Designs chaos experiments, creates failure injection frameworks, and facilitates game day exercises for distributed systems — producing runbooks, experiment manifests, rollback procedures, and post-mortem templates. Use when designing chaos experiments, implementing failure injection frameworks, or

Chaos Engineer When to Use This Skill Designing and executing chaos experiments Implementing failure injection frameworks (Chaos Monkey, Litmus, etc.) Planning and conducting game day exercises Building blast radius controls and safety mechanisms Setting up continuous chaos testing in CI/CD Improving system resilience based on experiment findings Core Workflow 1. System Analysis Map architecture, dependencies, critical paths, and failure modes 2. Experiment Design Define hypothesis, steady state, blast radius, and safety controls 3. Execute Chaos Run controlled experiments with monitoring and quick rollback 4. Learn & Improve Document findings, implement fixes, enhance monitoring 5. Automate Integrate chaos testing into CI/CD for continuous resilience Reference Guide Load detailed guidance based on context: Topic Reference Load When Experiments references/experiment design.md Designing hypothesis, blast radius, rollback Infrastructure references/infrastructure chaos.md Server, network, zone, region failures Kubernetes references/kubernetes chaos.md Pod, node, Litmus, chaos mesh experiments Tools & Automation references/chaos tools.md Chaos Monkey, Gremlin, Pumba, CI/CD integration Game Days references/game days.md Planning, executing, learning from game days Safety Checklist Non obvious constraints that must be enforced on every experiment: Steady state first — define and verify baseline metrics before injecting any failure Blast radius cap — start with the smallest possible impact scope; expand only after validation Automated rollback ≤ 30 seconds — abort path must be scripted and tested before the experiment begins Single variable — change only one failure condition at a time until behaviour is well understood No production without safety nets — customer facing environments require circuit breakers, feature flags, or canary isolation Close the loop — every experiment must produce a written learning summary and at least one tracked improvement Output Templates When implementing chaos engineering, provide: 1. Experiment design document (hypothesis, metrics, blast radius) 2. Implementation code (failure injection scripts/manifests) 3. Monitoring setup and alert configuration 4. Rollback procedures and safety controls 5. Learning summary and improvement recommendations Concrete Example: Pod Failure Experiment (Litmus Chaos) The following shows a complete experiment — from hypothesis to rollback — using Litmus Chaos on Kubernetes. Step 1 — Define steady state and apply the experiment Step 2 — Create and apply a Litmus ChaosEngine manifest Step 3 — Monitor during the experiment Step 4 — Rollback / abort if steady state is violated Concrete Example: Network Latency with toxiproxy Concrete Example: Chaos Monkey (Spinnaker / standalone) [Documentation](https://jeffallan.github.io/claude skills/skills/devops/chaos engineer/)

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