Platform Incident Response & Troubleshooting Automation
Automate incident triage and root cause analysis from observability data
What You Can Do
Feed your logs, metrics, and traces into Claude to automatically detect anomalies, correlate alerts, and identify root causes in distributed systems. This skill generates step-by-step remediation procedures, prioritizes incidents by severity, and creates incident reports—compressing hours of manual triage into minutes.
Features
Parse structured and unstructured logs to spot error patterns, latency spikes, and unusual behavior
Correlate symptoms across logs, metrics, and traces to pinpoint the failing component or configuration
Determine CRITICAL/HIGH/MEDIUM/LOW classification and map affected services
Generate step-by-step recovery procedures tailored to the incident type
Group related alerts and suppress known false positives to focus on real issues
Identify downstream impact when a dependency fails (e.g., payment service down → checkout broken)
Build chronological incident narratives from distributed traces and timestamps
Create post-incident verification steps to confirm resolution
Example Output
Example 1: Root Cause Analysis
INCIDENT: Database connection pool exhaustion
DETECTED: 2026-07-31 14:23 UTC
ROOT CAUSE: Scheduled backup query at 14:20 UTC opened 100+ connections without cleanup, exhausting the 150-connection pool
IMPACT: All backend services lost database access; 15-minute outage affecting 10K+ users
SEVERITY: CRITICAL
Example 2: Remediation Steps
- ✓ Identify the backup job consuming connections (
SELECT * FROM pg_stat_activity WHERE state='idle') - ✓ Terminate stale connections:
SELECT pg_terminate_backend(pid) WHERE state='idle' - ✓ Restart connection pooler (PgBouncer) to reset state
- ✓ Verify pool recovery: check active connections drop below 50
- ✓ Monitor for 5 minutes; declare recovered when response times normalize
Example 3: Impact Timeline
- 14:20 — Backup job starts, opens 100 connections
- 14:23 — Connection pool exhausted; app connection attempts fail
- 14:23–14:28 — Service degradation; customers see timeouts
- 14:28 — On-call engineer restarts pooler
- 14:30 — Connections normalized; service restored
What's Included
- SKILL.md: Complete incident response workflow with decision trees for triage, root cause analysis, and remediation
- Log analysis template: Standardized format for parsing logs from Datadog, CloudWatch, ELK, Prometheus, and similar platforms
- Remediation runbook template: Structured format for step-by-step recovery procedures with verification steps
- Incident report template: Post-incident summary including root cause, timeline, impact, and prevention measures
- Alert correlation checklist: Guidelines for grouping related alerts and suppressing noise
- Root cause decision tree: Flowchart to guide investigators through common failure modes and investigation paths
Who It's For
- SRE/Platform engineers — Reduce MTTR by automating triage and root cause analysis during on-call hours
- DevOps engineers — Quickly generate runbooks when paged to unstick customers
- On-call incident responders — Get immediate guidance during off-hours outages and production issues
- Operations managers — Understand incident severity and user impact to communicate with stakeholders
- Infrastructure engineers — Document failure modes and prevention measures for operational runbooks
Best For
- Incident severity assessment — Classify CRITICAL/HIGH/MEDIUM/LOW and determine blast radius in seconds
- Root cause analysis (RCA) — Correlate logs and metrics to move from symptom (high latency) to cause (connection pool exhaustion)
- Performance degradation investigation — Pinpoint the service, endpoint, or query causing slowness
- Automated runbook generation — Transform incident learnings into recovery procedures for the next occurrence
- Alert noise reduction — Group and suppress correlated alerts so you focus on genuine critical issues
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