How does it handle health checks in Kubernetes?

The skill provides dedicated /health/live and /health/ready endpoints, including logic to check database and cache connectivity for accurate readiness signaling.

Does it integrate with distributed tracing tools?

Yes, it implements OpenTelemetry standards, allowing your FastAPI application to export traces to platforms like Jaeger, Honeycomb, or Datadog.

Does this skill support JSON logging for production?

Yes, it configures structlog to provide structured JSON logging optimized for production log aggregators like ELK or Loki, while maintaining readable console output for development.

Can I track custom business metrics with this skill?

Absolutely. It includes patterns and decorators for tracking custom metrics like database query latency and cache hit/miss ratios using Prometheus.

FastAPI Observability

Name: FastAPI Observability
Author: Lobbi-Docs

byLobbi-Docs

0•

分析と監視

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

This skill streamlines the implementation of comprehensive observability in FastAPI services by providing standardized patterns for structured JSON logging, real-time metrics, and distributed tracing. It includes pre-configured middleware for request tracking, custom decorators for monitoring database and cache performance, and robust health check endpoints compatible with Kubernetes liveness and readiness probes. Whether you are debugging a local service or scaling a microservice architecture, this skill ensures your backend provides the telemetry data needed for modern monitoring stacks like Grafana, Prometheus, and Jaeger.

主な機能

01Structured JSON logging with context-aware structlog configuration

02Prometheus metrics instrumentation for endpoints and custom resource tracking

03OpenTelemetry (OTel) integration for distributed tracing and APM

04Standardized health check endpoints for Kubernetes liveness and readiness probes

05Request-ID tracking middleware for end-to-end log correlation

060 GitHub stars

ユースケース

01Setting up centralized monitoring for a production FastAPI microservice

02Diagnosing performance bottlenecks with custom DB and cache latency metrics

03Standardizing telemetry data across multiple Python backend services

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lobbi-docs/claude fastapi-observability

For use in Claude.ai and ChatGPT

Download Skill