Distributed Tracing & Observability

关于

This skill equips Claude with the expertise to implement and manage distributed tracing systems within modern microservice architectures. It provides comprehensive patterns for setting up observability stacks using Jaeger and Grafana Tempo, along with production-grade instrumentation code for Python, Node.js, and Go using OpenTelemetry standards. By enabling granular visibility into request flows, spans, and context propagation, it helps developers pinpoint latency issues, trace error propagation across service boundaries, and optimize system performance through data-driven analysis and service dependency visualization.

主要功能

• Automated Jaeger and Grafana Tempo infrastructure setup via Kubernetes and Docker
• Advanced sampling strategies including Probabilistic, Rate Limiting, and Adaptive
• Distributed context propagation and log correlation implementation patterns
• Querying and analysis workflows for identifying slow requests and service bottlenecks
• 23,194 GitHub stars
• Multi-language OpenTelemetry instrumentation for Python, Node.js, and Go

使用场景

• Correlating application logs with specific trace IDs to troubleshoot production errors
• Visualizing service dependencies and request paths in distributed systems
• Debugging intermittent latency spikes across complex microservice meshes