Python Observability Patterns

소개

The python-observability skill equips Claude with the expertise to instrument Python applications for high-visibility production monitoring. It provides standardized patterns for implementing JSON-based structured logging using structlog, tracking the 'Four Golden Signals' via Prometheus, and managing distributed tracing with OpenTelemetry. By integrating these practices, developers can ensure their systems are debuggable without code changes, enabling faster incident response and deeper performance analysis through correlation IDs and bounded metric cardinality.

주요 기능

• Instrumenting the Four Golden Signals: Latency, Traffic, Errors, and Saturation
• OpenTelemetry integration for modern distributed tracing architectures
• 27,605 GitHub stars
• Structured JSON logging configuration with structlog for machine-readable logs
• Prometheus metric collection with optimized label cardinality
• Correlation ID propagation patterns for end-to-end request tracing

사용 사례

• Implementing end-to-end request tracing across a complex chain of Python services
• Setting up centralized logging for microservices to enable faster production debugging
• Creating Prometheus dashboards to monitor service latency and error rates in real-time