Accelerating Mainframe Modernization: Learn How Partners Are Leveraging AWS Transform

Customers increasingly seek to modernize mainframe workloads by migrating to AWS, attracted by potential cost savings, improved agility, and reduced technical debt. AWS Systems Integrator partners have the expertise, scale, and skills to lead large mainframe transformations, and our customers collaborate with these partners to achieve large-scale migrations. Today, we are excited to announce the general availability of AWS Transform for mainframe service, a unique platform powered by agentic AI. This service represents a breakthrough in mainframe modernization, transforming what has traditionally been a multi-year journey into a process measured in months.

In this blog, we are going to learn how our partners have been leveraging AWS Transform to deliver mainframe modernization projects and expand their modernization business practice.

Introducing AWS Transform for Mainframe

AWS Transform for mainframe, previewed as ‘Q Developer transformation capability for mainframe’ at re:Invent 2024, is now generally available. AWS Transform for mainframe accelerates modernization of IBM z/OS applications. Powered by specialized AI agents trained using AWS’s years of experience, it streamlines the entire transformation process from initial analysis and planning to code refactoring and migration. This enables organizations to modernize faster, reduce risk and cost, and achieve efficient and reliable path towards cloud migration.

AWS Transform introduces a suite of enhancements designed to accelerate the mainframe modernization journey. The enhanced code analysis now identifies cyclomatic complexity, identically named components, and duplicate program IDs, while offering import/export functions for file classification and in-UI file comparison. Documentation capabilities have been expanded with improved accuracy, including an AI-powered chat experience for querying the generated documentation and flexible document viewing within the interface. Business users can now extract business logic to better understand source code functionality and logic. The release also introduces interactive relationship exploration between files when creating domains and infrastructure-as-code foundations for modernized application environments.

AWS Transform for mainframe is available in US East (N. Virginia) and Europe (Frankfurt) Regions. Additionally, we’re introducing a public preview of Reforge, an Large Language Model (LLM) powered code restructuring tool that optimizes refactored Java code with human-readable comments, further enhancing code maintainability.

Challenges in Mainframe Modernization

Parters assisting organizations with mainframe modernization generally face three major challenges which can be solved using AWS Transform:

Speed and Agility: Traditional modernization of complex mainframe systems, containing millions of lines of legacy code, typically requires multi-year timelines and extensive manual effort. Partners leverage AWS Transform to accelerate this process, enabling rapid transformation while preserving critical business functionality.
Complexity: Mainframe applications feature tightly integrated architectures and intricate business logic that resist straightforward cloud migration. Partners use AWS Transform’s AI-powered analysis and code transformation capabilities to systematically decompose these complex systems and ensure accurate preservation of business logic.
Skills Gap: As experienced mainframe experts transition out, organizations struggle to maintain systems when modernizing to newer technologies. Partners bridge this gap with the help of AWS Transform’s documentation and knowledge preservation features, enabling effective knowledge transfer between legacy and modern platforms.

Let’s explore in more detail how AWS Transform for mainframe addresses these challenges.

AWS Transform for Mainframe: Key Capabilities

To address the challenges of mainframe modernization, AWS Transform for mainframe provides the following key capabilities:

Code Analysis: Automatically examines mainframe codebases, creating detailed dependency graphs, measuring code complexity, and identifying component relationships. It categorizes code components and provides metrics to aid in modernization planning.
Document Generation: Creates comprehensive technical and functional documentation of mainframe applications, preserving critical knowledge about features, program logic, and data flows. It includes an AI-powered chat interface with natural language processing for easy information retrieval.
Business Logic Extraction: Extracts and documents complex logic in clear, business-friendly language, offering visibility into business processes embedded within legacy applications. This helps both business and technical stakeholders better understand application functionality.
Code Decomposition: Assists in breaking down monolithic applications into multiple manageable domains, enhancing agility and maintainability. It provides tools for updating dependencies and exploring component relationships.
Modernization Planning: Creates prioritized modernization wave sequences based on code dependencies, volume, and user priorities. This systematic approach enables customized planning that aligns with specific organizational needs.
Code Refactoring: Automates the conversion of COBOL and JCL to object-oriented languages like Java and Groovy while maintaining functional equivalence in the modernized code.
Reforge (Public Preview): Leverages LLMs to optimize refactored Java code, improving readability and maintainability by restructuring code and adding human-readable comments.
Code Deployment: Provides infrastructure-as-code templates that streamline the deployment and setup of modernized application environments in AWS.

How Partners Leverage AWS Transform to Strengthen their Mainframe Modernization Practice

AWS Transform for mainframe represents a significant breakthrough in modernization technology, drastically reducing IBM z/OS application transformation time from years to months. Our partners have been able to streamline customer’s migration journey using AWS Transform—from initial analysis and planning to code refactoring and migration. The new Generative AI (GenAI) powered service has generated significant interest among our AWS Mainframe Migration Competency Consulting Partners and other AWS Partners who collaborated on its launch.

Our elite launch partners Accenture, Capgemini, Cognizant, DXC Technology, HCLTech, Infosys, Kyndryl, Nomura Research Institute (NRI), and Pega Systems have successfully used AWS Transform to accelerate mainframe modernization for our joint customers. These partners are scaling their modernization practices through AWS Transform, which streamlines key project phases including analysis, documentation, decomposition, and transformation. Using AWS Transform’s capabilities, partners can now demonstrate working applications and deliver results in a fraction of the time traditionally required. This rapid progress helps build customer confidence, secure project approvals, and create early momentum in complex mainframe modernization initiatives.

Let’s hear from our elite launch partners about how AWS Transform is influencing their mainframe modernization journey.

	“AWS Transform brings a fresh perspective into the mainframe modernization effort by helping accelerate our understanding of the legacy code and reducing our reliance in Subject Matter Expects. Compared with a traditional approach we see the ability to leverage innovation at a much faster pace, leveraging the collaboration between Accenture and AWS leading to an optimized delivery timeline.” – Noe Gutierrez, Managing Director, Cloud First Design, Accenture

	“The modernization of mainframe applications is crucial for unlocking the full potential of cloud solutions. Historically, this transformation has been a lengthy, complex process spanning several years. However, with AWS Transform for Mainframe, we now have the power to accelerate this journey, completing modernization projects in months rather than years, dramatically reducing costs and risks for our financial services clients. By harnessing AWS Transform agentic AI capabilities, we simplify complex modernization efforts while ensuring business continuity and cost-efficiency. Our collaboration with clients will continue to drive rapid innovation, using AWS’s AI to enable faster, simpler transformations with better outcomes.” – Shashi Gupta, VP, Capgemini FS – Global AWS CoE

	“At Cognizant, we help enterprises modernize legacy mainframe systems to unlock agility, cost savings, and digital innovation. As part of that journey, we’ve evaluated AWS Transform for Mainframe Modernization and are excited by its potential to accelerate code analysis, documentation and refactoring powered by Blu Age. This AI-powered capability streamlines the discovery and transformation of COBOL workloads, reducing manual effort. By automating key steps in the modernization lifecycle, we can enable clients to shift from legacy to cloud-native architectures faster, while empowering their teams to focus on innovation and long-term value creation.” – Pramod Bijani SVP – Head Platform Group (Engineering), Cognizant

	“AWS Transform is a powerful enabler for DXC Assure Platform engineering team, supporting mainframe COBOL application migration to DXC Assure Cloud. Through AI-driven code analysis at scale combined with DXC’s own GenAI capabilities developed on HAQM Bedrock, we anticipate migration analysis time reduction by up to 25%. As part of the Assure Platform migration toolkit, AWS Transform also has the potential to offer alternatives to the traditional lift-and-shift migration approach by enabling AI-powered software architecture re-platforming that seamlessly aligns with the Assure Platform’s cloud-native architecture, ultimately delivering improved performance and cost benefits to our clients.” – Jim Restivo Sr. Vice President of Insurance Solutions

	“Mainframe modernization has always been a complex problem. AWS Transform offers a revolutionary solution to address this complexity. It provides automation coverage on critical area of productivity that are code analysis, decomposition, documentation, and iterative transformation. We have observed a potential of 10-15% improvement in engineering efforts and around 15% reduction in cycle time. It further helps with significant reduction of about 30% in dependency on legacy systems SMEs time. We expect further productivity gains as the solution leverages inherent potential of agentic-AI experience with human-in-the-loop oversight. This significantly enhances our confidence on delivering better ROI for the digital transformation that our customers are undertaking.” – Sandeep Rajpathak, Senior Vice President and Global Head, Custom Applications, Digital Business Services, HCLTech

	“Legacy modernization is essential for enterprises to stay competitive. Updating outdated, complex mainframe systems is key but often challenging due to their complexity, limited documentation, and shortage of experts. AWS Transform for Mainframe simplifies this with AI-driven tools for analysis, documentation, decomposition, and refactoring workflows—streamlining the process, while reducing complexities, and need for mainframe expertise. Combined with our deep expertise in mainframe modernization and the Infosys Live Enterprise Application Development platform, part of Infosys Cobalt and Infosys Topaz, we help enterprises achieve greater agility and efficiency in their transformation journeys.” – Balakrishna D. R. (Bali), Executive VP and Global Services Head, AI and Industry Verticals, Infosys

	“Due to the nature of large enterprise mainframe applications, modernization projects are often complex, time-consuming and come with significant risk. For many organizations, identifying the right application team SMEs, and conducting exploratory and deep analysis of the source code and documentation, can be challenging and prone to errors. As an alliance partner of AWS, Kyndryl has experienced first-hand how the AWS Transform solution can support and accelerate the mainframe modernization journey for customers, whether they aim to modernize on, integrate with, or move applications off the mainframe. Its ability to translate complex code terms leveraging generative AI helps to improve understanding of and working with application documentation. Based on our work with AWS Transform, our projections indicate that a project typically taking 12 months could potentially be completed in about 8 months, representing an approximate 33% time savings. The combination of Kyndryl’s deep mainframe expertise and the generative AI capabilities provided by AWS Transform can help customers across various industries streamline their mainframe transformation initiatives, increase productivity, and hence drive more business value.” – Richard Baird, Chief Technology Officer for Core Enterprise & zCloud, Kyndryl

	“Nomura Research Institute (NRI) collaborated on a proof of concept (PoC) for AWS Transform by leveraging its extensive expertise in financial institution systems. This PoC focused on assessing the tool’s ability to modernize mainframe systems, especially in creating documentation that visualizes the functions of complex legacy systems in the financial industry. By leveraging AWS Transform’s AI agent functionality, we were able to significantly streamline the process that would typically require experienced engineers to accurately interpret, document, and verify the relationships between programs and the logic of business codes. For instance, in the analysis of complex components—a task that would normally take approximately one month—we confirmed that the same process could be completed within just about one week. This represents a major step forward in enhancing both efficiency and productivity. Looking ahead, NRI aims to deepen its collaboration with AWS Transform by exploring further improvements to the tool and innovative ways to maximize its capabilities. NRI seeks to provide its clients with more accurate, efficient, and cost-effective modernization solutions by leveraging AWS Transform for legacy system analysis, accelerating the assessment and planning phases, and applying it during execution stages such as code conversion and refactoring. Ultimately, the goal is to empower organizations’ digital transformation initiatives and support them in navigating modernization journeys with confidence and success. NRI is committed to making AWS Transform a cornerstone of its modernization practice for clients in diverse industries.” – Hitoshi Okayama, General Manager, Broker Dealers System Service Department, Nomura Research Institute, Ltd.

	“The integration of AWS Transform with Pega’s AI centric Legacy Transformation tooling has significantly accelerated client value with their Discovery, Design and Development processes. With AWS Transform’s AI capabilities, we’ve compressed what was historically multi-year projects into accelerated cloud modernization initiatives that enable organizations to realize business value in under 90 days. Most Enterprise clients are handicapped due to the lack of documentation, key skills, compressed budgets, regulatory changes and massive amounts of technical debt with modernizing their legacy applications and driving strategic business process change at speed. The combined technological capabilities of AWS Transform and Pega Blueprint give clients the unparalleled ability to rapidly analyze their legacy applications, augment the analysis with limited documentation, screen images, voice recordings to generate unprecedented insights into the business rules, data models, and workflows that are embedded within the legacy application and leverage AI to consume these insights to develop a functional and cloud ready application model. This approach has positioned clients to tackle complex legacy application modernization projects with confidence to unlock significant economic value both from an operational budget management as well as business model change.” – Ravesh Lala, Legacy Transformation Practices Leader