monitoring-observability

To correlate distributed traces with structured logs, you must standardize structured logs with trace IDs. This allows investigations to follow a request end-to-end across microservices by linking Jaeger or Tempo spans directly to Loki or ELK log entries.

The golden signals you should monitor for microservices are latency, traffic, errors, and saturation. Tracking these four metrics provides a baseline for system reliability and helps identify performance bottlenecks during incident response.

Setting up Prometheus instrumentation and alerting requires instrumenting services to expose time-series metrics and defining Alertmanager-style severity rules. This establishes SLO-oriented dashboards and golden-signal driven alerts for fast incident response.

The best way to propagate trace context across services using Jaeger or Tempo is by implementing distributed tracing with propagated trace context. This correlates spans across microservices and applies sensible sampling to track requests end-to-end.

Yes, you can use Grafana dashboards for SLO-driven alert rules and continuous review. They visualize key time-series metrics from Prometheus and define dashboard rules that support fast incident response and ongoing system reliability evaluation.

End-to-end observability typically uses separate specialized tools like Prometheus for metrics, Loki or ELK for logs, and Jaeger or Tempo for traces. This Skill provides guidance on unifying these scattered signals into a single correlated monitoring strategy.