Error Handling
What is error handling?
Error handling is the systematic approach to managing errors and failures in your code or system, including understanding error codes, implementing retry logic, and ensuring your system responds appropriately when things go wrong. Robust error handling is essential for production systems to prevent issues from cascading and to ensure reliability for users.
Without proper error handling, problems like feedback getting stuck in queues or systems failing unpredictably become common.
What makes error handling robust?
Robust error handling includes several key components. You need to understand the specific error codes your system might encounter and determine the best way to respond to each type of error. Some errors should trigger automatic retries, while others indicate problems that won't be fixed by trying again.
Better error handling means building in proper retry logic so temporary failures don't cause permanent problems. It means ensuring your system degrades gracefully when things go wrong rather than cascading failures. When you migrate from a tool with basic error handling to one with more sophisticated capabilities—like moving from Zapier to AWS Step Functions—you gain reliability through these improved error handling features.
How do teams learn to implement error handling?
Error handling is a technical skill you can develop systematically. Start by learning the common patterns for error handling in the tools you're using, such as Lambdas and Step Functions. Understanding these patterns gives you a framework for developing an error handling plan.
Once you've implemented your plan, you can use code review—whether from teammates or AI assistants—to critique your approach from an error handling perspective. This iterative refinement helps you build production-grade systems that are rock solid. The combination of learning patterns, implementing systematically, and refining through review makes error handling accessible even if you're new to building technical systems.
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