structured-logging-and-observability
Use this skill when building production services, pipelines, or automation that needs to be debugged, monitored, or audited. Add structured logs, metrics, and health checks before shipping any service.
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- Repository
- aiming-lab/MetaClaw
- Last source activity
- March 10, 2026 at 18:04
- Detected SKILL.md language
- English
- Stars
- 3,464
- Forks
- 453
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- structured-logging-and-observability
- description
- Use this skill when building production services, pipelines, or automation that needs to be debugged, monitored, or audited. Add structured logs, metrics, and health checks before shipping any service.
- category
- automation
# Structured Logging and Observability
**Log levels:**
- `DEBUG`: detailed diagnostic (off in production)
- `INFO`: normal operation milestones
- `WARNING`: recoverable unexpected state
- `ERROR`: operation failed, action needed
**Structured logs (JSON) over free-form text:**
```python
import structlog
log = structlog.get_logger()
log.info("request_complete", method="POST", path="/api/data", status=200, latency_ms=42)
```
**Metrics to expose:** request rate, error rate, latency (p50/p95/p99), queue depth.
**Health check endpoint:** `/health` returning `{"status": "ok"}` — required for load balancers.
**Anti-pattern:** Logging only on error; you can't diagnose what you didn't observe.
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