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opentelemetry

Implement OpenTelemetry tracing, metrics, and logs for Go and Python applications.

Updated Feb 2, 2026
Search Tags:#monitoring#logging#metrics#observability#distributed systems#tracing#opentelemetry
One-click install
npx skills add https://github.com/JNZader-Vault/project-starter-framework --skill opentelemetry-jnzader-vault
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: opentelemetry
Source: https://github.com/JNZader-Vault/project-starter-framework/tree/main/.ai-config/skills/infrastructure/opentelemetry
Command: npx skills add https://github.com/JNZader-Vault/project-starter-framework --skill opentelemetry-jnzader-vault

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive solution for instrumenting applications to collect traces, metrics, and logs, enabling deep visibility into distributed systems.

Core Features & Use Cases

  • Distributed Tracing: Track requests as they flow across multiple services.
  • Metrics Collection: Gather performance metrics like request latency and error rates.
  • Log Aggregation: Centralize logs for easier debugging and analysis.
  • Use Case: Instrument a microservices architecture to pinpoint performance bottlenecks and identify the root cause of errors across services like Go backend APIs and Python FastAPI applications.

Quick Start

Configure OpenTelemetry tracing and metrics for a Go application using OTLP and set up the collector with Jaeger and Prometheus.

Frequently Asked Questions about opentelemetry

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I implement distributed tracing across Go and Python microservices?▼

Implement distributed tracing across Go and Python microservices by instrumenting applications with OpenTelemetry to track requests as they flow across multiple services, using OTLP to send data to a collector configured for Jaeger.

How does OpenTelemetry log aggregation work for debugging distributed systems?▼

OpenTelemetry log aggregation centralizes logs from distributed systems for easier debugging and analysis, instrumenting Go and Python applications to collect traces, metrics, and logs for deep visibility into microservices architectures.

Can I collect metrics and traces from a Python FastAPI application using Prometheus?▼

Yes, you can collect metrics and traces from a Python FastAPI application using Prometheus by instrumenting the application with OpenTelemetry and configuring the collector to gather performance metrics like request latency and error rates.

What is the best way to pinpoint performance bottlenecks in a microservices architecture?▼

The best way to pinpoint performance bottlenecks in a microservices architecture is using OpenTelemetry to instrument distributed systems, gathering metrics and distributed traces to identify the root cause of errors across services.

Does this observability pattern support configuring collectors with Docker Compose?▼

Yes, this observability pattern supports configuring collectors with Docker Compose, providing configuration examples for Jaeger, Prometheus, and Grafana to integrate traces, metrics, and logs from Go and Python applications.

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