Can I use this for both Kubernetes and Docker environments?

Yes, it includes deployment configurations for Kubernetes (via Jaeger Operator) and local development setups using Docker Compose.

Which languages does this skill support for instrumentation?

The skill provides patterns and code snippets for Python (Flask), Node.js (Express), and Go, specifically using the OpenTelemetry SDK.

What tracing standards does this skill utilize?

It focuses on OpenTelemetry (OTel), which is the industry standard for vendor-neutral instrumentation, ensuring your tracing setup is portable and future-proof.

Does it support Grafana integration?

Yes, it includes setup guides for Grafana Tempo, enabling you to store and visualize traces within the Grafana ecosystem alongside metrics and logs.

How does this help with debugging microservices?

It allows you to find slow requests, trace error propagation across services, and visualize service dependency graphs to pinpoint exactly where a request failed or slowed down.

Distributed Tracing for Microservices

Name: Distributed Tracing for Microservices
Author: HermeticOrmus

byHermeticOrmus

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分析与监控

Implements distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks.

This skill empowers Claude to architect and implement robust observability solutions for distributed systems using industry-standard tools like OpenTelemetry, Jaeger, and Tempo. It provides specialized knowledge to instrument applications across multiple languages, configure context propagation through HTTP headers, and deploy tracing infrastructure in Kubernetes or Docker environments. By providing patterns for span management and log correlation, it helps developers gain full visibility into request flows, map service dependencies, and rapidly diagnose root causes in complex microservice architectures.

主要功能

01Context propagation strategies for seamless tracking across service boundaries

02Advanced sampling configuration and trace analysis query patterns

032 GitHub stars

04Log correlation and automated service dependency mapping

05Multi-language instrumentation (Python, Node.js, Go) using OpenTelemetry standards

06Infrastructure setup for Jaeger and Grafana Tempo in Kubernetes and Docker

使用场景

01Diagnosing high-latency requests in complex microservices architectures

02Optimizing distributed system performance by uncovering hidden bottlenecks

03Visualizing end-to-end request paths to identify points of failure

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add hermeticormus/libreuiux-claude-code distributed-tracing

For use in Claude.ai and ChatGPT

Download Skill