Implement error tracking with Sentry for automatic exception monitoring, release tracking, and performance issues. Use when setting up error monitoring, tracking bugs in production, or analyzing application stability.

Error Tracking Table of Contents [Overview]( overview) [When to Use]( when to use) [Quick Start]( quick start) [Reference Guides]( reference guides) [Best Practices]( 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: Reference Guides Detailed implementations in the references/ directory: Guide Contents [Sentry Setup](references/sentry setup.md) Sentry Setup, Node.js Sentry Integration [Express Middleware Integration](references/express middleware integration.md) Express Middleware Integration [Python Sentry Integration](references/python sentry integration.md) Python Sentry Integration [Source Maps and Release Management](references/source maps and release management.md) Source Maps and Release Management, CI/CD Release Creation [Custom Error Context](references/custom error context.md) Custom Error Context [Performance Monitoring](references/performance monitoring.md) 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

error-tracking