Title

AWS re:Invent 2023 - Automate app upgrades & maintenance using Amazon Q Code Transformation (DOP229)

Summary

Amazon Q Code Transformation is a new feature designed to automate application upgrades and maintenance.
Vishwesh Saraswathi, the principal product manager, and Jas Chhabra, the senior SDM, introduced and discussed the feature.
The feature addresses the challenge of balancing application updates with productive business work, which often leads to technical debt and security issues.
Amazon Q Code Transformation leverages Amazon's 17 years of experience, AI capabilities, and knowledge bases to automate the upgrade process.
The feature currently supports Java upgrades (Java 8 and Java 11 to Java 17) with plans to include more versions and languages.
The process involves uploading code to a secure cloud environment, analyzing it, applying upgrades, and iterating through build errors automatically.
Developers receive a patch file or diff to apply to their IDE, maintaining control over the final changes.
The system uses a combination of rule-based upgrades, program analysis, and LLM (Large Language Models) techniques to build a knowledge base and apply necessary changes.
The feature is in preview, with limitations such as primarily supporting open source packages and not yet handling internal dependencies.
Future enhancements include support for upgrading from Windows .NET to .NET Core on Linux.
The tool has been used internally at Amazon to migrate over 1,000 Java apps, saving significant developer effort.

The Amazon Q Code Transformation tool aims to significantly reduce the time and effort required for application upgrades, which traditionally are time-consuming and require extensive research and manual work.
By automating the upgrade process, developers can focus on more value-adding activities such as building new features and improving customer value.
The tool's ability to analyze and understand codebases, even those not written by the current team, can greatly reduce the learning curve and potential errors during upgrades.
The integration with Amazon Q plus Code Whisperer toolkit plugin suggests a seamless experience within developers' existing workflows.
The use of AI, specifically LLMs, in conjunction with a comprehensive knowledge base, represents a sophisticated approach to automating code transformation tasks.
The emphasis on security and compliance indicates that Amazon is aware of the importance of keeping applications up-to-date with the latest security patches and performance improvements.
The future capability to assist with migrations from Windows .NET to .NET Core on Linux shows Amazon's commitment to supporting a wide range of technologies and platforms.
The internal use case of upgrading 1,000+ Java applications at Amazon demonstrates the tool's effectiveness and potential impact on developer productivity at scale.