Damon Cortesi, et al, announce serverless EMR is now in preview:
Today we’re happy to announce Amazon EMR Serverless, a new option in Amazon EMR that makes it easy and cost-effective for data engineers and analysts to run petabyte-scale data analytics in the cloud. With EMR Serverless, you can run applications built using open-source frameworks such as Apache Spark, Hive, and Presto, without having to configure, manage, optimize, or secure clusters. EMR Serverless automatically provisions and scales the compute and memory resources required by your applications, and you only pay for the resources that your applications use.
In this post, we discuss the benefits of EMR Serverless, walk you through the core concepts of EMR Serverless and how you can use it, and show you a quick demo.
If you’re already using EMR for ephemeral work—that is, using a Spark cluster to perform data transformations and then shutting it down—this makes a lot of sense as long as there’s not a major difference in cost.