QE Chaos Resilience

SkillDev tools

Injects controlled faults (network partition, latency, process kill, disk pressure) into distributed systems and validates recovery behavior. Use when testing circuit breakers, failover paths, retry logic, or building confidence in system resilience through chaos engineering.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the QE Chaos Resilience skill

What this skill tells your AI

The instructions your AI receives, as published by proffesor-for-testing/agentic-qe in .claude/skills/qe-chaos-resilience/SKILL.md and read by ahel’s review.

Purpose

Guide the use of v3's chaos engineering capabilities including controlled fault injection, load/stress testing, resilience validation, and disaster recovery testing.

Activation

  • When testing system resilience
  • When performing chaos experiments
  • When load/stress testing
  • When validating disaster recovery
  • When testing circuit breakers

Quick Start

# Run chaos experiment
aqe chaos run --experiment network-latency --target api-service

# Load test
aqe chaos load --scenario peak-traffic --duration 30m

# Stress test to breaking point
aqe chaos stress --endpoint /api/users --max-users 10000

# Test circuit breaker
aqe chaos circuit-breaker --service payment-service

Agent Workflow

// Chaos experiment
Task("Run chaos experiment", `
  Execute controlled chaos on api-service:
  - Inject 500ms network latency
  - Monitor service health metrics
  - Verify circuit breaker activation
  - Measure recovery time
  - Document findings
`, "qe-chaos-engineer")

// Load testing
Task("Performance load test", `
  Run load test simulating Black Friday traffic:
  - Ramp up to 10,000 concurrent users
  - Maintain load for 30 minutes
  - Monitor response times and error rates
  - Identify bottlenecks
  - Compare against SLAs
`, "qe-load-tester")

Chaos Experiments

1. Fault Injection

await chaosEngineer.injectFault({
  target: 'api-service',
  fault: {
    type: 'latency',
    parameters: {
      delay: '500ms',
      jitter: '100ms',
      percentage: 50
    }
  },
  duration: '5m',
  monitoring: {
    metrics: ['response_time', 'error_rate', 'throughput'],
    alerts: true
  },
  rollback: {
    automatic: true,
    trigger: 'error_rate > 10%'
  }
});

2. Load Testing

await loadTester.execute({
  scenario: 'peak-traffic',
  profile: {
    rampUp: '5m',
    steadyState: '30m',
    rampDown: '5m'
  },
  users: {
    initial: 100,
    target: 5000,
    pattern: 'linear'
  },
  assertions: {
    p95_latency: '<500ms',
    error_rate: '<1%',
    throughput: '>1000rps'
  }
});

3. Stress Testing

await loadTester.stressTest({
  endpoint: '/api/checkout',
  strategy: 'step-increase',
  steps: [100, 500, 1000, 2000, 5000],
  stepDuration: '5m',
  findBreakingPoint: true,
  monitoring: {
    resourceUtilization: true,
    databaseConnections: true,
    memoryUsage: true
  }
});

4. Resilience Validation

await resilienceTester.validate({
  scenarios: [
    'database-failover',
    'cache-failure',
    'external-service-timeout',
    'pod-termination'
  ],
  expectations: {
    gracefulDegradation: true,
    automaticRecovery: true,
    dataIntegrity: true,
    recoveryTime: '<30s'
  }
});

Fault Types

FaultDescriptionUse Case
LatencyAdd network delayTest timeouts
Packet LossDrop network packetsTest retry logic
CPU StressConsume CPUTest resource limits
Memory PressureConsume memoryTest OOM handling
Disk FullFill disk spaceTest disk errors
Process KillTerminate processTest recovery

Chaos Report

interface ChaosReport {
  experiment: {
    name: string;
    target: string;
    fault: FaultConfig;
    duration: number;
  };
  results: {
    hypothesis: string;
    validated: boolean;
    metrics: {
      before: MetricSnapshot;
      during: MetricSnapshot;
      after: MetricSnapshot;
    };
    events: ChaosEvent[];
    recovery: {
      detected: boolean;
      time: number;
      automatic: boolean;
    };
  };
  findings: {
    severity: 'critical' | 'high' | 'medium' | 'low';
    description: string;
    recommendation: string;
  }[];
  artifacts: {
    logs: string;
    metrics: string;
    traces: string;
  };
}

Safety Controls

safety:
  blast_radius:
    max_affected_pods: 1
    max_affected_percentage: 10

  abort_conditions:
    - error_rate > 50%
    - p99_latency > 10s
    - service_unavailable

  excluded_environments:
    - production-critical

  required_approvals:
    production: 2
    staging: 0

SLA Validation

await resilienceTester.validateSLA({
  slas: {
    availability: 99.9,
    p95_latency: 500,
    error_rate: 0.1
  },
  period: '30d',
  report: {
    breaches: true,
    trends: true,
    projections: true
  }
});

Coordination

Primary Agents: qe-chaos-engineer, qe-load-tester, qe-resilience-tester Coordinator: qe-chaos-coordinator Related Skills: qe-performance, security-testing

Signals

GitHub stars
475
Forks
91
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
qe-chaos-resilience
Source
github.com/proffesor-for-testing/agentic-qe