python-observability

You can set up structured logging and distributed tracing in a FastAPI application by integrating structlog for JSON logging and OpenTelemetry for auto-instrumentation. This combination provides comprehensive observability to quickly diagnose production issues.

The best way to manage correlation IDs in asynchronous Python contexts is using structlog combined with OpenTelemetry. This ensures trace context is properly propagated across async operations for correlated logs and distributed traces.

Yes, this observability setup supports both Flask and FastAPI web frameworks. OpenTelemetry provides auto-instrumentation for these frameworks, automatically capturing incoming requests and generating distributed traces without requiring manual span creation.

Yes, you can expose Prometheus metrics alongside OpenTelemetry tracing in Python. This setup integrates the Prometheus client for metrics exposition while simultaneously using OpenTelemetry to collect distributed traces and application performance data.

To create custom spans for OpenTelemetry distributed tracing in Python, use the OpenTelemetry SDK to define specific operations within your application. This allows you to capture detailed performance traces beyond automatic web framework instrumentation.