Which tracing backends are supported?

This skill specifically covers setup and integration for Jaeger and Grafana Tempo, the industry standards for trace storage and visualization.

How does this help with microservice debugging?

It provides the tools to trace a single request ID across multiple services, making it easy to see exactly where a failure or delay occurred in a complex call chain.

Can I use this for production environments?

Absolutely. It includes production-ready Kubernetes deployment patterns and advanced sampling strategies to manage data volume and performance overhead effectively.

Does it support OpenTelemetry?

Yes, the skill emphasizes OpenTelemetry as the primary instrumentation standard for Python, Node.js, and Go applications to ensure future-proof observability.

Is there a performance penalty for tracing?

The skill provides best practices like probabilistic sampling and batch span processors to keep tracing overhead minimal, typically below 1% CPU impact.

Distributed Tracing & Observability

Name: Distributed Tracing & Observability
Author: amurata

byamurata

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分析与监控

Implements end-to-end request tracing using Jaeger and Tempo to identify performance bottlenecks across distributed microservices.

This skill provides comprehensive guidance for implementing and managing distributed tracing in complex microservice architectures. It covers instrumentation for major languages like Python, Node.js, and Go using OpenTelemetry standards, as well as setup procedures for Jaeger and Grafana Tempo via Kubernetes and Docker. By enabling deep visibility into request flows, it helps developers debug latency issues, understand service dependencies, and trace error propagation through every layer of their infrastructure to improve system reliability and performance.

主要功能

01Multi-language instrumentation support (Python, Node.js, Go)

02Advanced sampling strategies and trace analysis methods

03Infrastructure setup for Jaeger and Grafana Tempo

04Context propagation techniques for cross-service tracking

05Standardized OpenTelemetry implementation patterns

063 GitHub stars

使用场景

01Visualizing service dependencies and request flow paths

02Root cause analysis for error propagation across distributed systems

03Debugging high latency and performance bottlenecks in microservices

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add amurata/cc-tools distributed-tracing

For use in Claude.ai and ChatGPT

Download Skill