Aurora Serverless v2: The Good, the Better, and the Possibly Amazing

Three years ago at re:Invent 2017, AWS announced the original Amazon Aurora Serverless preview. I spent quite a bit of time with it, and when it went GA 9 months later, I published my thoughts in a post titled Aurora Serverless: The Good, the Bad and the Scalable.

If you read the post, you’ll see that I was excited and optimistic, even though there were a lot of missing features. And after several months of more experiments, I finally moved some production workloads onto it, and had quite a bit of success. Over the last 18 months, we’ve seen some improvements to the product (including support for PostgreSQL and the Data API), but there were still loads of problems with the scale up/down speeds, failover time, and lack of Aurora provisioned cluster features.

That all changed with the introduction of Amazon Aurora Serverless v2. I finally got access to the preview and spent a few hours trying to break it. My first impression? This thing might just be a silver bullet!

I know that’s a bold statement. 😉 But even though I’ve only been using it for a few hours, I’ve also read through the (minimal) docs, reviewed the pricing, and talked to one of the PMs to understand it the best I could. There clearly must be some caveats, but from what I’ve seen, Aurora Serverless v2 is very, very promising. Let’s take a closer look!

Update December 9, 2020: I’ve updated the post with some more information after having watched the “Amazon Aurora Serverless v2: Instant scaling for demanding workloads” presentation by Murali Brahmadesam (Director of Engineering, Aurora Databases and Storage) and Chayan Biswas (Principle Product Manager, Amazon Aurora). The new images are courtesy of their presentation.

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