What logging library does this skill utilize?

The skill uses 'structlog' to provide high-performance structured logging, supporting JSON formats for production environments and human-readable console output for local development.

Can I track custom metrics like database latency?

Absolutely. The skill provides pre-built decorators to easily track latency and hit rates for database queries and cache operations using Prometheus Histograms and Counters.

Is this skill compatible with Kubernetes?

Yes, it includes specialized health check routes (/health/live and /health/ready) designed specifically to work with Kubernetes liveness and readiness probes.

How are request IDs handled?

The skill includes middleware that generates a unique UUID for every request, binds it to the logging context for trace-ability, and returns it in the X-Request-ID response header.

Does it support distributed tracing across services?

Yes, it implements OpenTelemetry with OTLP exporters, allowing you to trace requests through FastAPI, HTTP clients, and Redis across your entire microservice architecture.

FastAPI Observability & Monitoring

Name: FastAPI Observability & Monitoring
Author: markus41

bymarkus41

•

分析与监控

Implements production-ready observability patterns including structured logging, Prometheus metrics, and OpenTelemetry tracing for FastAPI applications.

This skill provides a comprehensive suite of observability tools designed to make FastAPI services enterprise-ready and easy to debug. It features standardized configurations for structured logging using structlog, automated Prometheus metric collection, and distributed tracing with OpenTelemetry. By implementing these patterns, developers gain deep insights into application performance, request lifecycles, and system health through Kubernetes-compatible probes and custom instrumentation for databases and caches.

主要功能

01Custom decorators for tracking database and cache latency

029 GitHub stars

03Structured JSON logging with request-id context tracking via structlog

04Kubernetes-ready liveness and readiness health check endpoints

05Distributed tracing setup using OpenTelemetry and OTLP exporters

06Automated Prometheus metrics instrumentation for API endpoints

使用场景

01Setting up comprehensive monitoring for Grafana dashboards using Prometheus

02Transitioning a FastAPI app from basic print statements to production-grade structured logs

03Debugging performance bottlenecks in microservices using distributed tracing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add markus41/claude fastapi-observability

For use in Claude.ai and ChatGPT

主要功能

01Custom decorators for tracking database and cache latency

029 GitHub stars

03Structured JSON logging with request-id context tracking via structlog

04Kubernetes-ready liveness and readiness health check endpoints

05Distributed tracing setup using OpenTelemetry and OTLP exporters

06Automated Prometheus metrics instrumentation for API endpoints

使用场景

01Setting up comprehensive monitoring for Grafana dashboards using Prometheus

02Transitioning a FastAPI app from basic print statements to production-grade structured logs

03Debugging performance bottlenecks in microservices using distributed tracing

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add markus41/claude fastapi-observability

For use in Claude.ai and ChatGPT