What backends does this distributed tracing skill support?

The skill provides detailed setup and configuration guides for both Jaeger and Grafana Tempo, enabling flexible observability infrastructure.

Does it provide code examples for multiple languages?

Yes, it includes production-ready instrumentation examples for Python (Flask), Node.js (Express), and Go applications.

How does this help with debugging performance bottlenecks?

It teaches you how to query traces for high duration, analyze span-level latencies, and visualize the service dependency graph to pinpoint exactly where delays occur.

Does it support OpenTelemetry standards?

Yes, it focuses on OpenTelemetry (OTel) for application instrumentation, ensuring your tracing implementation is vendor-neutral and future-proof.

Can I use this for Kubernetes deployments?

Absolutely. The skill includes specific Kubernetes manifests for deploying Jaeger via Operators and configuring Tempo for cloud-native environments.

Distributed Tracing (Jaeger & Tempo)

Name: Distributed Tracing (Jaeger & Tempo)
Author: Microck

byMicrock

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分析与监控

Implement and manage end-to-end request tracking across microservices using Jaeger, Tempo, and OpenTelemetry.

This skill provides a comprehensive framework for implementing distributed tracing in complex microservices architectures. It guides users through setting up observability backends like Jaeger and Grafana Tempo, instrumenting applications in multiple languages (Python, Node.js, Go) using OpenTelemetry standards, and managing context propagation across service boundaries. By providing clear patterns for sampling, trace analysis, and log correlation, it enables developers to identify performance bottlenecks, debug latency issues, and visualize service dependencies with precision.

主要功能

01Infrastructure setup for Jaeger and Grafana Tempo via Kubernetes and Docker Compose

02Trace analysis techniques for identifying slow requests and error propagation

03OpenTelemetry-based context propagation and header management

04Advanced sampling strategies including probabilistic and rate-limiting

05Multi-language instrumentation patterns for Python, Node.js, and Go

062 GitHub stars

使用场景

01Debugging high latency in complex microservices request chains

02Implementing observability standards for production-grade cloud-native applications

03Visualizing service dependencies and identifying failure points in distributed systems

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add microck/opendots-microck distributed-tracing

For use in Claude.ai and ChatGPT

Download Skill