Which programming languages are covered for instrumentation?

It provides production-ready OpenTelemetry instrumentation examples for Python (Flask), Node.js (Express), and Go.

Can I correlate my traces with application logs?

Yes, the skill provides specific implementation patterns for injecting trace and span IDs into application logs to enable seamless navigation between traces and logs.

How does distributed tracing impact application performance?

The skill includes best practices and sampling strategies, such as probabilistic and adaptive sampling, to keep performance overhead typically under 1% CPU impact.

Which tracing backends are supported by this skill?

This skill specifically covers setup and integration for Jaeger and Grafana Tempo, utilizing OpenTelemetry for vendor-neutral instrumentation.

Does this skill support Kubernetes deployments?

Yes, it includes detailed configuration patterns for deploying tracing infrastructure using Kubernetes Operators and production-ready YAML manifests.

Distributed Tracing & Observability

Name: Distributed Tracing & Observability
Author: drgaciw

bydrgaciw

0•

Analytics & Monitoring

Implements end-to-end request tracking across microservices using Jaeger, Tempo, and OpenTelemetry to eliminate performance bottlenecks.

This skill provides comprehensive guidance for implementing distributed tracing in modern microservice architectures. It enables developers to visualize the entire lifecycle of a request across service boundaries, identifying latency issues, error propagation, and service dependencies. By leveraging OpenTelemetry standards and popular backends like Jaeger and Grafana Tempo, the skill offers production-ready patterns for Kubernetes and Docker environments, multi-language instrumentation for Python, Node.js, and Go, and advanced sampling strategies to ensure high observability with minimal performance overhead.

Key Features

01Multi-language OpenTelemetry instrumentation for Python, Node.js, and Go

02Trace-log correlation for unified debugging workflows

03Advanced sampling strategies including Probabilistic and Rate Limiting

04Infrastructure setup for Jaeger and Grafana Tempo backends

050 GitHub stars

06Standardized context propagation patterns for HTTP headers

Use Cases

01Optimizing database performance by visualizing span durations

02Identifying the root cause of high latency in complex microservices

03Tracing error propagation through service dependency chains

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add drgaciw/academic-compliance-hub-glm distributed-tracing

For use in Claude.ai and ChatGPT

Key Features

01Multi-language OpenTelemetry instrumentation for Python, Node.js, and Go

02Trace-log correlation for unified debugging workflows

03Advanced sampling strategies including Probabilistic and Rate Limiting

04Infrastructure setup for Jaeger and Grafana Tempo backends

050 GitHub stars

06Standardized context propagation patterns for HTTP headers

Use Cases

01Optimizing database performance by visualizing span durations

02Identifying the root cause of high latency in complex microservices

03Tracing error propagation through service dependency chains

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add drgaciw/academic-compliance-hub-glm distributed-tracing

For use in Claude.ai and ChatGPT