Resolving AWS API Gateway 500 Internal Server Error

The AWS API Gateway is a powerful tool that allows developers to create, manage, and secure APIs at any scale. But, like any online service, it can occasionally throw a 500 Internal Server Error. This common HTTP response code indicates that an unexpected condition has occurred, preventing the server from fulfilling the request.

What Causes Internal Server Error in API Gateway?

The 500 status code might be the most used and most generic HTTP error on this planet. It can be caused by many things. Here are a few possibilities:

  • Lambda function failures: If you get it from an API endpoint that integrates with AWS Lambda, it usually means your code buggy.
  • Inconsistent error mapping: Many of the errors we talked about here can become a 500 error when finally landing on your client as a response. You’ll get a “limit exceeded,” but it will have a 500 status code instead of 429. So you have to extract the right error out of this response, check what the real cause is, and then look at how to solve it.
  • Timeout issues: If the API request exceeds the set timeout limit, it can return a 500 Internal Server Error.
  • Misconfiguration: Incorrect settings in your API Gateway could be responsible for throwing a 500 Internal Server Error.

Since the error can be anything really, a retry can technically solve that problem, but usually, it doesn’t. If you monitor your system carefully and get one of these every few million requests, it could be that cosmic rays flipped some bits or whatever. Still, if you see a 500 status code more often than that, it’s crucial to investigate; it can very well point to an inconsistency that will blow up sooner or later.

How Do I Debug AWS API Gateway 500 Errors?

Debugging the AWS API Gateway involves using various AWS tools to hunt down the error and fix it.

  • DashbirdMonitor, debug and improve API Gateways quick and easy all in one place. Dashbird gives developers a real-time overview of all API executions, detects errored invocations within them and lets you quickly identify root cause. It’s free for the first 1 million invocations per month.
  • CloudWatch logs: Use AWS CloudWatch logs to track, analyze, and store logs from your AWS resources. CloudWatch logs help detect and diagnose errors within your API Gateway.
  • X-Ray: AWS X-Ray, AWS’s distributed tracing system, visualizes and analyzes your applications. It helps identify areas that need improvement or have errors.

With the right strategies, you can resolve these issues effectively. For a deeper understanding of server errors and API Gateway, visit What is AWS API Gateway? and explore more about the various pros and cons of using an API Gateway.

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Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.

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Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.