The supply of continually updated information streaming at zero or low latency is referred to as real-time (data) monitoring [(Fatemi Moghaddam et al., 2015)]. IT monitoring entails routinely gathering data from all areas of an organization's IT system, such as on hardware, virtualized environments, networking, and security settings, as well as the application stack, including cloud-based applications, and software user interfaces in cloud computing companies. IT employees use this data to assess system performance, identify abnormalities, and fix issues. Real-time application monitoring raises the stakes by delivering a continuous low-latency stream of relevant and current data from which administrators may quickly spot major issues. Alerts can be delivered more rapidly to suitable personnel – or even to automated systems – for remediation. Cloud computing companies can disclose and forecast trends and performance by recording real-time monitoring data over time.

Nife Cloud Computing & Cloud-Native Development#

Nife is a serverless platform for developers that allows enterprises to efficiently manage, launch, and scale applications internationally. It runs your apps near your users and grows to compute in cities where your programme is most often used. Traditionally, programmes are placed on the cloud computing companies which are located far away from the end-user. When data moves between regions and places, it creates computational issues such as bandwidth, cost, and performance, to mention a few.

Nife architecture#

Cloud is constructed in the style of a Lego set. To build a multi-region architecture for your applications across constrained cloud regions, you must first understand each component: network, infrastructure, capacity, and computing resources [(Odun-Ayo et al., 2018)]. Manage and monitor the infrastructure as well. This still does not affect application performance.

Nife PaaS Platform enables you to deploy various types of services near the end-user, such as entire web apps, APIs, and event-driven serverless operations, without worrying about the underlying infrastructure. Nife includes rapid, continuous deployments as well as an integrated versioning mechanism for managing applications. To allow your apps to migrate across infrastructure globally, you may deploy normal Docker containers or plug your code straight from your git repositories. Applications may be deployed in many places spanning North America, Latin America, Europe, and the Asia Pacific. The Nife edge network includes an intelligent load balancer and geo-routing based on rules.

Nife Instantly deploy all applications

To install any application quickly and easily everywhere, NIFE provides on-demand infrastructure from a wide range of worldwide suppliers.

• Nife deploy your application in seconds by using Docker images or by connecting your git repository and simply deploying.

• Run internationally with a single click - Depending on your requirements, you may run your apps in any or all of our locations. With 500 Cloud, Edge, and Telco sites, you can go worldwide.

• Seamless auto-scaling- Any region, any position at the nearest endpoint at your fingertips [(Diaby and Bashari, 2017)].

• Anything may be run - NIFE are ready to power Telco Orchestration demands from MEC to MANO to ORAN beyond the edge cloud using Containers, Functions, and MicroVMs!

Nife's Edge Ecosystem

It is critical to stay current with the ecosystem to have a resilient, intelligent global infrastructure [(Kaur et al., 2020)]. NIFE collaborate with various cloud computing companies' supporters to establish an edge ecosystem, whether it be software, hardware, or the network.

• Flexible - Customers of NIFE have access to infrastructure distributions worldwide, in every corner and area, thanks to the Public Edge. NIFE can reach Billions of users and Trillions of devices using these.

• Unified - Nife's Global Public Edge is a network of edge computing resources that support numerous environments that are globally spread and deployable locally.

• Widely dispersed - Developers may distribute workloads to resources from public clouds, mobile networks, and other infrastructures via a single aggregated access.

How does Nife's real-time application monitoring function?#

Nife's real-time monitoring conveys an IT environment's active and continuing condition. It may be configured to focus on certain IT assets at the required granularity.

The following are examples of real-time data: CPU and memory usage; application response time; service availability; network latency; web server requests; and transaction times are all factors to consider.

Real-time application monitoring tools, in general, shows pertinent data on customised dashboards. Data packet categories and formats can be shown as numerical line graphs, bar graphs, pie charts, or percentages by admins. The data displays can be adjusted based on priorities and administrative choices.

The Nife's Real-Time Monitoring and Benefits of Cloud Computing#

Collecting real-time monitoring data allows IT administrators to analyse and respond to current occurrences in the IT environment in real time. Furthermore, cloud computing companies may store and analyse real-time data over time to uncover patterns and better notice irregularities that fall outside of the predefined system and application behaviour limits. This is referred to as trend monitoring and it's among the best benefits of cloud computing.

Reactive monitoring vs. proactive monitoring: Reactive monitoring has long been used in cloud computing companies and data centres as a troubleshooting tool [(Poniszewska-Maranda et al., 2019)]. The name of this technique reveals its distinguishing feature: It responds to triggers that indicate the occurrence of an event.

Large-scale manufacturing units, especially industrial setups, have complicated equipment. Condition-based monitoring at the edge is unprecedented. Can this cost be reduced?

Learn More!

Background#

The world is leaning toward the Industrial 4.0 transformation, and so are the manufacturers. The manufacturers are moving towards providing services rather than selling one-off products. Edge computing in manufacturing is used to collect data, manage the data, and run the analytics. It becomes essential to monitor assets, check for any faults, and predict any issues with the devices. Real-time data analysis of assets detects faults so we can carry out maintenance before the failure of the system occurs. We can recognize all the faulty problems with the equipment. Hence, we need condition-based monitoring.

Why Edge Computing for Condition-Based Monitoring?#

Edge computing is used to collect data and then label it, further manage the data, and run the system's analytics. Then, we can send alerts to the end enterprise customer and the OEM to notify them when maintenance service is required. Using network edge helps eliminate the pain of collecting data from many disparate systems or machines.

The device located close to the plants or at the edge of the network provides condition-based monitoring, preempts early detection, and correction of designs, ensuring greater productivity for the plant.

Key Challenges and Drivers of Condition-Based Monitoring at Edge#

• Device Compatibility
• Flexibility in Service
• Light Device Support
• Extractive Industries

Solution#

To detect machinery failures, the equipment has a layer of sensors. These sensors pick up the information from the devices and pass it to a central processing unit.

Here, edge computing plays a crucial part in collecting and monitoring via sensors. The data from the sensors help the OEM and the system administrators monitor the exact device conditions, reducing the load on the end device itself. This way, administrators can monitor multiple sensors together. With the generation of the events, failure on one device can be collated with another device.

Edge also allows processing regardless of where the end device is located or if the asset moves. The same application can be extended to other locations. Alternatively, using edge helps remove the pain of collecting data from many disparate systems/machines in terms of battery.

The edge computing system based on conditions is used to collect statistics, manage the data, and run the analytics without any software hindrance. A system administrator can relax as real-time data analysis detects faults to carry out maintenance before any failure occurs.

Condition-based monitoring can be used in engineering and construction to monitor the equipment. Administrators can use edge computing industrial manufacturing for alerts and analytics.

On-Prem vs. Network Edge#

Given that the on-prem edge is lightweight, it's easy to place anywhere on the location. On the other hand, installing a device is overridden if the manufacturing unit decides to go with the network edge; hence, flexibility is automatically achieved.

How Does Nife Help with Condition-Based Monitoring at Edge?#

Use Nife as a network edge device to compute and deploy applications close to the industries.

Nife works on collecting sensor information, collating it, and providing immediate response time.

Benefits and Results#

• No difference in application performance (70% improvement from Cloud)
• Reduce the overall price of the Robots (40% Cost Reduction)
• Manage and monitor all applications in a single pane of glass
• Seamlessly deploy and manage navigation functionality (5 min to deploy, 3 min to scale)

Edge computing is an asset to different industries, especially device manufacturers, helping them reduce costs, improve productivity, and ensure that administrators can predict device failures.

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