performance

S3 Table Buckets vs Redshift

AWS released S3 Table Buckets at re:Invent 2024, and at release they were pretty much only usable with Elastic Map Reduce. However, over the past year, the S3 Tables team has been making improvements. And while there are still some limitations, S3 Tables with Athena gives a user experience similar to traditional data warehouses such as Redshift.

Which leads to the question: can Athena and S3 Tables be a cost-effective replacement for Redshift? In this post I show how to use S3 Tables, and run some performance comparisons to answer that question.

Migrating Java Applications to Kubernetes

Your CTO messages you out of the blue one day: How much effort would it be to run XYZ on Kubernetes? Shudder. Although there are some nuances to the process, it is fairly straightforward. This article assumes some knowledge of containers, Kubernetes, and JVM applications. Our goal is to migrate the application with as few … Read More

What’s the point of Lambda SnapStart?

Lambda SnapStart is intended to improve the cold start time for a Lambda function. It’s been available for Java workloads since 2022, and was recently released for Python and .Net workloads. It works by running the initialization code of your Lambda function when you release a version, and then storing an image of the Lambda execution environment. Cold starts load this image rather than running the initialization themselves. Given that cold starts happen unpredictably, and may be measured in seconds, this seems like a win-win situation.

The reality, as usual, is more nuanced. SnapStart introduces its own cold start delays, as it loads the image into the runtime. And it increases the time and effort of deployment. In this post I drill down into the nuance, so that you can decide whether it’s a worthwhile choice fo your project.