What technologies does this skill support?

It focuses on OpenTelemetry for instrumentation with Jaeger and Tempo as backend collectors, supporting Python, Node.js, and Go environments.

How does this help with debugging?

It allows you to trace a single request across every service it touches, showing exactly where it slows down or fails in the request chain.

Does this skill cover log correlation?

Yes, it provides patterns for injecting trace IDs into application logs to link spans directly with log entries for unified troubleshooting.

Can I use this for production environments?

Yes, the skill includes production-ready Kubernetes deployment templates and guidance on sampling strategies to manage performance overhead.

Distributed Tracing & Observability

Name: Distributed Tracing & Observability
Author: GaitanS

byGaitanS

分析与监控

Implements distributed tracing using Jaeger and Tempo to monitor request flows and optimize performance in microservices architectures.

关于

This skill provides comprehensive guidance for implementing distributed tracing across complex microservice architectures using industry-standard tools like Jaeger and Tempo. It equips developers with implementation patterns for application instrumentation using OpenTelemetry in Python, Node.js, and Go, while also covering infrastructure setup via Kubernetes and Docker Compose. By providing best practices for context propagation, sampling strategies, and log correlation, this skill enables teams to visualize end-to-end request journeys, diagnose latent performance bottlenecks, and resolve cross-service failures with precision.

主要功能

Multi-language instrumentation patterns for Python, Node.js, and Go
Standardized OpenTelemetry integration for vendor-neutral observability
Trace-to-log correlation techniques for enhanced debugging
Advanced sampling strategies including probabilistic and rate-limiting
0 GitHub stars
Infrastructure templates for Jaeger and Grafana Tempo deployments

使用场景

Diagnosing high-latency bottlenecks in complex microservice dependency chains
Visualizing service maps and request flows for architectural analysis
Debugging intermittent errors that propagate across service boundaries

关于

主要功能

Multi-language instrumentation patterns for Python, Node.js, and Go
Standardized OpenTelemetry integration for vendor-neutral observability
Trace-to-log correlation techniques for enhanced debugging
Advanced sampling strategies including probabilistic and rate-limiting
0 GitHub stars
Infrastructure templates for Jaeger and Grafana Tempo deployments

使用场景

Diagnosing high-latency bottlenecks in complex microservice dependency chains
Visualizing service maps and request flows for architectural analysis
Debugging intermittent errors that propagate across service boundaries