Monitoring and Observability: Logs, Metrics, Traces

Monitoring and observability help teams keep services healthy and reliable. Monitoring collects data to show what happened. Observability uses that data to explain why it happened and how to fix it. Together, they turn complex systems into understandable ones.

Logs capture individual events with a timestamp, context, and a short message. To be useful, make logs structured: fields such as service, level, timestamp, requestId, and userId. Use clear levels (INFO, WARN, ERROR) and include a correlation ID so you can follow a single request across services. Centralize logs in a searchable store and set up alerts for unusual activity.

Metrics are numbers that describe behavior over time. Track latency, error rate, and throughput, plus resources like CPU and memory. Keep a small, meaningful set of metrics and show them in dashboards. Set alert thresholds that reflect real goals, not just occasional spikes. Remember that traffic changes metrics, so baselines should adapt gradually.

Traces show how a request travels through a distributed system. Each service adds a span, and the whole path forms a trace. Traces help you see bottlenecks, identify where delays come from, and connect clues from logs and metrics. Instrument your code with a standard like OpenTelemetry, and store traces in a trace backend. Consider sampling to limit data while still revealing the important paths.

In practice, logs, metrics, and traces work together. For example, a checkout request slows. A metric reveals higher latency, and a trace points to the payment service as the slow link. Logs in that service show a database timeout. This combination speeds up diagnosis and improves resilience.

Practical steps to start:

  • Define a few core SLIs like p95 latency, error rate, and availability.
  • Instrument key services with a standard like OpenTelemetry.
  • Centralize logs, metrics, and traces in one visible place.
  • Use a common requestId to connect data across layers.
  • Review baselines and adjust thresholds as traffic grows.

The goal is clear: make operations predictable, not chaotic. With steady practice, monitoring becomes part of everyday work, guiding improvements rather than reacting to crises.

Key Takeaways

  • Logs, metrics, and traces are complementary tools for understanding system behavior.
  • Structure and correlation IDs help you connect data across services.
  • Start small, use open standards, and grow your observability over time.