Modernizing Data Centers without Refactoring: Smart Solutions for a Seamless Transition

Data centre modernization without refactoring can be achieved through smart lift-and-shift, containerization, infrastructure virtualization, and high-performance network storage. This approach enables organisations to migrate to the cloud or adopt hybrid solutions without compromising security, predictability, and performance. It has resulted in significant gains in operational efficiency and response time, including a 30% reduction in operating costs, a 1.5 percentage point increase in average availability, and up to 5 times faster migration time. Real-world use cases include financial institutions, public agencies, and manufacturers that have successfully applied this model.

Data centre modernization without refactoring can be achieved through smart lift-and-shift, containerization, infrastructure virtualization, and high-performance network storage. This approach enables organizations to migrate to the cloud or adopt hybrid solutions without compromising security, predictability, and performance. It has resulted in significant gains in operational efficiency and response time, including a 30% reduction in operating costs, a 1.5 percentage point increase in average availability, and up to 5 times faster migration time. Real-world use cases include financial institutions, public agencies, and manufacturers that have successfully applied this model.

One notable example of leveraging these techniques is EPAM's modernization journey with Amazon Q Developer. Legacy code modernization presents significant challenges for organizations looking to stay competitive in today’s rapidly evolving digital landscape. Organizations face the dual challenge of maintaining business continuity while modernizing their legacy systems for cloud environments. This transformation requires organizations to carefully navigate between preserving essential business logic and implementing modern architectural patterns.

EPAM, an AWS Premier Partner, collaborated with one of the largest privately held companies in the direct-selling industry to modernize their legacy applications to AWS Cloud. The modernization initiative focused on multiple business-critical applications, primarily built in Java 8 with Oracle Database backend, that serve as the backbone for the client’s operations across multiple product segments including nutrition, health and beauty, home care, and personal care.

Amazon Q Developer, an AI code assistant, seamlessly integrated into the development pipeline to address these challenges. This innovative AI code assistant helped teams tackle various tasks, from generating new features, automating language upgrades, and refactoring legacy code to fixing bugs and automating deployments. By providing detailed explanations for its code suggestions while maintaining high quality standards, Amazon Q Developer significantly improved developer efficiency across the entire software development lifecycle, resulting in substantial time and effort savings.

EPAM engineers utilized Amazon Q Developer to transform these complex legacy systems into modern cloud-native architectures on AWS. The tool enabled the team to autonomously perform a range of tasks—from implementing new microservices and documenting code to testing, reviewing, and refactoring Java code, as well as performing critical platform upgrades.

Amazon Q Developer played a crucial role in boosting EPAM’s development productivity. By automating routine tasks and providing intelligent code suggestions, the tool enabled developers to focus on more strategic aspects of the modernization project.

Use Case 1: Generating New API Endpoints
Creating new API endpoints traditionally requires developers to invest 1-2 days per endpoint, involving multiple steps from designing the API contract to writing unit tests and documentation. Using Amazon Q Developer, the team dramatically accelerated this process for three new API endpoints in an existing microservice. Q Developer efficiently generated the initial code implementation along with comprehensive unit test coverage, requiring only minor modifications such as renaming variables, enhancing error handling, and refining test cases. The unit tests generated proved remarkably reliable with minimal adjustments needed. Along with this, Q Developer also generated comprehensive comments/documentation of the code improving the maintainability. This reduced the total development time to just 4 hours for all three endpoints – a 70% time saving compared to the traditional approach, allowing developers to focus on fine-tuning business logic rather than writing boilerplate code.

Use Case 2: Integrating Legacy Systems
Integrating a legacy monolith application with modern microservices traditionally requires developers to manually write extensive integration code, taking 1-2 weeks per integration point. Amazon Q Developer accelerated this process by automatically generating REST API client code in the monolith to consume microservice endpoints, along with data transfer objects (DTOs), error handling, and retry logic with integration test templates. While developers still needed to validate business rules and fine-tune error scenarios, Q Developer’s ability to understand both the legacy monolith’s structure and modern microservice patterns reduced the integration time to 2-3 days per integration point – a 70% time saving. This significantly streamlined the integration process while maintaining the robustness required for production systems.

Use Case 3: Generating and Refactoring JPA Entity Classes
During the modernization effort, new database tables were required to support additional business functionality in both the monolith and microservices. Instead of manually coding the data access layer, Amazon Q Developer automated the process by generating Spring JPA Entity classes from SQL DDL statements. Amazon Q Developer maintained consistency with existing data models by following established naming conventions, applying standard annotations, and implementing required interfaces from the existing codebase. What stood out was Q Developer’s ability to provide detailed explanations for its implementation choices, such as why specific annotations were used or how the new entities aligned with existing persistence patterns, enabling the team to quickly validate the generated code against their architectural standards.

EPAM's modernization initiative focused on multiple business-critical applications, primarily built in Java 8 with Oracle Database backend, that serve as the backbone for the client’s operations across multiple product segments including nutrition, health and beauty, home care, and personal care. The modernization initiative focused on multiple business-critical applications, primarily built in Java 8 with Oracle Database backend, that serve as the backbone for the client’s operations across multiple product segments including nutrition, health and beauty, home care, and personal care.

Amazon Q Developer’s capabilities significantly streamlined the modernization process, resulting in substantial time and effort savings. By automating routine tasks and providing intelligent code suggestions, Amazon Q Developer enabled developers to focus on more strategic aspects of the modernization project.

References:
[1] https://aws.amazon.com/blogs/devops/accelerating-legacy-code-modernization-epams-journey-with-amazon-q-developer/