THE NEED FOR CHANGE
Legacy Java complexity increased modernization pressure and resource demands
Operating in cloud security and compliance, the business needed to maintain platform performance, security, and long-term support. Its Java 8 environment faced the end of public updates, while the migration involved more than 40 backend modules, over 100 APIs, and a codebase exceeding 4 million lines.
- Security exposure from legacy Java environment
- Complex dependencies across 40+ backend modules
- Large-scale codebase modernization effort
- Compressed timelines for migration
- Extensive testing for security and stability
- Limited engineering capacity
Comprehensive testing and limited engineering capacity added further pressure to the modernization effort. The business needed an efficient capability to accelerate backend modernization while maintaining security, performance, and stability.
ARCHITECTING THE TRANSFORMATION
An accelerated capability for backend modernization
We established an AI-assisted approach to streamline the migration from Java 8 to Java 17 while supporting code analysis, refactoring, and validation. Amazon Q analyzed the existing codebase, identified incompatible patterns, and recommended replacements for Java 17. It also supported regression testing to validate performance and stability following the migration. The approach helped address deprecated APIs and vulnerabilities while managing dependencies across the large codebase. By combining automated analysis and refactoring with engineering expertise, the modernization was completed with significantly reduced project staffing.
THE IMPACT
Stronger security, improved efficiency, greater platform stability
Improved runtime efficiency
Strengthened security posture
Minimized operational costs
Supported long-term platform stability
>60% reduction in storage footprint
