Home icon

Optimizing cold start performance of AWS Lambda using advanced priming strategies with SnapStart

Compute Blog



This article discusses optimizing cold start performance for AWS Lambda functions using advanced priming strategies with SnapStart, focusing on Java and Spring Boot applications.

  • SnapStart can reduce Lambda function startup time from several seconds to sub-second
  • Two priming strategies are introduced:
    • Invoke Priming: Executes application endpoints during snapshot creation
    • Class Priming: Preloads classes without triggering business logic
  • Performance improvements observed:
    • ON_DEMAND startup: 6.1 seconds
    • SnapStart without priming: 1.4 seconds
    • SnapStart with class priming: 1.1 seconds
    • SnapStart with invoke priming: 0.8 seconds
  • Developers should choose priming strategy based on specific use case and potential side effects

The article provides a detailed implementation guide and sample code for implementing these optimization techniques in Java Lambda functions.



Go to article

The AWS News Feed is currently looking for gold sponsors. If you want to support the AWS community and reach a large audience of AWS professionals, consider sponsoring the AWS News Feed.

Related articles

May 13
2025
Improving SnapStart Performance in .NET Lambda Functions
Aug 19
2025
Under the hood: how AWS Lambda SnapStart optimizes function startup latency
Nov 18
2024
AWS Lambda now supports SnapStart for Python and .NET functions
Jul 18
2024
AWS Lambda now supports SnapStart for Java functions that use the ARM64 architecture

The AWS News Feed is currently looking for silver sponsors. If you want to support the AWS community and reach a large audience of AWS professionals, consider sponsoring the AWS News Feed.