distributed-tracing
CommunityTrack requests across microservices with Jaeger & Tempo.
Software Engineering#debugging#microservices#observability#Jaeger#OpenTelemetry#distributed tracing#Tempo
Authoranton-abyzov
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This skill helps you implement distributed tracing with Jaeger and Tempo, providing end-to-end visibility into request flows across microservices to identify latency, dependencies, and failure points.
Core Features & Use Cases
- Jaeger/Tempo Setup: Deploy Jaeger or Tempo using Kubernetes or Docker Compose for trace collection and storage.
- Application Instrumentation: Instrument your Python, Node.js, or Go applications using OpenTelemetry for automatic span generation.
- Context Propagation: Ensure trace context is propagated across all service boundaries using HTTP headers.
- Use Case: Your microservices architecture is experiencing intermittent latency. Use this skill to set up Jaeger, instrument your services with OpenTelemetry, and then analyze traces to pinpoint the exact service or database call causing the bottleneck.
Quick Start
Use the distributed-tracing skill to set up Jaeger using Docker Compose and instrument a Python Flask application with OpenTelemetry.
Dependency Matrix
Required Modules
jaegertempoopentelemetrykubernetesdocker-compose
Components
assetsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: distributed-tracing Download link: https://github.com/anton-abyzov/sw-soccer-manager/archive/main.zip#distributed-tracing Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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