An alert starts an investigation; it does not explain the failure. Observability helps a team ask new questions about system behavior using the telemetry it emits. Useful evidence connects the customer symptom to the path taken by a request.
Follow one request
Example: Order-status responses slow down. A latency metric reveals the change. A trace shows that affected requests spend most of their time waiting on a carrier call. Correlated logs show timeouts and retry attempts.
That evidence suggests a dependency problem. It still needs verification: compare healthy requests, check the time window, and test whether the proposed fix restores the customer experience.
Apply it
Instrument one important user journey. Propagate trace context across service boundaries and include trace identifiers in relevant structured logs. Track latency, failures, and traffic with enough context to distinguish affected operations.
Choose alerts around actionable user impact. Set sampling and retention deliberately, protect sensitive fields, and control high-cardinality labels.
Metrics summarize behavior, traces connect work, and logs record events. None automatically proves a root cause, and missing telemetry can hide part of the story.
Related: DORA and DevEx.