| name | chaos-engineering |
| description | Chaos Engineering is the discipline of experimenting on a system to Use when this capability is needed. |
| metadata | {"author":"amnadtaowsoam"} |
Chaos Engineering
Skill Profile
(Select at least one profile to enable specific modules)
Overview
Chaos Engineering is the discipline of experimenting on a system to build confidence in its capability to withstand turbulent conditions in production. By proactively injecting failures, you discover weaknesses before they cause outages.
Core Principle: "Break things on purpose to learn how to make them stronger."
Why This Matters
- Proactive Discovery: Find weaknesses before customers do
- Confidence Building: Verify that resilience patterns actually work
- Cultural Shift: Normalizes failure as expected, not exceptional
- Reduced MTTR: Practice recovery procedures under controlled conditions
- Better Architecture: Forces design for failure from the start
Core Concepts & Rules
1. Core Principles
- Follow established patterns and conventions
- Maintain consistency across codebase
- Document decisions and trade-offs
2. Implementation Guidelines
- Start with the simplest viable solution
- Iterate based on feedback and requirements
- Test thoroughly before deployment
Inputs / Outputs / Contracts
- Inputs:
- System architecture and component mapping
- Steady state metrics (baseline)
- Hypothesis to test
- Blast radius configuration
- Entry Conditions:
- System is in production with real traffic
- Monitoring and alerting are operational
- Rollback mechanisms are documented and tested
- Outputs:
- Experiment report with findings
- Updated monitoring dashboards
- Action items for system improvements
- Artifacts Required (Deliverables):
- Experiment documentation (hypothesis, results, findings)
- Metrics before/during/after experiment
- Screenshots/graphs of system behavior
- Acceptance Evidence:
- Test Report (screenshot/log)
- Benchmark Result (latency, error rate)
- Security Scan Report (if applicable)
- Success Criteria:
- Hypothesis validated or disproven with data
- System recovered to steady state within defined timeframe
- No customer impact exceeding blast radius
Skill Composition
- Depends on: Failure Modes Analysis (40-system-resilience/failure-modes)
- Compatible with: Postmortem Analysis, Monitoring & Observability
- Conflicts with: Production systems without monitoring/rollback capabilities
- Related Skills:
Quick Start / Implementation Example
- Review requirements and constraints
- Set up development environment
- Implement core functionality following patterns
- Write tests for critical paths
- Run tests and fix issues
- Document any deviations or decisions
def example_function():
pass
Assumptions / Constraints / Non-goals
- Assumptions:
- Development environment is properly configured
- Required dependencies are available
- Team has basic understanding of domain
- Constraints:
- Must follow existing codebase conventions
- Time and resource limitations
- Compatibility requirements
- Non-goals:
- This skill does not cover edge cases outside scope
- Not a replacement for formal training
Compatibility & Prerequisites
- Supported Versions:
- Python 3.8+
- Node.js 16+
- Modern browsers (Chrome, Firefox, Safari, Edge)
- Required AI Tools:
- Code editor (VS Code recommended)
- Testing framework appropriate for language
- Version control (Git)
- Dependencies:
- Language-specific package manager
- Build tools
- Testing libraries
- Environment Setup:
.env.example keys: API_KEY, DATABASE_URL (no values)
Test Scenario Matrix (QA Strategy)
| Type | Focus Area | Required Scenarios / Mocks |
|---|
| Unit | Core Logic | Must cover primary logic and at least 3 edge/error cases. Target minimum 80% coverage |
| Integration | DB / API | All external API calls or database connections must be mocked during unit tests |
| E2E | User Journey | Critical user flows to test |
| Performance | Latency / Load | Benchmark requirements |
| Security | Vuln / Auth | SAST/DAST or dependency audit |
| Frontend | UX / A11y | Accessibility checklist (WCAG), Performance Budget (Lighthouse score) |
Technical Guardrails & Security Threat Model
1. Security & Privacy (Threat Model)
- Top Threats: Injection attacks, authentication bypass, data exposure
2. Performance & Resources
3. Architecture & Scalability
4. Observability & Reliability
Agent Directives & Error Recovery
(ข้อกำหนดสำหรับ AI Agent ในการคิดและแก้ปัญหาเมื่อเกิดข้อผิดพลาด)
- Thinking Process: Analyze root cause before fixing. Do not brute-force.
- Fallback Strategy: Stop after 3 failed test attempts. Output root cause and ask for human intervention/clarification.
- Self-Review: Check against Guardrails & Anti-patterns before finalizing.
- Output Constraints: Output ONLY the modified code block. Do not explain unless asked.
Definition of Done (DoD) Checklist
Anti-patterns / Pitfalls
- ⛔ Don't: Log PII, catch-all exception, N+1 queries
- ⚠️ Watch out for: Common symptoms and quick fixes
- 💡 Instead: Use proper error handling, pagination, and logging
Reference Links & Examples
- Internal documentation and examples
- Official documentation and best practices
- Community resources and discussions
Versioning & Changelog
- Version: 1.0.0
- Changelog:
- 2026-02-22: Initial version with complete template structure
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