Live Tracking App for Converged Network Device Health Analysis

Installing converged network solutions is a transformative step for any organization looking to streamline its IT infrastructure. By offering real-time insights into the health of converged network devices, these solutions help IT teams identify device health issues from a centralized platform.

With more network devices becoming affordable and easy to install, companies of every size are standardizing their use of network devices within their IT premises. However, companies of every size don’t usually have a well-engineered device health monitoring system in place.

The client identified this gap and wanted to democratize technology by building a web application to help organizations across sectors accurately measure network device health metrics. The client wanted this app to evaluate the performance metrics of sensors, switches, controllers, detectors, servers, and cameras and display live data feeds.

They approached Capital Numbers to build this centralized software application. They requested our team to develop a large and complex app that could provide real-time insights into the status of critical network devices and assets.

Plus, they wanted this app to contain configurable micro apps, which organizations could tailor according to their needs. Each micro application had to have data visualization capabilities showing device health metrics, alerting authorities to any anomalies before they escalated into costly downtime.

Capital Numbers began by developing this application’s three micro frontends: a main micro frontend, an asset micro frontend, and a general micro frontend. We created each of these micro frontends as a self-contained React app, each one communicating with the other through powerful APIs.

We added configurable data visualization elements in each micro frontend, eliminating the risks of costly upgrades associated with monolith front ends. We also incorporated color-coded indicators to clearly show device health statuses. We concurrently added new features in each micro frontend without affecting the entire system, enabling easy development.

We built the backend using Python because it allowed seamless integration with various network devices and protocols. Python’s robust libraries, like Pandas and NumPy, came with various statistical functions that helped access and process raw data related to network device performance.

For data storage, we used PostgreSQL and enhanced the app’s overall code quality with TypeScript. We incorporated alerts and notifications within the system using the NATS messaging layer. With NATS, we could enable prompt detection of potential network device failures. With Grafana's beautiful charts and geo maps, we could create customizable dashboards.

In addition to the above, we added NetraGPT to allow users to query and obtain device health reports and metrics. By training the GPT model, we fully equipped it to respond to complex user queries about network device health.

Once we made all the integrations, we checked the optimal performance of the dashboards and summary views. We thoroughly diagnosed if the system gave visual reports of network device health metrics and interfaces precisely as needed.

Capital Numbers’ strategic architectural decisions drove exceptional outcomes. The final product is an outstanding GUI containing transformative insights and intuitive displays on device health metrics. Here’s what the application brings forth: