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observability-principles

Standardize structured logging, correlation IDs, distributed traces, and metrics collection.

Updated Mar 31, 2026
Search Tags:#logging#metrics#observability#tracing#opentelemetry#mdc#correlation-id
One-click install
npx skills add https://github.com/baldimir/bob-skills --skill observability-principles-baldimir
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: observability-principles
Source: https://github.com/baldimir/bob-skills/tree/main/.bob/skills/observability-principles
Command: npx skills add https://github.com/baldimir/bob-skills --skill observability-principles-baldimir

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Production systems often suffer from opaque behavior, making debugging and reliability improvements difficult. This Skill provides universal observability principles to standardize how logs, traces, and metrics are collected and interpreted across teams.

Core Features & Use Cases

  • Structured logging guidance with MDC/correlation ID patterns to attach context to every log message.
  • Distributed tracing concepts and OpenTelemetry integration to enable end-to-end request visibility.
  • Metrics guidance for counters, histograms, and gauges, plus how to expose a metrics endpoint for monitoring and alerting.

Quick Start

Configure structured logging with JSON output, propagate correlation IDs across service boundaries, enable tracing with OpenTelemetry, and instrument key business metrics.

Frequently Asked Questions about observability-principles

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

FAQPage Schema
How do I implement distributed tracing with OpenTelemetry across services?▼

Distributed tracing with OpenTelemetry provides end-to-end request visibility by propagating correlation IDs across service boundaries. This enables tracking requests through distributed systems to simplify debugging and performance tuning.

What is structured logging with MDC and correlation IDs?▼

Structured logging with MDC attaches contextual information to every log message using correlation IDs. This pattern standardizes log collection with JSON output, making it easier to trace requests across distributed systems.

How do I set up metrics collection for monitoring and alerting?▼

Metrics collection uses counters, histograms, and gauges to monitor system behavior in real time. Exposing a metrics endpoint enables alerting on key business metrics and performance indicators across distributed applications.

Can I use these observability principles with any framework or language?▼

These observability principles apply to distributed systems across languages and frameworks. They provide non-invasive groundwork that framework-specific observability skills can extend with clear MDC patterns and header propagation guidance.

Why do I need correlation IDs in my production logs?▼

Correlation IDs in production logs solve the problem of opaque system behavior by linking related log messages across service boundaries. This standardization makes debugging distributed systems and improving reliability significantly easier.

What's the best way to standardize observability across multiple teams?▼

Standardize observability by implementing universal principles for logs, traces, and metrics collection. This approach ensures consistent interpretation across teams, enabling simplified debugging and performance tuning in production systems.

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