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Building an Observability Stack: Logs, Metrics, and Traces
Orihost
Posted by
April 30, 2026
Date Published
Observability Is a System, Not a Dashboard
Teams often collect logs but still struggle during incidents. The missing piece is linking logs, metrics, and traces into one workflow.
The Three Signals Explained
- Logs: detailed events for root cause evidence.
- Metrics: trend and SLO visibility across time.
- Traces: per-request path to isolate slow components.
What Each Signal Is Best For
| Question | Best Signal | Why |
|---|---|---|
| Are users impacted now? | Metrics | Fast aggregate status |
| Which service is slow? | Traces | End-to-end latency breakdown |
| What exact error happened? | Logs | Full context and payload clues |
Baseline Stack for Mid-Sized Apps
- Define SLIs/SLOs before tool setup.
- Instrument HTTP + DB calls for tracing.
- Include
request_idandtrace_idin logs. - Alert on user-impact thresholds, not raw noise.
- Add runbook links to alert payloads.
Common Failure Pattern
Alert fires, on-call checks dashboard, then manually jumps across tools with no shared ID context. Fix this by enforcing correlation identifiers across all telemetry paths.