golang-observability

To add observability to a Go service, you instrument it with structured logging, metrics, tracing, and profiling using tools like slog, Prometheus, and OpenTelemetry. This turns hidden runtime activity into structured signals for diagnosis.

The best way to implement structured JSON logging in Golang is using slog for production output. It supports context-aware correlation and helps migrate from older loggers to generate queryable, structured telemetry data.

Configure Prometheus metrics in Go by designing histograms with proper naming conventions and implementing cardinality control. This prevents unbounded label growth while enabling effective burn-rate alerts and dashboard visualization.

Yes, OpenTelemetry tracing works with slog for context propagation. You can correlate traces, logs, and exemplars by placing spans correctly, propagating context, and recording errors across your Go service telemetry.

Yes, you can use pprof for safe continuous profiling in production Go applications. The approach includes privacy-aware practices for user monitoring and compliance to ensure runtime profiling does not expose sensitive data.

You need OpenTelemetry context propagation when adding observability to a new Go API or hardening an existing service. It ensures trace spans are linked across service boundaries and correlated with structured logs.