Generative AI has brought many new possibilities to organizations. It has equipped them with new abilities to retire technical debt, modernize legacy systems, and build agile infrastructure to help unlock the value that is trapped in their internal data. However, many enterprises still rely heavily on legacy IT infrastructure, particularly mainframes and VMware-based systems. These platforms have been the backbone of critical operations for decades, but they hinder organizations’ ability to innovate, scale effectively, and reduce technical debt in an era where cloud-first strategies dominate. The need to modernize these workloads is clear, but the journey has traditionally been complex and risky.
The complexity spans multiple dimensions. Financially, organizations face mounting licensing costs and expensive migration projects. Technically, they must untangle legacy dependencies while meeting compliance requirements. Organizationally, they must manage the transition of teams who’ve built careers around legacy systems and navigate undocumented institutional knowledge.
AWS Transform directly addresses these challenges with purpose-built agentic AI that accelerates and de-risks your legacy modernization. It automates the assessment, planning, and transformation of both mainframe and VMware workloads into cloud based architectures, streamlining the entire process. Through intelligent insights, automated code transformation, and human-in-the-loop workflows, organizations can now tackle even the most challenging modernization projects with greater confidence and efficiency.
Mainframe workload migration
AWS Transform for mainframe is the first agentic AI service for modernizing mainframe workloads at scale. The specialized mainframe agent accelerates mainframe modernization by automating complex, resource-intensive tasks across every phase of modernization — from initial assessment to final deployment. It streamlines the migration of legacy applications built on IBM z/OS, including COBOL, CICS, DB2, and VSAM, to modern cloud environments–cutting modernization timelines from years to months.
Let’s look at a few examples of how AWS Transform can help you through different aspects of the migration process.
Code analysis – AWS Transform provides comprehensive insights into your codebase, automatically examining mainframe codebases, creating detailed dependency graphs, measuring code complexity, and identifying component relationships
Documentation – AWS Transform for mainframe creates comprehensive technical and functional documentation of mainframe applications, preserving critical knowledge about features, program logic, and data flows. You can interact with the generated documentation through an AI-powered chat interface to discover and retrieve information quickly.
Business rule logic extraction – AWS Transform extracts and presents complex logic in plain language so you can gain visibility into business processes embedded within legacy applications. This enables both business and technical stakeholders to gain a greater understanding of application functionality.
Code decomposition – AWS Transform offers sophisticated code decomposition tools, including interactive dependency graphs and domain separation capabilities, enabling users to visualize and modify relationships between components while identifying key business functions. The solution also streamlines migration planning through an interactive wave sequence planner that considers user preferences to generate optimized migration strategies.
Modernization Wave planning – With its specialized agent, AWS Transform for mainframe creates prioritized modernization wave sequences based on code and data dependencies, code volume, and business priorities. It enables modernization teams to make data-driven, customized migration plans that align to their specific organizational needs.
Code refactoring – AWS Transform can refactor millions of lines of mainframe code in minutes, converting COBOL, VSAM, and DB2 systems into modern Java Spring Boot applications while maintaining functional equivalence and transforming CICS transactions into web services and JCL batch processes into Groovy scripts. The solution provides high-quality output through configurable settings and bundled runtime capabilities, producing Java code that emphasizes readability, maintainability, and technical excellence.
Deployments – AWS Transform provides customizable deployment templates that streamline the deployment process through user-defined inputs. For added efficiency, the solution bundles the selected runtime version with the migrated application, enabling seamless deployment as a complete package.
By integrating intelligent documentation analysis, business logic extraction, and human-in-the-loop collaboration capabilities, AWS Transform helps organizations accelerate their mainframe transformation while reducing risk and maintaining business continuity.
VMware modernization
With rapid changes in VMware licensing and support model, organizations are increasingly exploring alternatives despite the difficulties associated with migrating and modernizing VMware workloads. This is aggravated by the fact that the accumulation of technical debt typically creates complex, poorly documented environments managed by multiple teams, leading to vendor lock-in and collaboration challenges that hinder migration efforts further.
AWS Transform is the first agentic AI service for VMware modernization of its kind that helps you to overcome those difficulties. It can offset risk and accelerate the modernization of VMware workloads by automating application discovery, dependency mapping, migration planning, network conversion, and EC2 instance optimization, reducing manual effort and accelerating cloud adoption.
The process is organized into four phases: inventory discovery, wave planning, network conversion, and server migration. It uses agentic AI capabilities to analyze and map complex VMware environments, converting network configurations into AWS built-in constructs and helps you to orchestrate dependency-aware migration waves for seamless cutovers. In addition, it also provides a collaborative web interface that keeps AWS teams, partners, and customers aligned throughout the modernization journey.
Let’s take a quick tour to see how this works.
Setting up
Before you can start using the service, you must first enable it by navigating to the AWS Transform console. AWS Transform requires AWS IAM Identity Center (IdC) to manage users and setup appropriate permissions. If you don’t yet have IdC set up it will ask you to configure it first and return to the AWS Transform console later to continue the process.
With IdC available, you can then proceed to choosing the encryption settings. AWS Transform gives you the option to use a default AWS managed key or you can use your own custom keys through AWS Key Management Service (AWS KMS).
After completing this step, AWS Transform will be enabled. You can manage admin access to the console by navigating to Users and using the search box to find them. You must create users or groups in IdC first if they don’t already exist. The service console will help admins provision users who will get access to the web app. Each provisioned user receives an email with a link to set password and get their personalized URL for the webapp.
You interact with AWS Transform through a dedicated web experience. To get the url, navigate to Settings where you can check your configurations and copy the links to the AWS Transform web experience where you and your teams can start using the service.
Discovery
AWS Transform can discover your VMware environment either automatically through AWS Application Discovery Service collectors or you can provide your own data by importing existing RVTools export files.
To get started, choose the Create or select connectors task and provide the account IDs for one or more AWS accounts that will be used for discovery. This will generate links that you can follow to authorize each account for usage within AWS Transform. You can then move on to the Perform discovery task, where you can choose to install AWS Application Discovery Service collectors or upload your own files such as exports from RVTools.
Provisioning
The steps for the provisioning phase are similar to the ones described earlier for discovery. You connect target AWS accounts by entering their account IDs and validating the authorization requests which will then enable the next steps such as the Generate VPC configuration step. Here, you can import your RVTools files or NSX exports from Import/Export from NSX, if applicable, and enable AWS Transform to understand your networking requirements.
You should then continue working through the job plan until you reach the point where it’s ready to deploy your Amazon Virtual Private Cloud (Amazon VPC). All the infrastructure as code (IaC) code is stored in Amazon Simple Storage Service (Amazon S3) buckets in the target AWS account.
Review the proposed changes and, if you’re happy, start the deployment process of the AWS resources to the target accounts.
Deployment
AWS Transform requires you to set up AWS Application Migration Service (MGN) in the target AWS accounts to automate the migration process. Choose the Initiate VM migration task and use the link to navigate to the service console, then follow the instructions to configure it.
After setting up service permissions, you’ll proceed to the implementation phase of the waves created by AWS Transform and start the migration process. For each wave, you’ll first be asked to make various choices such as setting the sizing preference and tenancy for the Amazon Elastic Compute Cloud (Amazon EC2) instances. Confirm your selections and continue following the instructions given by AWS Transform until you reach the Deploy replication agents stage, where you can start the migration for that wave.
After you start the waves migration process, you can switch to the dashboard at any time to check on progress.
With its agentic AI capabilities, AWS Transform offers a powerful solution for accelerating and de-risking mainframe and VMware modernization workloads. By automating complex assessment and transformation processes, AWS Transform reduces the time associated with legacy system migration while minimizing the potential for errors and business disruption enabling more agile, efficient, and future-ready IT environments within your organization.
Things to know
Availability – AWS Transform for mainframe is available in US East (N. Virginia) and Europe (Frankfurt) Regions. AWS Transform for VMware offers different availability options for data collection and migrations. Please refer to the AWS Transform for VMware FAQ for more details.
Pricing – Currently, we offer our core features—including assessment and transformation—at no cost to AWS customers.
Here are a few links for further reading.
Dive deeper into mainframe modernization and learn more about about AWS Transform for mainframe.
Explore more about VMware modernization and how to get started with your VMware migration journey.
Check out this interactive demo of AWS Transform for mainframe and this interactive demo of AWS Transform for VMware.
— Matheus Guimaraes | @codingmatheus
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