
Incident Runbook Templates
Low Riskby @sickn33Verified Source
About
Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication.
name: incident-runbook-templates description: "Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication." risk: critical source: community date_added: "2026-02-27"
Incident Runbook Templates
Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication.
Do not use this skill when
- The task is unrelated to incident runbook templates
- You need a different domain or tool outside this scope
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Use this skill when
- Creating incident response procedures
- Building service-specific runbooks
- Establishing escalation paths
- Documenting recovery procedures
- Responding to active incidents
- Onboarding on-call engineers
Core Concepts
1. Incident Severity Levels
| Severity | Impact | Response Time | Example | |----------|--------|---------------|---------| | SEV1 | Complete outage, data loss | 15 min | Production down | | SEV2 | Major degradation | 30 min | Critical feature broken | | SEV3 | Minor impact | 2 hours | Non-critical bug | | SEV4 | Minimal impact | Next business day | Cosmetic issue |
2. Runbook Structure
1. Overview & Impact
2. Detection & Alerts
3. Initial Triage
4. Mitigation Steps
5. Root Cause Investigation
6. Resolution Procedures
7. Verification & Rollback
8. Communication Templates
9. Escalation Matrix
Runbook Templates
Template 1: Service Outage Runbook
# [Service Name] Outage Runbook
## Overview
**Service**: Payment Processing Service
**Owner**: Platform Team
**Slack**: #payments-incidents
**PagerDuty**: payments-oncall
## Impact Assessment
- [ ] Which customers are affected?
- [ ] What percentage of traffic is impacted?
- [ ] Are there financial implications?
- [ ] What's the blast radius?
## Detection
### Alerts
- `payment_error_rate > 5%` (PagerDuty)
- `payment_latency_p99 > 2s` (Slack)
- `payment_success_rate < 95%` (PagerDuty)
### Dashboards
- [Payment Service Dashboard](https://grafana/d/payments)
- [Error Tracking](https://sentry.io/payments)
- [Dependency Status](https://status.stripe.com)
## Initial Triage (First 5 Minutes)
### 1. Assess Scope
```bash
# Check service health
kubectl get pods -n payments -l app=payment-service
# Check recent deployments
kubectl rollout history deployment/payment-service -n payments
# Check error rates
curl -s "http://prometheus:9090/api/v1/query?query=sum(rate(http_requests_total{status=~'5..'}[5m]))"
2. Quick Health Checks
- [ ] Can you reach the service?
curl -I https://api.company.com/payments/health - [ ] Database connectivity? Check connection pool metrics
- [ ] External dependencies? Check Stripe, bank API status
- [ ] Recent changes? Check deploy history
3. Initial Classification
| Symptom | Likely Cause | Go To Section | |---------|--------------|---------------| | All requests failing | Service down | Section 4.1 | | High latency | Database/dependency | Section 4.2 | | Partial failures | Code bug | Section 4.3 | | Spike in errors | Traffic surge | Section 4.4 |
Mitigation Procedures
4.1 Service Completely Down
# Step 1: Check pod status
kubectl get pods -n payments
# Step 2: If pods are crash-looping, check logs
kubectl logs -n payments -l app=payment-service --tail=100
# Step 3: Check recent deployments
kubectl rollout history deployment/payment-service -n payments
# Step 4: ROLLBACK if recent deploy is suspect
kubectl rollout undo deployment/payment-service -n payments
# Step 5: Scale up if resource constrained
kubectl scale deployment/payment-service -n payments --replicas=10
# Step 6: Verify recovery
kubectl rollout status deployment/payment-service -n payments
4.2 High Latency
# Step 1: Check database connections
kubectl exec -n payments deploy/payment-service -- \
curl localhost:8080/metrics | grep db_pool
# Step 2: Check slow queries (if DB issue)
psql -h $DB_HOST -U $DB_USER -c "
SELECT pid, now() - query_start AS duration, query
FROM pg_stat_activity
WHERE state = 'active' AND duration > interval '5 seconds'
ORDER BY duration DESC;"
# Step 3: Kill long-running queries if needed
psql -h $DB_HOST -U $DB_USER -c "SELECT pg_terminate_backend(pid);"
# Step 4: Check external dependency latency
curl -w "@curl-format.txt" -o /dev/null -s https://api.stripe.com/v1/health
# Step 5: Enable circuit breaker if dependency is slow
kubectl set env deployment/payment-service \
STRIPE_CIRCUIT_BREAKER_ENABLED=true -n payments
4.3 Partial Failures (Specific Errors)
# Step 1: Identify error pattern
kubectl logs -n payments -l app=payment-service --tail=500 | \
grep -i error | sort | uniq -c | sort -

