Use when performing chaos engineering incident drill — planned failure injection exercise framework with observation checklists, hypothesis definition, blast radius controls, rollback procedures, and post-drill analysis. Guides teams through designing, executing, and learning from controlled chaos experiments to validate incident response readiness and system resilience.
Scanned 9/8/2026
Install to Claude Code
npx -y skills add cloudthinker-ai/CloudSkills --skill chaos-engineering-incident-drill --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: chaos-engineering-incident-drill
enabled: true
description: |
Use when performing chaos engineering incident drill — planned failure
injection exercise framework with observation checklists, hypothesis
definition, blast radius controls, rollback procedures, and post-drill
analysis. Guides teams through designing, executing, and learning from
controlled chaos experiments to validate incident response readiness and
system resilience.
required_connections:
- prefix: slack
label: "Slack (for drill coordination)"
config_fields:
- key: drill_name
label: "Drill Name"
required: true
placeholder: "e.g., Database failover drill"
- key: target_service
label: "Target Service/System"
required: true
placeholder: "e.g., payment-api, Redis cluster"
- key: drill_date
label: "Scheduled Date"
required: true
placeholder: "e.g., 2024-02-15 14:00 UTC"
- key: environment
label: "Target Environment"
required: false
placeholder: "e.g., staging, production-canary"
features:
- INCIDENT
---
# Chaos Engineering Incident Drill
Drill: **{{ drill_name }}**
Target: **{{ target_service }}** | Environment: **{{ environment }}**
Scheduled: **{{ drill_date }}**
## Pre-Drill Planning
### Hypothesis
Define what you expect to happen:
> **Hypothesis:** When [failure injection], we expect [expected behavior]. The system should [recover/failover/degrade gracefully] within [time threshold] and monitoring should detect the issue within [detection threshold].
### Blast Radius Controls
- [ ] Drill is scoped to a single service / availability zone / percentage of traffic
- [ ] Kill switch is prepared and tested (how to stop the experiment instantly)
- [ ] Affected downstream services identified and owners notified
- [ ] Customer impact assessment completed (expected: none / minimal / controlled)
- [ ] Rollback procedure documented and ready
### Prerequisites Checklist
- [ ] Stakeholders notified (engineering, SRE, support, management)
- [ ] On-call team aware and standing by
- [ ] Monitoring dashboards open and shared
- [ ] Baseline metrics captured (latency, error rate, throughput)
- [ ] Experiment tooling tested (Chaos Monkey, Litmus, Gremlin, etc.)
- [ ] Incident channel created for drill coordination
- [ ] No conflicting deployments or maintenance windows
- [ ] Runbooks for the target service reviewed
### Abort Criteria
Stop the experiment immediately if:
- [ ] Customer impact exceeds expected threshold
- [ ] Error rates exceed ___% for more than ___ minutes
- [ ] Cascading failures detected beyond target blast radius
- [ ] Recovery does not begin within ___ minutes
- [ ] A real incident is declared during the drill
## Experiment Design
### Failure Injection Scenarios
| Scenario | Injection Method | Expected Behavior | Duration |
|----------|-----------------|-------------------|----------|
| _e.g., Kill primary DB_ | _terminate instance_ | _failover to replica_ | _5 min_ |
| _e.g., Network partition_ | _block traffic on port_ | _circuit breaker activates_ | _3 min_ |
| _e.g., CPU saturation_ | _stress-ng 100% CPU_ | _autoscaling triggers_ | _10 min_ |
### Observation Points
| What to Observe | Dashboard/Tool | Baseline Value | Threshold |
|----------------|---------------|---------------|-----------|
| Error rate | _Grafana/Datadog_ | _< 0.1%_ | _> 1%_ |
| Latency p99 | _APM tool_ | _200ms_ | _> 2000ms_ |
| Alert firing | _PagerDuty_ | _none_ | _within 5 min_ |
| Auto-recovery | _K8s/ASG_ | _N/A_ | _within 10 min_ |
## Drill Execution
### Phase 1: Baseline (T-10 min)
- [ ] Capture baseline metrics screenshot
- [ ] Confirm all monitoring is green
- [ ] Announce drill start in incident channel
- [ ] Confirm kill switch operator is ready
### Phase 2: Injection (T=0)
- [ ] Execute failure injection
- [ ] Start timer
- [ ] Begin observation log
### Phase 3: Observation (T+0 to T+N)
**Observation Log:**
| Time | Observation | Expected? | Notes |
|------|-------------|-----------|-------|
| T+0 | _injection executed_ | _yes_ | — |
| T+1m | _what happened_ | _yes/no_ | — |
| T+5m | _what happened_ | _yes/no_ | — |
### Phase 4: Recovery (after injection ends or abort)
- [ ] Stop failure injection / activate kill switch
- [ ] Monitor recovery metrics
- [ ] Record time to recovery
- [ ] Verify service returns to baseline
### Phase 5: Wrap-Up
- [ ] Announce drill complete in incident channel
- [ ] Capture post-drill metrics screenshot
## Post-Drill Analysis
### Results Summary
| Aspect | Expected | Actual | Pass/Fail |
|--------|----------|--------|-----------|
| Detection time | _X min_ | _Y min_ | _pass/fail_ |
| Alert fired correctly | _yes_ | _yes/no_ | _pass/fail_ |
| Auto-recovery worked | _yes_ | _yes/no_ | _pass/fail_ |
| Recovery time | _X min_ | _Y min_ | _pass/fail_ |
| Customer impact | _none_ | _none/minimal_ | _pass/fail_ |
| Blast radius contained | _yes_ | _yes/no_ | _pass/fail_ |
### Hypothesis Validation
- **Confirmed / Partially Confirmed / Refuted**
- Key findings: ___
### Findings and Action Items
| Finding | Severity | Action Item | Owner | Ticket |
|---------|----------|-------------|-------|--------|
| _finding_ | _high/med/low_ | _action_ | _name_ | _link_ |
### Recommendations for Next Drill
- Suggested next experiment: ___
- Environment upgrade needed: ___
- Tooling improvements: ___
## Counter-Rationalizations
| Shortcut | Counter | Why |
|----------|---------|-----|
| "We can skip some steps for this case" | Adapt the workflow steps, don't skip them | Skipped steps are where incidents and oversights originate |
| "The user seems to already know what to do" | Complete all workflow phases with the user | The workflow catches blind spots that experience alone misses |
| "This is a minor case, full process is overkill" | Scale the process down, don't turn it off | Minor cases become major when unstructured; the process scales, not disappears |
| "I'll fill in the details later" | Complete each section before moving on | Deferred details are forgotten; real-time capture is more accurate |
| "The template output isn't necessary" | Always produce the structured output format | Structured output enables comparison, audit trails, and handoff to other teams |
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