Network Monitoring & Observability

This demo shows the kind of KPI view operations teams actually use when they are trying to decide whether something is noise, congestion, or the start of a real incident. The four charts track one interface across seven days: Service Quality, Utilization, Packet Loss, and Error Ratio. Service Quality is a simple derived metric for this example, calculated as 100 - (5 x packet loss), to show how raw counters can be rolled into one score that is easier to read quickly. Hover to inspect exact values, or click a chart to pin one timestamp across all four panels.

Note: This is a small-scale demo, with one interface standing in for the much larger fleets these views usually represent. In production, threshold values and KPI correlations are not arbitrary: they are determined through analysis of historical data, traffic baselines, and fault correlation studies before any alarming logic is deployed. Getting those thresholds right is the real analysis and calibration work.

At scale, with hundreds of interfaces across dozens of sites, manual "eyes on glass" monitoring is not viable. These thresholds drive automated alarming and ticketing pipelines: a threshold breach raises an alarm, a correlation engine groups related events, and a ticket is opened automatically with enriched context (site, device, interface, severity, duration). The engineer receives a ticket, not a page of raw charts.