tempo-troubleshoot

TraceQL lets you filter Tempo traces by service, duration, and status to pinpoint latency. Construct queries scoped to a specific service and time range, then correlate results with Loki logs and Mimir metrics for root-cause analysis across microservices.

Build TraceQL queries by filtering on service name, error status, and time range to isolate failures. Avoid high-cardinality attributes that degrade performance, and link matching traces to logs and metrics for deeper context.

Yes. Use TraceQL to find traces, then link them to Loki logs and Mimir metrics within the same service and time window. This trace-log-metrics correlation provides holistic visibility into request-level failures and bottlenecks.

Navigate distributed traces to examine spans across services, identify which span caused latency or errors, and correlate with logs and metrics. Scope queries to your service and time range to keep analysis focused and performant.

TraceQL does not execute queries directly in this Skill; it provides guidance only. Avoid high-cardinality attributes, scope queries tightly by service and time range, and use external Tempo or Grafana instances to run the queries you construct.

Use distributed tracing when errors span multiple services and logs alone don't show the flow. TraceQL queries on the payments service reveal which span failed, then correlate with logs and metrics to identify root cause.