Nothing ruins a good application faster than poor error handling. I've seen applications crash because of a single unhandled error, leaving users confused and frustrated. Good error handling isn't just about preventing crashes—it's about creating a smooth experience even when things go wrong.

When I first started building applications, I focused on the happy path. I'd write code assuming everything would work perfectly. But in production, things go wrong. APIs fail, databases timeout, users enter invalid data. You need to handle all of these cases gracefully.

Error handling basics

The first rule of error handling is to never let errors crash your application silently. If something goes wrong, you need to know about it. But you also don't want to show users technical error messages that confuse them.

I usually have different error handling for different layers of my application. At the API level, I catch errors and return appropriate HTTP status codes and messages. At the UI level, I catch errors and show user-friendly messages. And I always log detailed errors on the server where I can see them.

Try-catch blocks are your friend, but you need to use them wisely. Don't just catch everything and ignore it. Catch specific errors and handle them appropriately. If you're calling an external API, catch network errors and timeout errors separately. Each type of error might need different handling.

Structured error responses

When your API returns an error, make it consistent. I always return errors in the same format: a status code, an error type, a message, and sometimes additional details. This makes it easier for frontend developers to handle errors, and it makes debugging easier too.

For example, if a user tries to create an account with an email that's already registered, I return a 409 Conflict status with a clear message. If they send invalid data, I return a 400 Bad Request with details about what's wrong. Consistent error formats make everything easier to work with.

User-friendly error messages

The error message you show users should be helpful, not technical. Instead of "SQLSTATE[23000]: Integrity constraint violation," show "This email is already registered." Users don't care about database errors—they care about what went wrong and what they can do about it.

I keep a mapping of technical errors to user-friendly messages. When an error occurs, I look it up and return the appropriate message. This takes a bit of work upfront, but it makes a huge difference in user experience.

For errors that users can fix, tell them how. "Password must be at least 8 characters" is better than just "Invalid password." Give users actionable information so they can correct the problem.

Logging is essential

Good logging is crucial for debugging production issues. When something goes wrong, you need to be able to figure out what happened. But logging everything can be overwhelming, so you need to be strategic about what you log.

I usually log errors with enough context to understand what happened. That means including the user ID, the request path, the parameters, and a stack trace. I also log important events like user logins, payment processing, and other critical actions.

Use different log levels appropriately. Debug logs are for development. Info logs are for important events. Warning logs are for things that might be problems. Error logs are for actual errors. This helps you filter logs and focus on what matters.

Error tracking services

For production applications, I always use an error tracking service like Sentry, Rollbar, or Bugsnag. These services automatically capture errors, collect context, and notify you when problems occur. They're invaluable for catching issues you might otherwise miss.

Error tracking services do more than just log errors. They group similar errors together, show you how many users are affected, and help you prioritize which errors to fix first. They also capture the full context—the user's browser, their location, what they were doing when the error occurred.

Setting up error tracking is usually pretty straightforward. You install a library, add a few lines of code, and you're done. The service handles the rest. It's one of those things that pays for itself the first time it catches a critical bug.

Monitoring and alerts

Error tracking is reactive—it tells you when something has already gone wrong. Monitoring is proactive—it helps you catch problems before they become critical. I monitor things like response times, error rates, database query performance, and server resource usage.

I set up alerts for things that indicate problems. If error rates spike, I want to know. If response times get slow, I want to know. If database connections are maxing out, I want to know. The key is to set thresholds that catch real problems without alerting on every minor fluctuation.

False alarms are the enemy of good monitoring. If you get too many alerts for things that aren't actually problems, you'll start ignoring them. Then when a real problem occurs, you might miss it. Set your thresholds carefully, and adjust them based on what you actually see.

Health checks

Health check endpoints are simple but useful. They're endpoints that return whether your application is working correctly. Monitoring services can ping these endpoints regularly, and if they don't respond or return an error, you know something's wrong.

A good health check verifies that critical components are working. It might check that the database is reachable, that external APIs are responding, or that required services are running. If any of these fail, the health check fails, and you get alerted.

I usually have a simple health check that just returns 200 OK, and a more detailed one that checks individual components. The simple one is fast and good for basic uptime monitoring. The detailed one is slower but gives you more information about what's wrong.

Graceful degradation

Sometimes things fail, and you can't fix them immediately. But that doesn't mean your entire application has to stop working. Graceful degradation means your application continues to function, maybe with reduced features, when some components fail.

For example, if an external API is down, maybe you can show cached data instead. If image processing fails, maybe you can show a placeholder. The key is to think about what happens when dependencies fail and handle those cases gracefully.

This requires thinking about your application's dependencies and which ones are critical. Some features might be nice to have but not essential. If those fail, you can disable them without breaking the core functionality.

Testing error scenarios

It's easy to test the happy path, but you also need to test what happens when things go wrong. What happens when the database is slow? What happens when an external API times out? What happens when users send invalid data?

I try to test these scenarios, either through automated tests or by intentionally breaking things in a staging environment. This helps me find edge cases and make sure error handling actually works. It's better to find these issues in testing than in production.

The bottom line

Error handling and monitoring aren't glamorous, but they're essential. Users don't notice good error handling—they just see an application that works smoothly. But they definitely notice bad error handling when things break in confusing ways.

Start with the basics: proper try-catch blocks, user-friendly error messages, and good logging. Then add error tracking and monitoring. As your application grows, you can add more sophisticated error handling and monitoring strategies.

The goal isn't to prevent all errors—that's impossible. The goal is to handle errors gracefully when they occur and catch problems quickly so you can fix them. Good error handling and monitoring give you confidence that you'll know when something goes wrong and can fix it before it impacts too many users.