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AWS Transform - Migration Launch Guide
Services and agentsLatest innovationsBenefitsHow to access AWS TransformCustomer successGetting started

AWS Transform

AWS Transform is a collaborative enterprise IT transformation workbench powered by specialized AI agents, agentic workflows, and continuous learning that accelerates cloud migration, legacy application modernization, and tech debt reduction. It offers purpose-built transformations for mainframe, VMware, and Windows workloads, and automates code modernization at scale—from version and framework upgrades to fully custom, organization-specific transformations.

By automating complex tasks like assessments, code analysis, refactoring, dependency mapping, and transformation planning, AWS Transform dramatically reduces project timelines and costs. Its shared workspaces and natural language chat experience enable cross-functional teams to collaborate in real time, track progress, and manage transformations from start to finish.

In its first year, AWS Transform has migrated tens of thousands of VMs and processed over 4.5 billion lines of code, saving 1.69 million hours of manual effort across mainframe, Windows/.NET, infrastructure, and custom code modernization.

To get started, see AWS Transform in the AWS Management Console. For the latest features, see AWS Transform. For detailed guidance, see the AWS Transform User Guide.

Services and agents

AWS Transform provides specialized AI agents for five primary use cases. Each agent is purpose-built on 20 years of AWS migration and modernization experience and is accessible from the web console, CLI, IDE (Kiro, VS Code), or through MCP (Model Context Protocol) integration.

AWS Transform assessments (migration assessments)

AWS Transform assessments help you evaluate the cost, feasibility, and business value of migrating on-premises infrastructure to AWS. Using AI-powered agents, assessments provide automated right-sizing recommendations, multi-scenario comparison, and interactive refinement through natural language chat.

Key capabilities include:

  • Cost estimation – Get cost estimates for Amazon EC2, Amazon RDS for SQL Server, Amazon EBS, Amazon S3, Amazon FSx, and end user computing services.

  • Automated right-sizing – Analyzes on-premises server specifications and recommends appropriately sized EC2 instances based on CPU, memory, and performance requirements.

  • SQL Server assessment – Specialized analysis for SQL Server migrations to Amazon RDS or EC2, including BYOM/LI licensing options and Database Savings Plans (up to 20% savings).

  • Business value assessment – Evaluates staff productivity gains, resilience improvements, and business agility beyond infrastructure cost savings.

  • Sustainability – Estimates carbon footprint reduction from migrating to AWS.

  • Multi-scenario comparison – Create multiple scenarios with different assumptions (pricing models, regions, instance families, licensing) and compare side by side with what-if analysis.

  • Chat-based interaction – Refine assessments interactively through natural language. Supports rough estimation with limited data, adding inventory through chat, and modifying costs on the fly.

  • Deliverable generation – Generate executive presentations (PPTX) and detailed reports (PDF) directly from assessment results.

AWS Transform accepts inventory data from multiple sources including the AWS Transform Discovery Tool, RVTools (VMware), CMDB exports, Migration Evaluator, partner discovery tools, and MPA format files.

Use assessments at the start of your migration journey to build the business case, inform planning, and gain executive approval.

To learn more, see Migration assessments in the AWS Transform User Guide.

AWS Transform for VMware migrations

AWS Transform for VMware migrations accelerates enterprise cloud migrations with purpose-built AI agents that automate the entire lifecycle—from discovery and wave planning through network conversion and cutover. By unifying teams, tools, and workflows in a single collaborative workbench, migrations that once took years now complete in months.

The service supports VMware, bare metal, Hyper-V, and database workloads. Key capabilities include:

  • Intelligent wave planning – AI agents analyze application dependencies, business priorities, and technical constraints to group workloads into optimized migration waves. What once required weeks of manual effort now takes minutes.

  • Landing zone creation – Automates the generation of Landing Zone Accelerator (LZA) configurations with secure, multi-account AWS environments, consistent governance, and security controls. Supports CloudFormation, CDK, Terraform, and LZA formats.

  • Automated network conversion – Converts complex on-premises network configurations into AWS equivalents (VPCs, subnets, transit gateways) up to 80x faster than manual methods.

  • Rehost or replatform – Manages the full rehosting lifecycle (agent deployment, test instances, cutover orchestration) or replatforms applications to containers on Amazon ECS or Amazon EKS in the same workflow.

The service supports first-party AWS agents, third-party partner agents, and custom Bring Your Own Agent workflows.

To learn more, see AWS Transform for VMware migrations.

Watch the following video from re:Invent 2025 on how to complete a large-scale migration with agentic AI: Reimagining large-scale migration planning with agentic AI.

AWS Transform for Windows modernization

AWS Transform accelerates full-stack Windows modernization by up to 5x across application, UI framework, database, and deployment layers. Using the specialized Windows modernization agent, teams can modernize .NET applications, SQL Server databases, and deployment processes—reducing operating costs by up to 70% by moving away from costly licenses.

Key capabilities include:

  • .NET framework modernization – Upgrades legacy .NET Framework applications to .NET 8+ (cross-platform), enabling containerization and Linux deployment.

  • SQL Server migration – Automates database modernization from SQL Server to open-source engines (PostgreSQL, MySQL) or AWS-managed databases.

  • UI framework upgrades – Modernizes legacy UI frameworks (for example, Web Forms to Blazor or React).

  • Deployment modernization – Converts traditional IIS deployments to containerized microservices on Amazon ECS or Amazon EKS.

In addition to the AWS Transform web console, a Visual Studio extension (VSIX) provides an integrated IDE experience for .NET modernization.

To learn more, see AWS Transform for Windows.

AWS Transform for mainframe modernization

AWS Transform accelerates mainframe application modernization from years to months. The specialized mainframe agent streamlines the entire transformation process—from initial analysis and planning to code refactoring and application reimagining—reducing risk and costs.

Key capabilities include:

  • Codebase analysis – Analyzes COBOL, PL/I, JCL, and other mainframe languages to map dependencies, detect missing artifacts, and assess complexity with visual dependency representations.

  • Automated refactoring – Converts mainframe code to modern languages (Java, C#) while preserving business logic. Works with Claude Code and other agentic IDEs for the forward engineering phase.

  • Data migration – Migrates mainframe data stores (VSAM, IMS DB, Db2) to cloud-native databases.

  • Testing and validation – Automated equivalence testing to ensure functional parity between legacy and modernized applications.

To learn more, see AWS Transform for mainframe.

AWS Transform custom (code modernization)

AWS Transform custom is the agentic AI service for eliminating technical debt at scale. It transforms any code pattern—from any language, framework, or runtime to any other—through both built-in (AWS managed) and custom transformation recipes.

Key capabilities include:

  • Built-in transformations – Ready out-of-the-box for common scenarios:

    • Java, Python, Node.js version upgrades (Lambda and non-Lambda)

    • AWS SDK v1 to v2 upgrades

    • Java X86 to Graviton

    • Log4J to SLF4J

    • Angular to React / Angular version upgrades

    • Spring Boot upgrades, JBoss to Spring Boot

    • Comprehensive code analysis and tech debt reporting

  • Custom transformations – Create your own for any-to-any use cases. Define transformation requirements in natural language, test on sample repositories, then apply at enterprise scale. Supports diverse scenarios from language translations (Progress 4GL to Java, C to Rust, COBOL to Java) to architectural changes (X86 to Graviton, microservices decomposition).

  • Continual learning – The agent learns from each execution, becoming smarter when applied repeatedly to similar repositories.

  • Scale – CLI-based interface that acts on one or multiple repositories. Integrates with CI/CD platforms for continuous modernization. Can run from laptop, EC2, ECS/EKS containers, or any pipeline.

  • IDE integration – Available through Kiro Power (VS Code extension), as well as agent skills for Claude Code, Cursor, and Codex.

  • Modernization Analysis (MODA) – Scans code for cloud-native maturity gaps and maps findings to AWS modernization pathways. Completes in 5–30 minutes per repository.

  • Agentic Readiness Analysis (ARA) – Evaluates whether systems are ready to be safely called by AI agents, covering APIs, identity, state management, human-in-the-loop controls, and observability.

  • Campaign management – Web experience for managing large-scale transformation campaigns, tracking progress across multiple repositories.

To learn more, see AWS Transform custom.

Latest innovations

AWS Transform continues to expand capabilities. Recent launches include:

  • MCP integration – Invoke transformation capabilities directly from orchestrators, IDEs, and coding environments using Model Context Protocol.

  • Kiro Power and agent skills – Pre-built playbooks and individual tasks accessible from Kiro, Claude Code, Cursor, and Codex.

  • Web-to-IDE handoff – Start modernization jobs in the web console, then hand off to developer IDEs for human-in-the-loop edits and refinement.

  • Agent builder toolkit – Extend AWS Transform with custom agents using Kiro Power combined with the AWS Transform base agent and SDK.

  • Expanded regions – Mumbai, Tokyo, Seoul, Sydney, Canada, and Europe.

  • CloudWatch metrics – Monitor cost, success/failure rates, and agent minutes.

For the latest updates, see AWS Transform – Latest Innovations.

Benefits

The following are the primary benefits of using AWS Transform:

  • Accelerate modernization – Modernize Windows, mainframe, and VMware applications up to 5x faster with agentic AI–powered automation of analysis, planning, documentation, and transformation tasks.

  • Deliver at scale – Transform hundreds of applications in parallel. AWS Transform automates high-effort, repeatable tasks so teams can deliver larger, more complex projects faster.

  • Reduce costs – Remove legacy infrastructure, licensing, and modernization costs. Customers report up to 70% reduction in operating costs by moving away from costly licenses.

  • Specialized agents built on AWS expertise – Achieve consistent, reliable outcomes using AI agents built on 20 years of AWS migration and modernization experience.

  • Unified collaboration – Shared workspaces and natural language chat enable cross-functional teams (project managers, architects, developers, security engineers) to work together in real time.

  • Flexible tooling – Use AWS Transform from the web console, CLI, IDE (Kiro, VS Code), or through MCP integration with your preferred orchestrators and coding environments.

How to access AWS Transform

The following table describes the interfaces you can use to access AWS Transform.

Interface Description
Web console AWS Transform console (https://console.aws.amazon.com/transform)—collaborative workbench for planning and tracking
CLI Command-line interface for automation, CI/CD integration, and batch operations
IDE (Kiro Power) VS Code extension and Kiro IDE for developer-centric workflows
Visual Studio (VSIX) Visual Studio extension for .NET modernization
Agent skills Pre-built plugins for Claude Code, Cursor, and Codex
MCP Model Context Protocol integration for orchestrators and custom toolchains

Customer success

The following are publicly available case studies of customers using AWS Transform.

Customer Use case Outcome Reference
IDEMIA .NET modernization 4x faster, 30% cost reduction Case study
Thomson Reuters Windows/.NET modernization 4x faster modernization Case study
Bridgestone Mainframe modernization Completed in 7 months, 90% efficiency gains Case study
CSL VMware migration (5,000 servers, 29 data centers) 10x faster planning, 30% operational cost savings Case study
ADP Compliance infrastructure Reimagined with AWS Transform Case study
Toyota Mainframe modernization Accelerated with generative AI Case study
Vector VMware migration 34% faster than traditional methods Case study
Mercedes-Benz SAP modernization RISE with SAP on AWS Case study

Getting started

To get started with AWS Transform, use the following resources:

For more information, contact your AWS account team.