distributed-tracing▌
aj-geddes/useful-ai-prompts · updated Apr 8, 2026
Set up distributed tracing infrastructure with Jaeger or Zipkin to track requests across microservices and identify performance bottlenecks.
Distributed Tracing
Table of Contents
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:
| Guide | Contents |
|---|---|
| Jaeger Setup | Jaeger Setup, Node.js Jaeger Instrumentation |
| Express Tracing Middleware | Express Tracing Middleware |
| Python Jaeger Integration | Python Jaeger Integration |
| Distributed Context Propagation | Distributed Context Propagation |
| Zipkin Integration | Zipkin 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
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★57 reviews- ★★★★★Isabella Ghosh· Dec 28, 2024
We added distributed-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Diya Gonzalez· Dec 8, 2024
distributed-tracing fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Layla Park· Dec 4, 2024
Registry listing for distributed-tracing matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Naina Ramirez· Dec 4, 2024
Useful defaults in distributed-tracing — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Amina Sanchez· Nov 27, 2024
I recommend distributed-tracing for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Layla Choi· Nov 27, 2024
Keeps context tight: distributed-tracing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Layla Wang· Nov 23, 2024
distributed-tracing reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 15, 2024
Keeps context tight: distributed-tracing is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Diya Anderson· Oct 18, 2024
Solid pick for teams standardizing on skills: distributed-tracing is focused, and the summary matches what you get after install.
- ★★★★★Layla Robinson· Oct 18, 2024
We added distributed-tracing from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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