Chaos Testing Principles

SkillMedia

Controlled failure injection: hypothesis design, blast radius control, safety mechanisms, game day planning, and resilience verification.

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 Chaos Testing Principles skill

What this skill tells your AI

The instructions your AI receives, as published by irahardianto/awesome-agv in .agents/skills/chaos-testing/SKILL.md and read by ahel’s review.

Controlled failure injection to build confidence in system resilience.

When to Invoke

  • Verifying system resilience before production deployment
  • Designing game day exercises
  • Testing circuit breakers, retries, and failover
  • Validating disaster recovery plans

Methodology

1. Define Steady State

Identify measurable indicators of normal system behavior:

  • Request success rate ≥ 99.9%
  • P99 latency < 500ms
  • Error rate < 0.1%

2. Form Hypothesis

"When [failure condition], the system will [expected behavior] because [mechanism]."

Example: "When database primary fails, the system will failover to replica within 30s because of automatic failover configuration."

3. Design Experiment

ElementDescription
TargetWhich component to perturb
Failure modeWhat kind of failure (latency, crash, partition)
Blast radiusScope of impact (single instance, AZ, region)
DurationHow long the failure persists
Abort criteriaWhen to immediately stop the experiment
Rollback planHow to restore normal operation

4. Execute

  • Start with smallest blast radius
  • Monitor continuously during experiment
  • Have rollback ready at all times
  • Stop immediately if abort criteria met

5. Analyze & Learn

  • Did system behave as hypothesized?
  • What broke unexpectedly?
  • What recovery mechanisms worked/failed?
  • Document findings and action items

Failure Injection Types

TypeExamples
ProcessKill process, OOM, CPU spike
NetworkLatency injection, packet loss, partition
InfrastructureInstance termination, AZ failure, disk full
ApplicationException injection, slow dependency, config error
DataCorrupt cache, stale data, schema mismatch

Safety Mechanisms (Non-Negotiable)

  1. Abort button — immediate experiment termination capability
  2. Blast radius limits — never affect >5% of production traffic initially
  3. Time-boxed — experiments have maximum duration
  4. Monitoring — real-time dashboards during experiments
  5. Business hours only — no chaos experiments during peak or off-hours
  6. Stakeholder communication — relevant teams informed before experiments

Game Day Planning

Checklist

  • Hypothesis documented
  • Blast radius defined and limited
  • Abort criteria specified
  • Rollback plan verified
  • Monitoring dashboards ready
  • Communication channel open
  • All participants briefed
  • No conflicting deployments scheduled

Related

  • Monitoring and Alerting Principles @.agents/rules/monitoring-and-alerting-principles.md
  • Incident Response @.agents/skills/incident-response/SKILL.md
  • Error Handling Principles .agents/rules/error-handling-principles.md

Signals

GitHub stars
156
Forks
53
Last commit
Aug 2026
Advanced
Catalog kind
skill
Gateway key
chaos-testing
Source
github.com/irahardianto/awesome-agv