Predicting a Database Crash Before It Happens

Use Case 01

PostgreSQL cluster. CPU at 62%, memory at 72%. No alerts firing. On-call team sees nothing wrong.

What's Actually Happening (Without ITOM)

Over 6 days: connection pool crept from 68% → 91%. Write latency drifted 4ms → 47ms. An analytics query held row locks. No individual metric breached a threshold.

What ITOM Does — Step by Step

1. Ingests time-series data across CPU, memory, connection pool, lock wait time, and write latency simultaneously
2. Computes composite health score — detects trajectory convergence toward failure even when no single metric alerts
3. Identifies offending query via session analysis: Session ID 48291 holding row-level locks
4. Fires predictive alert: connection pool exhaustion predicted in ~14 hours

ITOM Alert Output

> ITOM Alert: DB-PROD-CLUSTER-01
> Anomaly: Connection pool 91% (+23% over 6d)
> Write latency deviation: 3.4σ above 30d baseline
> Probable cause: Long-running query — Session ID 48291
> Estimated time to failure: ~14 hours

Without ITOM vs. With ITOM

Without ITOM: Database crashes at 2 AM. War room for 4+ hours.

With ITOM: DBA terminates query. Write latency normalizes in 30 min. No outage.

Key Metrics

• 6 days — Silent degradation
• 3.4σ — Latency deviation detected
• ~14h — Warning before crash
• 0 min — Downtime