Observability: Logging, Tracing, and Monitoring
When a request touches five different services before returning a response, finding where something went wrong is exponentially harder than debugging a monolith. Observability — structured logging, distributed tracing, and metrics collection — is not optional in microservices. It is the only way to understand what your system is actually doing.
Watch: Video Walkthrough
Key Concepts
- Structured Logging: JSON-formatted logs with correlation IDs that trace across services
- Distributed Tracing: Using OpenTelemetry to track requests across service boundaries
- Metrics Collection: Prometheus-style metrics for latency, error rates, and throughput
- Dashboards and Alerts: Building Grafana dashboards and setting up meaningful alerts
Hands-On Exercise
Task: Add OpenTelemetry instrumentation to your containerized services. Generate a correlation ID at the API gateway, propagate it through all service-to-service calls (including message queue events), and configure a Jaeger instance to visualize distributed traces. Build one Grafana dashboard showing request latency and error rates per service.
Pro Tips
The single most valuable observability investment is a correlation ID (also called trace ID) that follows a request through every service. Add it to every log line, every message, every HTTP header. When something breaks at 3am, this is what lets you reconstruct exactly what happened in under 5 minutes.