Test system resilience by simulating failures.
Chaos Engineering Practitioner
Chaos Monkey, LitmusChaos, Kubernetes
Best for
- ▸Design steady-state hypothesis validation for microservices during peak traffic periods
- ▸Execute controlled failure injection experiments on Kubernetes clusters with automatic rollback
- ▸Plan game day exercises to test incident response capabilities across distributed systems
- ▸Implement blast radius controls for chaos experiments in production environments
What you'll get
- ▸Scientific experiment design with measurable steady-state metrics, controlled fault injection plan, automated observation dashboards, and safety rollback procedures
- ▸Game day runbook with pre-experiment checklist, failure scenarios, team roles, communication protocols, and post-experiment analysis framework
- ▸Organizational chaos engineering maturity assessment with readiness criteria, experiment progression roadmap, and success metrics definition
System architecture details, monitoring capabilities, incident response maturity, and specific reliability concerns to validate through controlled failure injection.
Scientifically structured chaos experiments with hypothesis formulation, blast radius controls, measurement plans, and automated rollback strategies.
What's inside
“You are a Chaos Engineering Practitioner. You design, plan, and execute chaos experiments to proactively discover system weaknesses before they cause production incidents. - **Scientific hypothesis-driven testing**, not random breaking. Every experiment starts with a measurable steady-state hypothes...”
Covers
Not designed for ↓
- ×Breaking production systems without controlled recovery mechanisms
- ×Load testing or performance benchmarking without failure injection
- ×General monitoring and observability setup without chaos validation
- ×Security penetration testing or vulnerability assessment
SupaScore
89.03▼
Evidence Policy
Standard: no explicit evidence policy.
Research Foundation: 8 sources (3 books, 1 industry frameworks, 3 official docs, 1 web)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
v5.5 distilled from v2 via Claude Sonnet
Pipeline v4: rebuilt with 3 helper skills
Initial release
Prerequisites
Use these skills first for best results.
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Production Resilience Validation
Establish baseline observability, execute controlled chaos experiments, then analyze results to improve system resilience and incident response capabilities
© 2026 Kill The Dragon GmbH. This skill and its system prompt are protected by copyright. Unauthorised redistribution is prohibited. Terms of Service · Legal Notice