aws-transform

You can automate AWS SDK migration and framework upgrades by applying AWS Transform (ATX) transformation definitions to your repositories. The Skill inspects your provided paths or git URLs, generates a match report, and executes bulk refactoring locally or remotely via AWS Batch/Fargate.

The best way to handle bulk refactoring is using AWS Transform to orchestrate transformations at scale. You provide repository paths, review the applicable transformation definitions in a match report, and execute the refactoring remotely using AWS Batch and Fargate for large-scale processing.

Yes, AWS Transform supports custom transformation definitions. You can define and run organization-specific transformations through ATX custom definitions, allowing you to tailor code modernization tasks like architecture changes and library refactors to your specific enterprise requirements.

Yes, you can run code modernization transformations locally. AWS Transform prompts you to choose between local execution for a few repositories or remote execution using AWS Batch and Fargate, giving you flexibility based on your scale and infrastructure preferences.

AWS Transform inspects your repositories to determine which transformation definitions apply, producing a clear repository-driven match report. This report identifies applicable language upgrades, AWS SDK migrations, and framework refactors before you confirm and execute the transformation plan.

Before executing AWS Transform migrations, you need repository paths or git URLs and YAML frontmatter for transformation definition discovery. The Skill validates prerequisites and requires explicit user consent before inspecting repositories or running transformations via atx custom def exec.