metrics-logs-traces

Implement distributed tracing with OpenTelemetry by instrumenting microservices to trace request flows. This enables comprehensive system observability and helps debug production issues by visualizing request paths through complex architectures.

Correlate metrics, logs, and traces by tying latency spikes in service metrics with specific structured error logs and tracing the request's path. This correlation pinpoints performance issues and identifies root causes in complex architectures.

Set up metrics monitoring using the RED method for service monitoring and the USE method for resource monitoring. This approach tracks system health and performance, enabling effective alerting and deep insights into system behavior.

Yes, this observability approach works with Datadog, Prometheus, and Grafana. It satisfies requirements for setting up these monitoring tools and adheres to best practices for alerting and correlating metrics, logs, and traces.

Structured JSON logging standardizes log formats with appropriate levels for effective debugging. It enables efficient parsing and correlation of error logs with metrics and traces to pinpoint production issues in complex systems.

Distributed tracing adds overhead to request flows, so avoid it in simple monolithic architectures where request paths are already transparent. Use it when debugging complex microservices where understanding request flows is critical.