Chaos Testing Principles
SkillMediaControlled 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.
No other account needed.
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
| Element | Description |
|---|---|
| Target | Which component to perturb |
| Failure mode | What kind of failure (latency, crash, partition) |
| Blast radius | Scope of impact (single instance, AZ, region) |
| Duration | How long the failure persists |
| Abort criteria | When to immediately stop the experiment |
| Rollback plan | How 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
| Type | Examples |
|---|---|
| Process | Kill process, OOM, CPU spike |
| Network | Latency injection, packet loss, partition |
| Infrastructure | Instance termination, AZ failure, disk full |
| Application | Exception injection, slow dependency, config error |
| Data | Corrupt cache, stale data, schema mismatch |
Safety Mechanisms (Non-Negotiable)
- Abort button — immediate experiment termination capability
- Blast radius limits — never affect >5% of production traffic initially
- Time-boxed — experiments have maximum duration
- Monitoring — real-time dashboards during experiments
- Business hours only — no chaos experiments during peak or off-hours
- 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