SuperAPI AI Directory

error-tracking

Deployment & operations

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Updated 10-15 12:51

About this skill

Error Tracking

Table of Contents

  • Overview
  • When to Use
  • Quick Start
  • Reference Guides
  • Best Practices

Overview

Set up comprehensive error tracking with Sentry to automatically capture, report, and analyze exceptions, performance issues, and application stability.

When to Use

  • Production error monitoring
  • Automatic exception capture
  • Release tracking
  • Performance issue detection
  • User impact analysis

Quick Start

Minimal working example:

npm install -g @sentry/cli
npm install @sentry/node @sentry/tracing
sentry init -d

Reference Guides

Detailed implementations in the references/ directory:

Guide Contents
Sentry Setup Sentry Setup, Node.js Sentry Integration
Express Middleware Integration Express Middleware Integration
Python Sentry Integration Python Sentry Integration
Source Maps and Release Management Source Maps and Release Management, CI/CD Release Creation
Custom Error Context Custom Error Context
Performance Monitoring Performance Monitoring

Best Practices

✅ DO

  • Set up source maps for production
  • Configure appropriate sample rates
  • Track releases and deployments
  • Filter sensitive information
  • Add meaningful context to errors
  • Use breadcrumbs for debugging
  • Set user information
  • Review error patterns regularly

❌ DON'T

  • Send 100% of errors in production
  • Include passwords in context
  • Ignore configuration for environment
  • Skip source map uploads
  • Log personally identifiable information
  • Use without proper filtering
  • Disable tracking in production