Nova's Correlation Engine uses AI to analyze alerts from every monitoring source in real time, automatically grouping related signals into a single actionable incident. No more alert storms, no more duplicate tickets, no more wasted triage cycles.
When a Kubernetes pod crashes, the correlation engine simultaneously ingests the OOMKill event, error log spikes, failed health checks, and upstream latency anomalies. Instead of four separate tickets landing on four different engineers, Nova fuses them into a single incident with full causal context attached. Your team sees one notification with everything they need.
Basic correlation tools group alerts that fire within the same window. Nova goes deeper: it analyzes semantic similarity between alert messages, checks service ownership overlaps, and applies ML models trained on your incident history to determine whether alerts are truly related. A CPU spike on service A and a timeout on service B only get grouped if there's an actual dependency chain connecting them.
The correlation dashboard visualizes the grouping process live. As new alerts arrive, you see them snap into existing incident clusters or seed new ones. Each cluster shows its constituent signals, confidence score, and suggested severity. When correlation confidence drops below your threshold, Nova flags it for human review instead of auto-grouping, keeping false merges at zero.
See how Nova correlates thousands of signals into actionable incidents in under 30 seconds with zero false groups.