/blog/logs-traces-metrics
field guide
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telemtra.io
// observability signals

Logs, traces, and metrics:
which signal answers which question?

Good observability is not collecting everything. It is choosing the right signal for the question and keeping the signals linked by shared context.

Use logs when you need details

Logs are best for exact events: the error message, the payload class, the payment provider result, the user action, the retry reason. Structured logs are much more useful than plain text because they can be filtered and grouped.

Use traces when you need causality

Traces are best when one operation crosses boundaries. They show parent-child relationships between spans, expose slow dependencies, and make service maps possible.

Use metrics when you need trends or alerts

Metrics are best for long-running measurement: request rate, error rate, latency distributions, CPU, memory, queue depth, and saturation. They are usually the cheapest signal for alerting.

Use them together for production debugging

A practical workflow starts with a metric alert, opens a trace sample that explains latency or errors, then jumps to logs with the same trace or service context. That is why consistent OpenTelemetry resource attributes matter so much.

How Telemtra connects them

Telemtra keeps logs, traces, and metrics in one workspace. Dashboards and alerts point to the same service names. Service Map uses trace relationships. Data Shaper helps remove noisy logs before they distract from useful debugging data.