What are wide events in logging?

Wide events, also known as canonical log lines, are single, context-rich log entries emitted at the end of a request that contain all relevant technical, business, and environmental data for that specific transaction.

Why does this skill emphasize high cardinality fields?

High cardinality fields like user IDs or request IDs are critical for modern observability because they allow you to filter and group logs precisely to identify issues affecting specific users or unique requests.

Does this skill work with specific logging libraries?

The principles provided are library-agnostic and apply to any language or logging framework. It focuses on the strategy of data collection and structure rather than specific syntax.

How do wide events improve debugging compared to traditional logging?

Traditional logs are often scattered across multiple lines, making it hard to reconstruct the state of a request. Wide events put all context in one place, allowing you to see exactly what happened in a single query.

Logging Best Practices

Name: Logging Best Practices
Author: trancong12102

bytrancong12102

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Analytics & Monitoring

Implements high-performance observability patterns using wide events and canonical log lines for improved debugging and analytics.

This skill guides Claude in implementing modern observability standards by shifting from scattered, noisy logs to context-rich wide events. By consolidating request data, high-cardinality IDs, business context, and environment details into a single structured JSON event per service hop, it enables developers to perform deep analytics and resolve complex production issues. It is essential for teams looking to adopt the canonical log line pattern popularized by companies like Stripe and Honeycomb to improve system visibility.

Key Features

01High-cardinality tracking for specific user and request IDs

02Business context integration including subscription tiers and cart values

03Wide event implementation for consolidated request logging

041 GitHub stars

05Standardized JSON structure and middleware-based logging patterns

06Environment characteristic tagging for deployment and region correlation

Use Cases

01Correlating application errors with specific deployment versions and user segments

02Transforming scattered console.log calls into structured observability data

03Implementing canonical log lines in microservice architectures

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add trancong12102/ccc logging-best-practices

For use in Claude.ai and ChatGPT

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