Useful telemetry answers operational questions quickly: what changed, where did it change, and what is the user experiencing?
Logs are evidence
Logs are most useful when they describe a meaningful event with stable fields: operation, status, duration, resource, and correlation context. Avoid writing everything. The goal is to preserve enough evidence to explain a state transition without flooding the system with noise.
Metrics reveal shape
Metrics are excellent for trends and alerting. Request rate, error rate, latency distributions, queue depth, saturation, and resource utilization describe the shape of a system. Percentiles are often more informative than averages because tail latency is where users usually feel overload first.
Traces expose dependencies
A trace can connect one user-visible operation across several services. It is especially valuable when latency or failure spans multiple boundaries. Sampling should reflect the diagnostic value of traces rather than forcing every request to be retained forever.
Alert on symptoms
An alert should point to a situation that requires action. Prefer user-impacting symptoms and resource exhaustion signals over individual implementation counters that can move without consequence. Each alert needs an owner and a documented response path.
Telemetry is a product
Observability requires lifecycle management: retention, cost controls, schema stability, access controls, and a clear definition of what questions the data should answer. Treat telemetry as part of the operating system of the service rather than an afterthought.
Key takeaways
- Structure logs around events and stable fields.
- Use metrics for shape and alerting.
- Use traces to connect cross-service behavior.
- Every alert should correspond to an actionable operating state.