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go-observability

Implement structured logging, distributed tracing, and metrics in Go applications.

Updated Dec 31, 2025
Search Tags:#logging#metrics#go#observability#tracing#prometheus#opentelemetry
One-click install
npx skills add https://github.com/victorzhuk/go-ent --skill go-observability-victorzhuk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: go-observability
Source: https://github.com/victorzhuk/go-ent/tree/main/pkg/skills/go/go-observability
Command: npx skills add https://github.com/victorzhuk/go-ent --skill go-observability-victorzhuk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of effectively monitoring and debugging Go applications by providing comprehensive observability solutions.

Core Features & Use Cases

  • Structured Logging: Implements slog for organized, context-rich logs.
  • Distributed Tracing: Integrates OpenTelemetry for end-to-end request tracing.
  • Metrics Collection: Sets up Prometheus for performance monitoring.
  • Correlation IDs: Ensures consistent tracking of requests across services.
  • Use Case: Debugging a slow API endpoint by correlating logs, traces, and metrics to pinpoint the bottleneck.

Quick Start

Provide recommendations for integrating structured logging using slog into a Go service.

Frequently Asked Questions about go-observability

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

FAQPage Schema
How do I implement structured logging in Go using slog?▼

Structured logging in Go using slog involves organizing log entries with key-value pairs for context-rich output. This approach enables easier filtering and analysis of application logs during production debugging.

What's the best way to set up distributed tracing in Go with OpenTelemetry?▼

Distributed tracing in Go with OpenTelemetry captures end-to-end request flows across services. It provides spans and traces that help pinpoint bottlenecks and failures in complex microservice architectures.

How do I track correlation IDs across Go microservices for request debugging?▼

Tracking correlation IDs in Go involves passing unique identifiers through service requests to link logs, traces, and metrics. This ensures consistent monitoring of cross-service request flows.

Can I use Prometheus for metrics collection in a Go application?▼

Prometheus is fully supported for metrics collection in Go applications. It enables performance monitoring by scraping and storing time-series data, helping track API latency and resource utilization.

Does OpenTelemetry work with slog for Go observability?▼

OpenTelemetry and slog work together to provide comprehensive Go observability. Combining distributed tracing with structured logging allows you to correlate trace spans with specific log entries for effective debugging.

Why do I need correlation IDs when debugging slow Go API endpoints?▼

Correlation IDs are necessary for debugging slow Go API endpoints because they link related logs, traces, and metrics across multiple services. This unified view pinpoints exactly where bottlenecks occur in the request lifecycle.

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