implementing-observability

To implement OpenTelemetry instrumentation for a new microservice, you set up data collection for metrics, logs, and traces. This ensures you can immediately monitor performance, debug errors, and understand request flows in production.

The best way to set up the LGTM stack for self-hosted observability is deploying and configuring Loki, Grafana, Tempo, and Mimir. This provides a comprehensive framework for deep visibility into production systems.

Log-trace correlation works by enriching logs with trace context using OpenTelemetry. This pattern ensures seamless debugging by linking log entries directly to their originating request flows.

You need OpenTelemetry to achieve unified observability because it serves as the industry standard for implementing metrics, logs, and traces. It provides the comprehensive framework required for building visible and debuggable production systems.

You can use Grafana with Loki and Tempo for monitoring microservices by deploying them as the LGTM stack. Grafana visualizes the metrics, logs, and traces collected via OpenTelemetry to provide deep production visibility.

Limitations of self-hosted observability with the LGTM stack involve the operational overhead of deploying and configuring Loki, Grafana, Tempo, and Mimir yourself. You must manage the infrastructure required to maintain deep visibility into production systems.