observability-and-instrumentation
Add structured logging, metrics, and tracing so systems are debuggable and operable in production. Use when implementing new services, adding important features, or improving production readiness.
- License 许可
- MIT
- 最近更新
- 2026-07-22
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- observability-and-instrumentation
- description
- Add structured logging, metrics, and tracing so systems are debuggable and operable in production. Use when implementing new services, adding important features, or improving production readiness.
03 SKILL.md 正文
Observability and Instrumentation
Overview
If you cannot observe it, you cannot operate it. Instrument as you build, not as an afterthought.
When to Use
- Building new services or major features
- Preparing for production
- Investigating production issues (to improve future signal)
- Defining SLOs or alerts
Core Practices
Logging
- Structured (JSON) preferred
- Include request/correlation IDs
- Log at appropriate levels
- Avoid logging secrets or high-cardinality sensitive data
Metrics
- RED (Rate, Errors, Duration) for services
- USE (Utilization, Saturation, Errors) for resources
- Business metrics where they aid decisions
Tracing
- Propagate context across service boundaries
- Focus on critical paths first
Alerting
- Alert on symptoms (user-impacting) more than causes
- Make alerts actionable
- Avoid noisy alerts that train people to ignore them
Checklist
- [ ] Key operations have timing and error metrics
- [ ] Logs allow tracing a request across components
- [ ] Dashboards exist for the golden signals
- [ ] Alerts are defined for true pain points
Verification
- You can answer “is it working?” and “why is it slow/failing?” from the instrumentation
- New code paths are not invisible in production
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