wshobson/agents

incident-runbook-templates

Create structured incident response runbooks with step-by-step procedures, escalation paths, and recovery actions.

Quelltext ansehen
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Incident Runbook Templates

Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication.

When to Use This Skill

  • 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

SeverityImpactResponse TimeExample
SEV1Complete outage, data loss15 minProduction down
SEV2Major degradation30 minCritical feature broken
SEV3Minor impact2 hoursNon-critical bug
SEV4Minimal impactNext business dayCosmetic 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

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Best Practices

Do's

  • Keep runbooks updated - Review after every incident
  • Test runbooks regularly - Game days, chaos engineering
  • Include rollback steps - Always have an escape hatch
  • Document assumptions - What must be true for steps to work
  • Link to dashboards - Quick access during stress

Don'ts

  • Don't assume knowledge - Write for 3 AM brain
  • Don't skip verification - Confirm each step worked
  • Don't forget communication - Keep stakeholders informed
  • Don't work alone - Escalate early
  • Don't skip postmortems - Learn from every incident

Troubleshooting

Runbook steps work in staging but fail during a real incident

Steps often assume preconditions that are true in a healthy environment but not during an outage. For each command in your runbook, add a prerequisite check and a "what to do if this command fails" note:

bash
# Step: Check pod status
kubectl get pods -n payments

# Prerequisites: kubectl configured, kubeconfig points to correct cluster
# If this fails: run `aws eks update-kubeconfig --name prod-cluster --region us-east-1`
# Expected output: pods in Running state

On-call engineer panics and skips steps out of order

Add a numbered checklist at the top of the runbook that mirrors the section numbers, so responders can track progress under stress without reading the full document:

markdown
## Quick Checklist
- [ ] 1. Declare incident severity and open war room
- [ ] 2. Check service health (Section 4.1)
- [ ] 3. Check recent deployments (Section 4.1)
- [ ] 4. Roll back if deploy is suspect (Section 4.1)
- [ ] 5. Post initial notification to #payments-incidents
- [ ] 6. Escalate if > 15 min unresolved

Runbook is outdated — commands reference old cluster names or endpoints

Runbooks rot because they're updated manually. Include a "Last Verified" date and owner at the top, and add a CI check that validates all curl endpoints and kubectl context names are still valid:

markdown
## Runbook Metadata
| Field | Value |
|---|---|
| Last verified | 2024-11-15 |
| Owner | @platform-team |
| Review cadence | After every SEV1/SEV2 |

Stakeholder communication is delayed while engineers are heads-down

Assign a dedicated incident communicator role (separate from the incident commander) whose only job is to post status updates. Add a standing agenda in the communication template:

Update every 15 minutes (even if no new information):
- Current status (Investigating / Mitigating / Monitoring)
- Impact (what is broken, who is affected, % of traffic)
- What we are doing right now
- Next update in: 15 minutes

Database runbook commands cause additional downtime when run incorrectly

Add explicit warnings before destructive SQL commands and require a dry-run output check before executing:

sql
-- WARNING: This terminates active connections. Verify count first.
-- DRY RUN (check count before terminating):
SELECT count(*) FROM pg_stat_activity WHERE state = 'idle' AND query_start < now() - interval '10 minutes';

-- EXECUTE only after verifying count is reasonable (< 50):
SELECT pg_terminate_backend(pid) FROM pg_stat_activity
WHERE state = 'idle' AND query_start < now() - interval '10 minutes';

Related Skills

  • postmortem-writing - After resolving an incident, use postmortem templates to capture root cause and preventive actions
  • on-call-handoff-patterns - Structure shift handoffs so the incoming responder has full context on active incidents
aus demselben Repository

Weitere Skills

Alle Skills
wshobson
Community

typescript-advanced-types

Master TypeScript's advanced type system including generics, conditional types, mapped types, template literals, and utility types for building type-safe applications. Use when implementing complex type logic, creating reusable type utilities, or ensuring compile-time type safety in TypeScript projects.

Installationen
71.994
GitHub Stars
39.482
Aktualisiert
7. Sept.
wshobson
Community

tailwind-design-system

Build scalable design systems with Tailwind CSS v4, design tokens, component libraries, and responsive patterns. Use when creating component libraries, implementing design systems, or standardizing UI patterns.

Installationen
62.923
GitHub Stars
39.482
Aktualisiert
7. Sept.
wshobson
Community

nodejs-backend-patterns

Build production-ready Node.js backend services with Express/Fastify, implementing middleware patterns, error handling, authentication, database integration, and API design best practices. Use when creating Node.js servers, REST APIs, GraphQL backends, or microservices architectures.

Installationen
44.659
GitHub Stars
39.482
Aktualisiert
7. Sept.
wshobson
Community

kpi-dashboard-design

Design effective KPI dashboards with metrics selection, visualization best practices, and real-time monitoring patterns. Use this skill when building an executive SaaS metrics dashboard tracking MRR, churn, and LTV/CAC ratios; designing an operations center with live service health and request throughput; creating a cohort retention analysis view for a product team; or debugging a dashboard where metrics contradict each other due to inconsistent calculation methodology.

Installationen
4
GitHub Stars
39.481
Aktualisiert
7. Sept.