How does this help with performance optimization?

It allows you to identify specific 'spans' or operations within a trace that are causing high latency, enabling targeted optimization of slow database queries or service calls.

Which tools does this skill support?

This skill provides specific implementation patterns and configurations for Jaeger and Grafana Tempo, utilizing the OpenTelemetry standard for instrumentation.

Can I use this for production deployments?

Absolutely. It includes Kubernetes manifests for the Jaeger Operator and production-grade Tempo configurations, as well as Docker Compose for local development.

What is distributed tracing?

Distributed tracing is a method used to profile and monitor applications, especially microservices, by tracking requests as they move through different services to provide a complete view of the request journey.

Does this skill work with multiple programming languages?

Yes, it includes detailed instrumentation examples for Python (Flask), Node.js (Express), and Go applications.

Distributed Tracing Implementation

Name: Distributed Tracing Implementation
Author: HermeticOrmus

byHermeticOrmus

0•

分析与监控

Implements comprehensive distributed tracing using Jaeger and Tempo to monitor request flows and optimize microservice performance.

The Distributed Tracing skill provides a structured framework for implementing end-to-end observability across microservices using industry-standard tools like Jaeger, Tempo, and OpenTelemetry. It simplifies the complex process of tracking request journeys through distributed systems by providing ready-to-use deployment configurations for Kubernetes and Docker, alongside multi-language instrumentation patterns for Python, Node.js, and Go. This skill is essential for developers and SREs who need to identify latency bottlenecks, understand service dependencies, and debug error propagation in high-scale cloud-native environments.

主要功能

01Advanced trace analysis and query guidance

02Production-ready Jaeger and Tempo deployment configurations

03Context propagation and sampling strategy templates

04Multi-language instrumentation patterns for Python, Node.js, and Go

050 GitHub stars

06Log correlation and service dependency mapping

使用场景

01Debugging high latency and performance bottlenecks in microservices

02Visualizing complex request flows and service-to-service dependencies

03Identifying the root cause of error propagation in distributed systems

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add hermeticormus/after-the-third-cup distributed-tracing

For use in Claude.ai and ChatGPT

Download Skill