Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 4 SnapStart + DSQL request priming

Introduction In part 1 , we introduced our sample application. In part 2 , we measured the performance (cold and warm start times) of the Lambda function without any optimizations. We observed quite a large cold start time, especially if we use the Hibernate ORM framework. Using this framework also significantly increases the artifact size. In part 3 , we introduced AWS Lambda SnapStart as one of the approaches to reduce the cold start times of the Lambda function. We observed that by enabling the SnapStart on the Lambda function, the cold start time goes down significantly for both sample applications. It's especially noticeable when looking at the "last 70" measurements with the snapshot tiered cache effect. The biggest impact of just enabling the SnapStart is on the application using the Hibernate. In this part of our article series, we'll introduce how to apply Lambda SnapStart priming techniques. We'll start with the database (in our case, Aurora DSQL) request priming. The goal is