"In today's rapidly evolving software landscape, maintaining and modernizing Java applications is a critical challenge for many organizations. As new Java versions are released and best practices evolve, the need for efficient code transformation becomes increasingly important. Organizations today face significant challenges when modernizing their Java applications. Legacy codebases often contain outdated patterns, deprecated APIs, and inefficient implementations that hinder performance and maintainability."
"Traditional manual refactoring approaches are time-consuming, error-prone, and difficult to scale across large codebases. In addition, as developers spend more time on new development and deployment, the volume of technical debt continues to rise, requiring transformation of legacy code at-scale. AWS Transform custom addresses these challenges through intelligent automation, providing AWS-managed transformations - standardized transformation packages for common scenarios like Java version upgrades."
Organizations face legacy Java codebases with outdated patterns, deprecated APIs, and inefficient implementations that hinder performance and maintainability. Manual refactoring is time-consuming, error-prone, and hard to scale across large codebases, allowing technical debt to grow as development focus shifts to new features. AWS Transform custom applies agentic AI to automate large-scale code modernization, including language version upgrades, API migrations, and framework updates. AWS-managed, standardized transformation packages provide tested patterns for common scenarios such as Java version upgrades and enable execution at scale. Customers can create custom user-defined transformations to address organization-specific technical debt across languages and frameworks. The agent learns from executions to improve over time.
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