Review: AWS Lambda redefines 'on demand'

Amazon’s simple, scalable compute service runs your functions whenever needed, but is limited to Java, Python, and Node.js

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At a Glance
  • Amazon AWS Lambda

What if you could simply define a function to live in the cloud and handle the designated workloads, and not have to worry about provisioning servers, allocating RAM, scaling the number of instances, or configuring load balancing? How great would that be? In fact it is pretty great, as you can discover by using AWS Lambda.

AWS Lambda is a compute service. You can set up Lambda functions to respond to events, such as changes to data, asynchronously. You can call them directly or through an API gateway, synchronously. And you can use them to respond to HTTP(S) requests, synchronously.

AWS Lambda currently supports three computer language environments for handler functions: Node.js (JavaScript); Java code packaged as Jar or Zip files; and Python. Python support was recently added, unveiled at AWS re:Invent 2015. In the same presentation, CTO Werner Vogel mentioned that Lambda is now the fastest-growing service at AWS.

Amazon touts Lambda’s ability to extend other AWS services with custom logic; its ability to help you build custom back-end services; its completely automated administration; its built-in fault tolerance; its automatic scaling; its integrated security model; its invitation to bring your own code; its pay-per-use business model; and its flexible resource model.

To help you grok Lambda, I’ve curated some questions and answers about the service.

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