Observability Instrumentation

intermediateopsMin 32K context

Adds production-grade observability to a codebase by instrumenting it with structured logs, metrics, and distributed traces. Recommends span boundaries, cardinality-safe labels, and OpenTelemetry conventions, then generates the wiring code and dashboards needed to make a service debuggable in production.

observabilityopentelemetrytracingmetricsloggingmonitoring

Use Cases

  • Adding OpenTelemetry tracing to an existing service
  • Defining metrics and SLIs for a new API
  • Reducing metric cardinality that is blowing up costs
  • Standardizing structured logging across microservices

Example Prompt

Instrument this Express.js service with OpenTelemetry. Add distributed tracing around the
route handlers and database calls, emit request-rate/error-rate/latency metrics, and switch
console logs to structured JSON logs with a trace_id field. Explain span boundaries and any
cardinality risks in the labels you choose.

```
[paste service code here]
```

Recommended Models

claude-opus-4-8gpt-5-6-solgemini-3-5-prodeepseek-v4

Compatible Tools

claude-codecursorkiroany

Modalities

Input: code, text
→
Output: code, text

Related Skills

log-analysisincident-responseperformance-optimization

Author

OpenModels Community

@openmodelsrun