chaos-engineering-resilience

Q: How do I install chaos-engineering-resilience?

Run npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill chaos-engineering-resilience in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/chaos-engineering-resilience/ (personal) or .claude/skills/chaos-engineering-resilience/ (project).

by proffesor-for-testingTesting & QA

Chaos engineering principles, controlled failure injection, resilience testing, and system recovery validation. Use when testing distributed systems, building confidence in fault tolerance, or validating disaster recovery.

Installs: 132
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill chaos-engineering-resilience

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads chaos-engineering-resilience automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Chaos Engineering & Resilience Testing

<default_to_action> When testing system resilience or injecting failures:

DEFINE steady state (normal metrics: error rate, latency, throughput)
HYPOTHESIZE system continues in steady state during failure
INJECT real-world failures (network, instance, disk, CPU)
OBSERVE and measure deviation from steady state
FIX weaknesses discovered, document runbooks, repeat

Quick Chaos Steps:

Start small: Dev → Staging → 1% prod → gradual rollout
Define clear rollback triggers (error_rate > 5%)
Measure blast radius, never exceed planned scope
Document findings → runbooks → improved resilience

Critical Success Factors:

Controlled experiments with automatic rollback
Steady state must be measurable
Start in non-production, graduate to production </default_to_action>

Quick Reference Card

When to Use

Distributed systems validation
Disaster recovery testing
Building confidence in fault tolerance
Pre-production resilience verification

Failure Types to Inject

Category	Failures	Tools
Network	Latency, packet loss, partition	tc, toxiproxy
Infrastructure	Instance kill, disk failure, CPU	Chaos Monkey
Application	Exceptions, slow responses, leaks	Gremlin, LitmusChaos
Dependencies	Service outage, timeout	WireMock

Blast Radius Progression

Dev (safe) → Staging → 1% prod → 10% → 50% → 100%
     ↓           ↓         ↓        ↓
  Learn      Validate   Careful   Full confidence

Steady State Metrics

Metric	Normal	Alert Threshold
Error rate	< 0.1%	> 1%
p99 latency	< 200ms	> 500ms
Throughput	baseline	-20%

Chaos Experiment Structure

// Chaos experiment definition
const experiment = {
  name: 'Database latency injection',
  hypothesis: 'System handles 500ms DB latency gracefully',
  steadyState: {
    errorRate: '< 0.1%',
    p99Latency: '< 300ms'
  },
  method: {
    type: 'network-latency',
    target: 'database',
    delay: '500ms',
    duration: '5m'
  },
  rollback: {
    automatic: true,
    trigger: 'errorRate > 5%'
  }
};

Agent-Driven Chaos

// qe-chaos-engineer runs controlled experiments
await Task("Chaos Experiment", {
  target: 'payment-service',
  failure: 'terminate-random-instance',
  blastRadius: '10%',
  duration: '5m',
  steadyStateHypothesis: {
    metric: 'success-rate',
    threshold: 0.99
  },
  autoRollback: true
}, "qe-chaos-engineer");

// Validates:
// - System recovers automatically
// - Error rate stays within threshold
// - No data loss
// - Alerts triggered appropriately

Agent Coordination Hints

Memory Namespace

aqe/chaos-engineering/
├── experiments/*       - Experiment definitions & results
├── steady-states/*     - Baseline measurements
├── runbooks/*          - Generated recovery procedures
└── blast-radius/*      - Impact analysis

Fleet Coordination

const chaosFleet = await FleetManager.coordinate({
  strategy: 'chaos-engineering',
  agents: [
    'qe-chaos-engineer',          // Experiment execution
    'qe-performance-tester',      // Baseline metrics
    'qe-production-intelligence'  // Production monitoring
  ],
  topology: 'sequential'
});

Related Skills

shift-right-testing - Production testing
performance-testing - Load testing
test-environment-management - Environment stability

Remember

Break things on purpose to prevent unplanned outages. Find weaknesses before users do. Define steady state, inject failures, measure impact, fix weaknesses, create runbooks. Start small, increase blast radius gradually.

With Agents: qe-chaos-engineer automates chaos experiments with blast radius control, automatic rollback, and comprehensive resilience validation. Generates runbooks from experiment results.

FAQ

What does the chaos-engineering-resilience skill do?

How do I install chaos-engineering-resilience?

Run npx skills add https://github.com/proffesor-for-testing/agentic-qe --skill chaos-engineering-resilience in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/chaos-engineering-resilience/ (personal) or .claude/skills/chaos-engineering-resilience/ (project).

Which AI agents can use chaos-engineering-resilience?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is chaos-engineering-resilience safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains chaos-engineering-resilience?

It is published by proffesor-for-testing in proffesor-for-testing/agentic-qe. It has 132 recorded installs.