Distributed Tracing for Microservices

About

This skill provides comprehensive patterns and guidance for implementing distributed tracing in microservices architectures using OpenTelemetry, Jaeger, and Grafana Tempo. It enables developers to gain deep visibility into complex systems by tracking requests across service boundaries, visualizing dependencies, and analyzing latency issues. With support for Python, Node.js, and Go, it covers everything from infrastructure deployment via Kubernetes and Docker Compose to advanced application instrumentation and context propagation strategies.

Key Features

• Multi-language instrumentation patterns for Python, Node.js, and Go using OpenTelemetry
• Configurable sampling strategies including probabilistic, rate-limiting, and adaptive sampling
• Trace analysis techniques for error propagation tracking and service dependency mapping
• Infrastructure setup guides for Jaeger and Grafana Tempo on Kubernetes and Docker
• Context propagation standards for maintaining trace continuity across HTTP headers
• 0 GitHub stars

Use Cases

• Monitoring error propagation and root-cause analysis in production environments
• Visualizing service dependencies and request paths across microservices
• Debugging high latency and performance bottlenecks in distributed systems