logging-observability

Implement structured logging, OpenTelemetry tracing, and RED/USE metrics.

11|4|Updated Feb 9, 2026
One-click install
npx skills add https://github.com/wpank/ai --skill logging-observability-wpank
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: logging-observability
Source: https://github.com/wpank/ai/tree/main/skills/tools/logging-observability
Command: npx skills add https://github.com/wpank/ai --skill logging-observability-wpank

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides patterns and best practices for implementing robust logging, distributed tracing, and metrics collection, enabling developers to build highly observable and maintainable systems.

Core Features & Use Cases

  • Structured Logging: Implement consistent JSON logging with essential fields and context enrichment.
  • Distributed Tracing: Set up and utilize OpenTelemetry for tracing requests across services.
  • Metrics Collection: Employ RED and USE methods for monitoring request rates, errors, durations, and resource utilization.
  • Use Case: When developing a new microservice, use this Skill's guidelines to ensure it emits structured logs, participates in distributed traces, and exposes key metrics for monitoring and alerting.

Quick Start

Implement structured JSON logging for your Node.js application using the Pino library.

Frequently Asked Questions about logging-observability

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

FAQPage Schema
How do I implement structured logging for a microservice?

Structured logging is implemented by emitting consistent JSON logs enriched with essential context fields. Using libraries like Pino for Node.js, you ensure logs are machine-readable and contain necessary details for effective system debugging.

What is the RED method for monitoring system metrics?

The RED method is a metrics collection strategy for monitoring system health by tracking request Rates, Errors, and Durations. It provides a standardized approach to analyze performance bottlenecks and monitor microservice utilization.

How do I set up distributed tracing with OpenTelemetry?

Setting up distributed tracing with OpenTelemetry involves instrumenting code to trace requests across services, managing context propagation, and configuring trace sampling strategies. This enables developers to debug distributed requests and analyze performance bottlenecks.

Does this provide guidelines for log levels and trace sampling strategies?

Yes, it provides specific log level guidelines to standardize severity reporting and trace sampling strategies to manage telemetry overhead. These practices help balance observability data volume with effective system monitoring.

What is the best way to monitor microservice health using Prometheus and Grafana?

The best way to monitor microservice health is using a stack like Prometheus and Grafana to collect and visualize metrics. This enables comprehensive monitoring of system health, request rates, errors, durations, and resource utilization.