Serverless Tip: Don’t overpay when waiting on remote API calls

Our serverless applications become a lot more interesting when they interact with third-party APIs like Twilio, SendGrid, Twitter, MailChimp, Stripe, IBM Watson and others. Most of these APIs respond relatively quickly (within a few hundred milliseconds or so), allowing us to include them in the execution of synchronous workflows (like our own API calls).  Sometimes we run these calls asynchronously as background tasks completely disconnected from any type of front end user experience.

Regardless how they’re executed, the Lambda functions calling them need to stay running while they wait for a response. Unfortunately, Step Functions don’t have a way to create HTTP requests and wait for a response. And even if they did, you’d at least have to pay for the cost of the transition, which can get a bit expensive at scale. This may not seem like a big deal on the surface, but depending on your memory configuration, the cost can really start to add up.

In this post we’ll look at the impact of memory configuration on the performance of remote API calls, run a cost analysis, and explore ways to optimize our Lambda functions to minimize cost and execution time when dealing with third-party APIs.

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