Error Handling Patterns for Web Applications

Proper error handling is the difference between an application that fails gracefully and one that crashes mysteriously. Users should see helpful error messages, not blank screens or cryptic codes. Your backend should log detailed error information for debugging while returning safe messages to clients. AI-generated code often ignores error handling entirely, using the happy path only. This creates applications that work during demos but fail in production.

React Error Boundaries catch JavaScript errors in the component tree and display fallback UI instead of crashing the entire page. Create an Error Boundary component that wraps major sections of your application. Display a user-friendly error message with a retry option rather than a blank screen. Log errors to an error tracking service like Sentry for debugging. Place Error Boundaries at strategic points so that an error in one section does not take down the entire page.

Your frontend should handle every possible API response gracefully. Network failures, timeout errors, server errors, and validation errors all need different handling. Use a centralized API client that handles common error scenarios like expired authentication tokens. Display loading states while requests are pending and error states when they fail. Implement retry logic with exponential backoff for transient failures. Never show raw error messages from the server to end users.

Create a structured error hierarchy with a base error class that all custom errors extend. Include error codes, HTTP status codes, and user-facing messages. Use middleware to catch unhandled errors and format them consistently. Distinguish between operational errors that you expect and programming errors that indicate bugs. Operational errors should be handled gracefully, while programming errors should be logged and trigger alerts.

Implement structured logging with consistent formats across your application. Include request IDs that trace a request from the frontend through the backend. Use log levels appropriately with error for failures, warn for concerning situations, info for significant events, and debug for development details. Send logs to a centralized service like Datadog, Logtail, or CloudWatch. Set up alerts for error rate spikes so you know about issues before your users report them.

Integrate an error tracking service like Sentry, Bugsnag, or Rollbar to capture and aggregate errors automatically. These services group similar errors, track their frequency, and provide stack traces with source maps for debugging. Set up alerts for new errors and error rate increases. Review your error dashboard regularly to identify and fix recurring issues. The investment in error tracking pays for itself many times over by reducing time spent debugging production issues.

Adding robust error handling to an existing application touches nearly every file and requires understanding the full request lifecycle from user interaction through API calls to database operations. AI-generated code is particularly weak in this area, often using empty catch blocks or no error handling at all. SpringCode adds comprehensive error handling including Error Boundaries, API error management, structured backend errors, and error tracking integration.