Does it work with unstructured text logs?

While it offers strategies for parsing, the skill strongly recommends and provides implementation details for structured JSON logging to ensure logs are machine-queryable and more reliable.

Which logging platforms are compatible with these patterns?

The query patterns provided are optimized for CloudWatch Logs Insights, Datadog, and Elasticsearch (ELK stack), focusing on common failure modes like error spikes and auth failures.

Can it help identify Node.js memory leaks?

Yes, it includes specific patterns for monitoring process-level warnings, such as MaxListenersExceededWarning, which are common indicators of EventEmitter listener leaks.

How does this skill help with distributed tracing?

It provides patterns for generating and propagating correlation IDs through headers, allowing you to link logs from multiple services to a single user request for full-path reconstruction.

Node.js Log Analysis & Incident Response

Name: Node.js Log Analysis & Incident Response
Author: chavangorakh1999

bychavangorakh1999

0•

Analytics & Monitoring

Simplifies incident investigation by providing structured log parsing strategies, correlation ID tracing, and distributed query patterns.

The Log Analysis skill empowers Claude to efficiently navigate complex application logs during critical incident investigations. It provides domain-specific guidance on implementing structured logging with Pino, managing correlation ID propagation for distributed tracing, and executing optimized query patterns for CloudWatch and Elasticsearch. By standardizing log forensics, this skill helps developers move quickly from noise to signal, allowing for the reconstruction of request paths across multiple services to identify root causes in modern distributed systems.

Key Features

01Provides correlation ID strategies to trace requests across microservices architecture.

02Includes ready-to-use CloudWatch and Elasticsearch queries for error spikes and latency.

03Standardizes distributed trace reconstruction to identify bottlenecks in complex request paths.

04Monitors Node.js-specific events like unhandled promise rejections and memory leaks.

050 GitHub stars

06Implements structured JSON logging patterns using Pino for machine-queryable data.

Use Cases

01Optimizing application performance by identifying P99 latency bottlenecks via log queries.

02Investigating production incident root causes by correlating logs across distributed services.

03Debugging silent failures like unhandled promise rejections or EventEmitter leaks in Node.js.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add chavangorakh1999/sde-skills log-analysis

For use in Claude.ai and ChatGPT

Key Features

01Provides correlation ID strategies to trace requests across microservices architecture.

02Includes ready-to-use CloudWatch and Elasticsearch queries for error spikes and latency.

03Standardizes distributed trace reconstruction to identify bottlenecks in complex request paths.

04Monitors Node.js-specific events like unhandled promise rejections and memory leaks.

050 GitHub stars

06Implements structured JSON logging patterns using Pino for machine-queryable data.

Use Cases

01Optimizing application performance by identifying P99 latency bottlenecks via log queries.

02Investigating production incident root causes by correlating logs across distributed services.

03Debugging silent failures like unhandled promise rejections or EventEmitter leaks in Node.js.