observability-patterns

Structured JSON logging and distributed tracing in Spring Boot are configured using the Logstash encoder for log output and OpenTelemetry with Micrometer bridging for trace context propagation. This ensures logs and traces correlate across microservices.

Custom Micrometer metrics like counters, timers, and gauges are exposed to Prometheus by configuring the Micrometer Prometheus registry in your Spring Boot application, allowing Grafana to scrape and visualize the metric data.

Yes, the observability setup supports Kubernetes liveness and readiness probes by implementing Spring Boot health indicators, enabling reliable deployment health monitoring and automated container orchestration within production environments.

The best way to add alerting for JVM heap and DB pool saturation is by exporting custom Micrometer metrics to Prometheus and configuring alerting rules integrated directly with Grafana dashboards for real-time visualization.

Yes, you can use OpenTelemetry with Micrometer for Spring Boot observability by utilizing Micrometer bridging to connect distributed tracing data with custom application metrics, providing cohesive end-to-end visibility.

MDC context propagation is needed for structured logging in Spring Boot microservices to maintain trace identifiers across asynchronous boundaries, ensuring distributed traces and JSON logs remain correlated end-to-end.