Real-Time Network Device Health Monitoring and Analytics Dashboard

Organizations across sectors are increasingly adopting converged network solutions to streamline IT infrastructure. However, many lack a well-engineered device health monitoring system that provides real-time insights into device performance, health metrics, and potential failures. This gap results in delayed detection of issues, increased risk of costly downtime, and inefficient proactive maintenance, especially as the number and complexity of network devices grow.

A mid-to-large enterprise specializing in energy infrastructure management, deploying converged network devices such as routers, switches, and sensors across critical sites to ensure operational uptime.

• Develop a web-based application capable of providing real-time performance insights for a wide range of network devices including sensors, switches, controllers, servers, and cameras.
• Enable visualization of device health metrics with configurable, customizable dashboards and micro-apps.
• Implement alerting mechanisms for threshold breaches and device anomalies to facilitate proactive maintenance.
• Incorporate data visualization features such as dynamic graphs, trend lines, and historical data analysis.
• Allow users to query detailed device health reports via natural language processing capabilities integrated into the system.
• Design a scalable architecture that supports easy addition of new device types and metrics.

• Real-time data feeds displaying CPU usage, interface throughput, power consumption, system load, device uptime, temperature, failure rates, etc.
• Dynamic, auto-updating graphs and visual indicators showing device health status with color coding (green/yellow/red).
• Configurable dashboards allowing users to personalize metrics and layouts.
• Timestamped historical data views for trend analysis over selected timeframes.
• Threshold-based alerting system to notify users of abnormal performance metrics.
• Notification system for prompt alerts via email, SMS, or internal messaging.
• Drill-down features providing detailed logs and metrics for individual devices.
• Advanced filtering options to isolate specific devices, time periods, or metrics.
• Interactive network topology maps displaying device interconnections geographically and logically.
• Integrated natural language queries enabling users to generate detailed reports and metrics summaries using GPT-based capabilities.

• Network device protocols for seamless data collection (SNMP, REST APIs)
• Messaging infrastructure (NATS or similar) for alert notifications
• Data visualization platforms like Grafana for dashboard rendering
• Natural language processing models (e.g., GPT) for query handling
• Existing IT asset management or inventory systems (if applicable)

• System scalability to support up to thousands of concurrent device data streams
• High availability with 99.9% uptime SLA for dashboards and alerts
• Real-time data processing with minimal latency (target <1 second delay)
• Robust security protocols to protect sensitive network and device data
• Extensible architecture supporting addition of new device types and metrics without significant rework

The implementation of this real-time device health monitoring platform will enable organizations to detect and resolve network issues proactively, reducing unplanned downtime and maintenance costs. Expected outcomes include improved network reliability, faster incident response times, and enhanced operational efficiency, ultimately leading to a more resilient and cost-effective IT infrastructure management.