Microservices are a big deal. They can give us some pretty big wins for our architectures and teams, but microservices have plenty of costs too. As microservices, serverless, and other distributed systems architectures become even more prevalent in the industry, it's critical that we internalize their problems and strategies for solving them. In this article, we'll look at one example of the many tricky issues that network boundaries can introduce: timeouts. And before you flee in horror from the words "distributed systems," remember that even a tiny React app with a Node backend, or a simple iOS client talking to AWS Lambda, represents a distributed system. As you read this blog post, you are already participating in a distributed system that includes your web browser, a content delivery network, and a file storage system. In terms of background, I'll assume for this post that you understand how to make API calls and handle their success and failure in a language of your choice, but it doesn't matter whether those API calls are synchronous or asynchronous, HTTP or not.


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This article is related to


Architecture,Microservices,Error Handling