AWS Transform is an agentic AI–powered service designed to help organizations modernize mainframe and VMware workloads into cloud-based architectures.

Instead of relying on fully manual discovery and migration projects, AWS Transform uses specialized AI agents to automate tasks that typically slow teams down, including:

• Code analysis and dependency mapping
• Refactoring and code transformation
• Decomposition of large legacy applications
• Validation and transformation planning
• Modernization wave planning and deployment support

For many organizations, mainframes and VMware environments have been in place for decades and are tightly coupled to critical operations. That makes modernization financially, technically, and organizationally complex. AWS Transform helps you rethink and de-risk that journey by:

• Automating assessment and planning so you can see what you have, how it’s connected, and where to start.
• Reducing manual effort in code conversion and infrastructure design.
• Supporting human-in-the-loop workflows, so your teams stay in control while AI accelerates the heavy lifting.

Currently, core features such as assessment and transformation are offered at no cost to AWS customers, which can materially lower the upfront barrier to starting a modernization initiative.

AWS Transform for mainframe is described as the first agentic AI service for modernizing mainframe workloads at scale. It focuses on automating the end-to-end lifecycle of mainframe modernization—from initial assessment through deployment.

In practical terms, it can help you:

1. Understand and document your mainframe estate

• Code analysis: Automatically examines mainframe codebases, builds detailed dependency graphs, measures code complexity, and identifies relationships between components.
• Documentation: Generates technical and functional documentation for mainframe applications, preserving knowledge about features, program logic, and data flows.
• AI-powered documentation search: Lets your teams query the generated documentation via an AI chat interface to quickly retrieve information.

2. Expose and clarify business logic

• Business rule logic extraction: Extracts complex business logic and presents it in plain language, giving both business and technical stakeholders clearer visibility into how legacy applications actually work.

3. Plan and sequence modernization waves

• Code decomposition: Provides interactive dependency graphs and domain separation tools so you can visualize and adjust relationships between components.
• Modernization wave planning: Uses an interactive wave sequence planner to create prioritized migration waves based on code and data dependencies, code volume, and business priorities.

4. Refactor and deploy modernized applications

• Code refactoring at scale: Can refactor millions of lines of mainframe code in minutes, converting COBOL, VSAM, and DB2 systems into modern Java Spring Boot applications.
• Transaction and batch transformation: Transforms CICS transactions into web services and JCL batch processes into Groovy scripts, while maintaining functional equivalence.
• Deployment support: Provides customizable deployment templates and bundles the selected runtime version with the migrated application, enabling deployment as a complete package.

By combining intelligent documentation analysis, business logic extraction, and human-in-the-loop collaboration, AWS Transform helps you reimagine mainframe workloads as cloud-native applications while aiming to reduce risk and maintain business continuity. AWS Transform for mainframe is currently available in the US East (N. Virginia) and Europe (Frankfurt) Regions.

AWS Transform for VMware is designed to help organizations respond to changes in VMware licensing and support models by providing a structured, AI-assisted path to AWS. It focuses on environments that often have significant technical debt, are poorly documented, and are managed by multiple teams.

The service uses agentic AI to analyze and map complex VMware environments and then guide you through four main phases:

1. Inventory discovery

• Discovers your VMware environment using AWS Application Discovery Service collectors or by importing existing RVTools export files.
• Builds a view of applications, servers, and dependencies to inform planning.

2. Wave planning

• Uses AI to orchestrate dependency-aware migration waves, helping you group workloads for more seamless cutovers.
• Supports collaboration between AWS teams, partners, and customers through a shared web interface.

3. Network conversion

• Converts VMware network configurations into AWS-native constructs, such as Amazon VPC configurations.
• Generates Infrastructure as Code (IaC) artifacts and stores them in Amazon S3 in the target AWS account.
• Lets you review proposed changes before deploying the Amazon VPC and related resources.

4. Server migration

• Requires you to set up AWS Application Migration Service (MGN) in target AWS accounts.
• For each migration wave, you choose Amazon EC2 sizing preferences and tenancy before starting replication.
• Guides you through deploying replication agents and initiating the migration for each wave.
• Provides a dashboard so you can monitor migration progress across waves.

From an access and security standpoint, AWS Transform:

• Is enabled via the AWS Transform console.
• Uses AWS IAM Identity Center (IdC) to manage users and permissions.
• Supports encryption using either the default AWS managed key or your own keys via AWS Key Management Service (AWS KMS).

By automating application discovery, dependency mapping, migration planning, network conversion, and EC2 optimization, AWS Transform helps you reshape VMware environments for AWS while aiming to reduce manual effort, lower migration risk, and accelerate cloud adoption.