observability-and-instrumentation

Instrument code for production observability by adding structured logging, metrics, and tracing with stable event names and correlation IDs. This makes system behavior diagnosable across services, endpoints, and background jobs to answer what happened, why, and where.

Design structured telemetry by first defining 2–4 on-call questions for a feature, then picking signals like logs, metrics, and traces to answer them. Implement telemetry with correlation IDs and verify outputs against dashboards and alerts.

Correlation IDs link structured logging and tracing across services to locate bottlenecks and failures quickly. They connect events across distributed services, endpoints, and background jobs, ensuring you can trace what happened and where.

Yes, production-strong best practices include implementing RED metrics and alerting rules for deployed features. Define alerting rules to verify telemetry outputs and validate feature behavior against dashboards during incidents.

Add tracing and metrics instrumentation when features are deployed in production and need diagnosable behavior. Without telemetry, diagnosing incidents and validating feature behavior becomes guesswork, so instrument early to satisfy observability best practices.

Observability instrumentation applies to features deployed across services, endpoints, background jobs, and integrations. Structured logging, metrics, and tracing cover all these components to make production behavior observable and diagnosable.