Agent skill · operations · jeremylongshore
running-chaos-tests
Execute chaos engineering experiments to test system resilience.
Why this skill is useful
Provides specific chaos engineering methodologies and YAML/JSON definitions for experiments that the AI wouldn't reliably generate on its own.
What it needs
Requires chaos-mesh, litmus, pumba, toxiproxy installed locally. About 4k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Chaos Engineering Toolkit Overview Execute controlled chaos engineering experiments to test system resilience, fault tolerance, and recovery capabilities. Injects failures including network latency, service crashes, resource exhaustion, and dependency outages to verify that systems degrade gracefully and recover automatically. Prerequisites Distributed system or microservice architecture deployed in a staging/test environment Monitoring and alerting configured (Grafana, Datadog, CloudWatch, or Prometheus) Rollback capability for the target environment (manual or automated) Chaos engineering tool installed (toxiproxy, Pumba, Litmus, or Chaos Mesh) Explicit approval from the team to run chaos experiments Steady-state hypothesis defined (what "healthy" looks like in metrics) Instructions 1. Define the steady-state hypothesis: Identify measurable indicators of normal system behavior (e.g., p99 latency < 500ms, error rate < 0.1%, all health checks pass). Record baseline metrics before injecting any failures. Define the blast radius -- which services and users are affected by the experiment. 2. Design chaos experiments by category: Network: Inject latency (200-2000ms), packet loss (5-50%), DNS failure, connection timeout. Process: Kill a service instance, exhaust CPU or memory, fill disk. Dependency: Block access to database, cache, or external API. State: Corrupt data, introduce clock skew, simulate split-brain scenarios. 3. Start with minimal impact and increase gradually: Begin with read-only experiments (network latency on non-critical path). Progress to service-level failures (kill one instance of a multi-instance service). Only move to data-level chaos after infrastructure chaos is validated. 4. Execute each experiment with safeguards: Set a maximum experiment duration (5-15 minutes). Configure automatic rollback triggers (error rate > 5% triggers abort). Monitor system metrics in real-time during the experiment. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/running-chaos-tests