aj-geddes/useful-ai-prompts8 files

Distributed Tracing

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Specification
Skill ID
aj-geddes/useful-ai-prompts/distributed-tracing
Publisher
aj-geddes
Repository
useful-ai-prompts
Installs
0
Files
8
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

aj-geddes/useful-ai-prompts/distributed-tracingInstalls these files
  • SKILL.md
  • references/distributed-context-propagation.md
  • references/express-tracing-middleware.md
  • references/jaeger-setup.md
  • references/python-jaeger-integration.md
  • references/zipkin-integration.md
  • scripts/validate-api.sh
  • templates/api-scaffold.yaml

What this skill tells the agent

Distributed Tracing

Table of Contents

  • Overview
  • When to Use
  • Quick Start
  • Reference Guides
  • Best Practices

Overview

Set up distributed tracing infrastructure with Jaeger or Zipkin to track requests across microservices and identify performance bottlenecks.

When to Use

  • Debugging microservice interactions
  • Identifying performance bottlenecks
  • Tracking request flows
  • Analyzing service dependencies
  • Root cause analysis

Quick Start

Minimal working example:

# docker-compose.yml
version: "3.8"
services:
  jaeger:
    image: jaegertracing/all-in-one:latest
    ports:
      - "5775:5775/udp"
      - "6831:6831/udp"
      - "16686:16686"
      - "14268:14268"
    networks:
      - tracing

networks:
  tracing:

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
Jaeger SetupJaeger Setup, Node.js Jaeger Instrumentation
Express Tracing MiddlewareExpress Tracing Middleware
Python Jaeger IntegrationPython Jaeger Integration
Distributed Context PropagationDistributed Context Propagation
Zipkin IntegrationZipkin Integration, Trace Analysis

Best Practices

✅ DO

  • Sample appropriately for your traffic volume
  • Propagate trace context across services
  • Add meaningful span tags
  • Log errors with spans
  • Use consistent service naming
  • Monitor trace latency
  • Document trace format
  • Keep instrumentation lightweight

❌ DON'T

  • Sample 100% in production
  • Skip trace context propagation
  • Log sensitive data in spans
  • Create excessive spans
  • Ignore sampling configuration
  • Use unbounded cardinality tags
  • Deploy without testing collection

Use this skill in a project

Open any RiverX project, search the Skills panel for aj-geddes/useful-ai-prompts/distributed-tracing, and install it in one click.

Use this skill