over time, necessitating meticulous planning of the drone's path, task distribution, and strategic planning.
• Computational resources must also be properly apportioned over time to guarantee lower data energy usage and operation latency. A drone's power flight plan is critical for extending its service duration (Sedjelmaci et al., 2019).
• Due to a single drone's limited computing capability, many drones should be considered to deliver computing services continuously, where movement management, collaboration, and distribution of resources of numerous drones all necessitate sophisticated design.

Conclusion#

In drone computing, edge technology guarantees that all necessary work is completed in real-time, directly on the spot. In relief and recovery efforts, a drone equipped with edge technology can save valuable hours (Busacca, Galluccio, and Palazzo, 2020). Edge computing, and subsequently edge AI, have made it possible to take a new and more efficient approach to information analysis, resulting in a plethora of information drone computing options. Drones can give value in a range of applications that have societal implications thanks to edge technology. [Edge data centres] will likely play a key part in this, maybe aiding with the micro-location data needed to run unmanned drone swarms in the future. Increasing commercial drone technology does have the ability to provide advantages outside of addressing corporate objectives.

Read more about the Other Edge Computing Usecases.

Mobile Edge Computing (MEC) can aid is with real estate property browsing. MEC can provide a two-fold answer. Most buyers look at many residences and don't make decisions without viewing them. Engaging Mobile Edge Computing (MEC) applications like augmented reality (AR) and virtual reality (VR) demonstrate strong opportunities to connect the external and simulated worlds, whether it's putting a virtual couch in your sitting room as part of an interactive retail setting or allowing forecasting refurbishment steered by actual data as well as a layering of step-by-step graphic guidelines. As an element of synchronized and safe processes, the objective is to allow all sides to see what other sees. Combining smartphones and tablets, iPads, and smartwatches with virtual collaborative technologies redefine learning and allow product specialists to help from a distance (Ambrose and Shen, 2021). The goal is to make the distant assessment, replacement, and service of existing goods more efficient.

AR (augmented reality) and VR (virtual reality) are still considered specialized innovations which have yet to be widely accepted. A lot of it comes down to the issues that edge computing can now solve. Following the commercial release of 5G, AR (augmented reality) and VR (virtual reality) encompasses a slew of innovative application cases that, when combined by the edge of the network, will provide significant value to the sector and businesses. Applying virtual layers to live sights is what augmented reality is all about. It can be performed with a device, but in business, wearable technology is much more probably to be used. VR is total absorption in a digital perspective that requires the use of a set of glasses that block the user's view of the world surrounding them (Gerasimova, 2019).

The real estate sector is likely to be transformed by this technology, which some belief would make property hunting more effective. It can help purchaser's picture houses in progress and alleviate the stress of moving to the new location or purchasing from overseas.

What role does Edge and AR play in wooing customers in property hunting?#

With AR (augmented reality), real estate reaches new heights in terms of providing consumers with a more efficient and interesting visual journey. Retailers may now transport them to any destination they like. Offer visitors a digital tour to relieve the stress of having to figure out road signs and building numbers while travelling. People will also have a complete image of the place after they have had the opportunities to explore it. Aside from the ease, it provides to property buyers, it also assists real estate brokers in other ways. Augmented Reality may also be used for branding and advertising (Lang and Sittler, 2012).

The following are some of the marketing aspects of augmented reality for property investment:

• More dynamic print catalogues and large boards are being developed.
• Spatial that really can help for-sale properties in real-time.
• Get an interactive function in the app so a potential buyer may reach out to the retailer right away.
• A larger audience

How to Use Virtual Reality in Property Hunting?#

Virtual reality performs a vital part in the property market, from real estate development to housing developments. Let's take a look at several ways that may use virtual reality property hunting:

• Guided Visits: Property hunters, on the whole, compile a list of properties they wish to see and then go to the locations. Some residences are nearby, while some are on the periphery. As a result, planning a visit and narrowing down a list of prospective homes becomes physiologically and psychologically demanding. VR in the housing market efficiently overcomes all of these issues (Pleyers and Poncin, 2020).

• Participatory Visits: Participatory visits are growing in popularity these days. The key difference between supervised and participatory trips would be that active trips allow property hunters to tap on the display and zoom in on certain areas of the property.

• Virtual Staging: The term "virtual staging" refers to the technique of electronically furnishing vacant places. Simply defined, VS is a property investment internet marketing tactic that lets customers see themselves in completely furnished homes.

• Communication: Modern residences and ultra-luxury homes now provide a variety of public utilities. While such products and services provide convenience, they may also be perplexing sometimes.

The Benefits of Edge-VR in Property Hunting:#

• Time and money-saving.
• Creates an emotional bond.
• Profits increased.
• Experimentation is simple.
• Reach Out to a Larger Audience

What is the difference between VR and AR?#

AR and VR are both disruptive technologies, they have some significant distinctions:

Conclusion for Edge and AR#

Several businesses that are willing to embrace augmented reality are unable to do so due to limitations in their capacity to exchange data on the cloud. Companies may utilise graphical tools and applications like Zoom or Microsoft Exchange for normal communication, but they can't use the same cloud-based solutions for critical organisational activities like learning, support, or technical access because of data security and privacy ownership issues. AR and VR are on the verge of allowing participants to take their immersive experience with others, which is something that most people like about property hunting. In terms of what's feasible, both AR and VR are advancing at breakneck speed (Deaky and Parv, 2017). It's nearly a perfect match for property hunting.

To know the benefits of Edge Computing please read: Differentiation Between Edge Computing and Cloud Computing

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.

Edge technology as a modern industry sprung up as a result of the shift of processing from cloud to edge. Cloud gaming services is booming as a result of the need of more low latency benefits for the end users.

As the gadgets interconnected to the internet grows and their possibilities improve, so too does the demand for real making decisions free of cloud computing's delay and, sometimes in circumstances, connection. Edge technology is a modern industry that has sprung up as a result of the shift of processing resources from the cloud to the edge. Edge computing gives proper local machine learning to gadgets without the need to contact the cloud to make conclusions. IoT gadgets function under settings that vary from some of those found in corporate offices, necessitating the establishment of a new range of components to enable processing in such locations. The expanding usage of cloud-based AI techniques like machine learning techniques is pushing developments in hardware designs that can keep up with the applications' voracious need for computing power and storage capacity (Gan et al., 2019). Without developments in technology, technologies such as instant-booting PCs, cell phones, jaw-dropping video game graphics, lightning-fast in-memory analytics, and hugely spacious memory devices would be significantly more restricted or prohibitively costly.

Edge Computing#

Edge computing is a decentralized IT framework inside which customer data is analysed as near to the original point as feasible at the platform's perimeter. Edge computing relocates certain memory and computation capabilities away from the main data centre and nearer to the raw data. Instead of sending unprocessed information to a data centre for analysis and interpretation, this process is carried in which the information is captured, whether in a retail outlet, a manufacturing floor, a large utility, or throughout a smart city Coppolino et al., 2019. IT and corporate computing are being reshaped by edge computing.

Edge computing Hardware?#

The structural characteristics and capabilities required to operate a program at the edge are referred to as edge computing hardware. Centres, CPUs, networking devices, and endpoint devices are among these technologies (Capra et al.,2019) . Edge Ecosystem Analyzer is used to learn about additional aspects of the edge value chain.

Impact of Edge Computing on Hardware for Cloud Gaming#

Edge computing has a wide range of functions that work in a variety of circumstances and environments. Dependent on various application scenarios and sectors, they have various hardware needs. It's no coincidence that several businesses are moving to the edge as connection improves and the development of low-delay "real-time" data processing grows. With this change, nevertheless, there seems to be a significant necessity for edge computing gear to be created for unique circumstances for its many business applications, each with its own set of hardware specifications (Satyanarayanan et al., 2021) . For instance, in automated vehicles, ultimate decision-making is required for movement control, therefore increased hardware is a requirement owing to the massive volumes of data being analysed in real-time; but, thanks to the car's limited space, equipment design is indeed a limitation.

Gaming on the Edge ( and Cloud)#

The majority of game computation is now performed on gadgets directly. Although some computing may be performed on a remote server — where a gadget can transmit information to be analyzed and then delivered into these systems is often located far away in enormous data centres, which implies the time it would take for data to be delivered will eventually diminish the gaming performance. Rather than a single huge remote server, mobile edge computing depends on multiple small distribution centres that are located in a nearer close presence (Braun et al., 2017). So because gadgets won't just have to transfer information to a data computer, analyze it, and afterwards deliver the data, MEC can preserve computing power on gadgets for a smoother, quicker gameplay experience.

Cloud computing#

Something that includes offering distributed services via the internet is referred to as cloud computing. IaaS, PaaS, and SaaS are the three basic forms of cloud computing technology. It is possible to have a business or government cloud. Everyone on the internet may buy services from a cloud platform (Younas et al., 2018). A private cloud is a closed network or data centre that provides a platform as a service to a small group of individuals with policy actions and privileges. The purpose of cloud computing, whether business or government, is to give quick, flexible access to network infrastructure and IT applications.

Cloud infrastructure and hardware#

Cloud infrastructure is a word that refers to the hardware, abstract services, memory, and networking capacity that are required for cloud computing. Consider cloud infrastructure to be the technologies required to create a cloud. Cloud infrastructure is required to operate operations and services in the cloud.

Cloud Gaming#

Cloud gaming refers to the practice of playing games on servers located remotely in cloud services. On either a PC or smartphone, so no need to acquire and download games. Rather, to deliver game data to an application or website loaded on the target device, streaming sites create a steady internet service. The action is generated and performed on a distant server, yet everything here is seen and interacted with directly on the devices. Throughout most situations, cloud computing gaming involves an annual or monthly membership to obtain the game. Some applications need the acquisition of games in addition to the charge (Choy et al., 2014). Customized or internet apps are frequently given by cloud gaming solutions to stream sports.

Conclusion#

The role of the network is changing when it comes to offering exceptional experiences with these new interactions. The growing use of cloud-based AI techniques such as machine learning is driving hardware innovations that can keep up with the applications' insatiable need for computational power and storage space. Edge computing encompasses a wide range of capabilities that may be used in some situations and contexts (Gan et al., 2019). Cloud gaming is booming, due in part to the global coronavirus outbreak and broad implementation of shelter-in-place rules. Gaming is a tremendous technical platform that can be applied to a wide range of sectors, including Edge, Cloud and Hardware.

Read More about Edge Gaming

Can an AI-based edge computing platform drive businesses or is that a myth? We explore this topic here._

Introduction#

For a long time, artificial intelligence has been a hot issue. We've all heard successful tales of forward-thinking corporations creating one brilliant technique or another to use Artificial Intelligence technology or organizations that promise to put AI-first or be truly "AI-driven." For a few years now, Artificial Intelligence (AI) has been impacting sectors all around the world. Businesses that surpass their rivals are certainly employing AI to assist in guiding their marketing decisions, even if it isn't always visible to the human eye (Davenport et al., 2019). Machine learning methods enable AI to be characterized as machines or processes with human-like intelligence. One of the most appealing features of AI is that it may be used in any sector. By evaluating and exploiting excellent data, AI can solve problems and boost business efficiency regardless of the size of a company (Eitel-Porter, 2020). Companies are no longer demanding to be at the forefront or even second in their sectors; instead, businesses are approaching this transition as if it were a natural progression.

Artificial Intelligence's (AI-driven) Business Benefits#

Businesses had to depend on analytics researchers in the past to evaluate their data and spot patterns. It was practically difficult for them to notice each pattern or useful bit of data due to the huge volume of data accessible and the brief period in their shift. Data may now be evaluated and processed in real-time thanks to artificial intelligence. As a result, businesses can speed up the optimization process when it comes to business decisions, resulting in better results in less time. These effects can range from little improvements in internal corporate procedures to major improvements in traffic efficiency in large cities (Abduljabbar et al., 2019). The list of AI's additional advantages is nearly endless. Let's have a look at how businesses can benefit:

• A More Positive Customer Experience: Among the most significant advantages of AI is the improved customer experience it provides. Artificial intelligence helps businesses to improve their current products by analyzing customer behavior systematically and continuously. AI can also help engage customers by providing more appropriate advertisements and product suggestions (Palaiogeorgou et al., 2021).

• Boost Your Company's Efficiency: The capacity to automate corporate procedures is another advantage of artificial intelligence. Instead of wasting labor hours by having a person execute repeated activities, you may utilize an AI-based solution to complete those duties instantly. Furthermore, by utilizing machine learning technologies, the program can instantly suggest enhancements for both on-premise and cloud-based business processes (Daugherty, 2018). This leads to time and financial savings due to increased productivity and, in many cases, more accurate work.

• Boost Data Security: The fraud and threat security capabilities that AI can provide to businesses are a major bonus. AI displays usage patterns that can help to recognize cyber security risks, both externally and internally. An AI-based security solution could analyze when specific employees log into a cloud solution, which device they used, and from where they accessed cloud data regularly.

Speaking with AI Pioneers and Newcomers#

Surprisingly, by reaching out on a larger scale, researchers were able to identify a variety of firms at various stages of AI maturity. Researchers split everyone into three groups: AI leaders, AI followers, and AI beginners (Brock and von Wangenheim, 2019). The AI leaders have completely adopted AI and data analysis tools in their company, whilst the AI beginners are just getting started. The road to becoming AI-powered is paved with obstacles that might impede any development. In sum, 99% of the survey respondents have encountered difficulties with AI implementation. And it appears that the more we work at it, the more difficult it becomes. 75% or more of individuals who launched their projects 4-5 years ago faced troubles. Even the AI leaders, who had more effort than the other two groups and began 4-5 years earlier, had over 60% of their projects encounter difficulties. When it comes to AI and advanced analytics, it appears that many companies are having trouble getting their employees on board. The staff was resistant to embracing new methods of working or were afraid of losing their employment. Considering this, it should be unsurprising that the most important tactics for overcoming obstacles include culture and traditions (Campbell et al., 2019). Overall, it's evident that the transition to AI-driven operations is a cultural one!

The Long-Term Strategic Incentive to Invest#

Most firms that begin on an organizational improvement foresee moving from one stable condition to a new stable one after a period of controlled turbulence (ideally). When developers look at how these AI-adopting companies envision the future, however, this does not appear to be the case. Developers should concentrate their efforts on the AI leaders to better grasp what it will be like to be entirely AI-driven since these are the individuals who've already progressed the most and may have a better understanding of where they're headed. It's reasonable to anticipate AI leaders to continue to outpace rival firms in the future (Daugherty, 2018). Maybe it's because they have a different perspective on the current, solid reality that is forming. The vision that AI leaders envisage is not one of consistency and "doneness" in terms of process. Consider a forthcoming business wherein new programs are always being developed, with the ability to increase efficiency, modify job processing tasks, impact judgment, and offer novel issue resolution. It appears that the steady state developers are looking for will be one of constant evolution. An organization in which AI implementation will never be finished. And it is for this reason that we must start preparing for AI Edge Computing Platform to pave the way for the future.

References#

• Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S.A. (2019). Applications of Artificial Intelligence in Transport: An Overview. Sustainability, 11(1), p.189. Available at: link.
• Brock, J.K.-U., & von Wangenheim, F. (2019). Demystifying AI: What Digital Transformation Leaders Can Teach You about Realistic Artificial Intelligence. California Management Review, 61(4), pp.110–134.
• Campbell, C., Sands, S., Ferraro, C., Tsao, H.-Y. (Jody), & Mavrommatis, A. (2019). From Data to Action: How Marketers Can Leverage AI. Business Horizons.
• Daugherty, P.R. (2018). Human + Machine: Reimagining Work in the Age of AI. Harvard Business Review Press.
• Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2019). How Artificial Intelligence Will Change the Future of Marketing. Journal of the Academy of Marketing Science, 48(1), pp.24–42. Available at: link.
• Eitel-Porter, R. (2020). Beyond the Promise: Implementing Ethical AI. AI and Ethics.
• Palaiogeorgou, P., Gizelis, C.A., Misargopoulos, A., Nikolopoulos-Gkamatsis, F., Kefalogiannis, M., & Christonasis, A.M. (2021). AI: Opportunities and Challenges - The Optimal Exploitation of (Telecom) Corporate Data. Responsible AI and Analytics for an Ethical and Inclusive Digitized Society, pp.47–59.

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.

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-

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