Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →AWS Transform is AWS’s umbrella service for using agentic AI to assess, plan, execute, and govern infrastructure, application, and code transformation. The phrase “AWS toolkit for cloud migration” covers two related layers: managed migration workflows that AWS operates as a service, and the Agent Builder Toolkit that lets professional-services teams, independent software vendors, and enterprise customers create specialized agents around their own runbooks.
It is not a promise of unattended migration. AWS describes a guided, collaborative workbench in which agents analyze inventories, propose plans, prepare environments, and carry out approved actions. The quality of each recommendation still depends on the inventory, assumptions, constraints, permissions, and human review supplied by the customer.
As an Amazon Associate I earn from qualifying purchases.
What is AWS Transform?
AWS Transform is an agentic AI experience for transforming infrastructure, applications, and code, according to the AWS Transform User Guide. It brings specialized agents, shared workspaces, and migration workflows into one service rather than treating discovery, planning, landing-zone preparation, and execution as disconnected projects.
Outdated Drivers Are Slowing You Down
One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchWindows Errors? Fix Them Before They Spread
Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallThe documented scope is broad. It includes mainframe modernization; migration of virtual and bare-metal servers; VMware and Hyper-V environments; discovery and dependency analysis; migration-wave planning; landing-zone creation; network migration; server rehosting; and source-code containerization for Amazon Elastic Container Service (ECS) or Amazon Elastic Kubernetes Service (EKS).
#1 Best Overall
That breadth matters because a cloud program usually mixes several kinds of work. A server may be rehosted with minimal change, an application may need code changes and a container target, and the surrounding network and identity controls must be ready before either path is safe. AWS Transform presents these as connected stages with a common workspace and agent context.
Two layers sit behind the “toolkit” description
Readers often use “toolkit” to mean the whole AWS Transform product. In practice, AWS describes a managed service and an extensibility layer. Keeping them separate makes it easier to understand what AWS supplies and what your team must build.
| Layer | What it provides | Who uses it | What it does not imply |
|---|---|---|---|
| Managed AWS Transform workflows | Agents and guided workflows for discovery, assessment, planning, landing zones, networking, rehosting, modernization, and code transformation. | Organizations running their own migration and modernization programs. | That every decision or change is autonomous; approvals, permissions, and customer data remain essential. |
| Agent Builder Toolkit | Tools and integration points for creating custom transformation agents that follow an organization’s methods, controls, and runbooks. | Professional-services organizations, ISVs embedding transformation functions, and enterprises encoding internal standards. | That custom agents automatically inherit AWS’s migration scope, data quality, or compliance posture. |
The toolkit layer is therefore an extension mechanism, not a separate replacement for the managed migration service. A consulting organization could encode its assessment checklist in an agent; an ISV could embed a transformation step in its product; and an enterprise could enforce internal naming, security, or approval rules. Each organization remains responsible for testing those agents and controlling what they can change.
The Tool Desk
Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →How AWS uses agents during a cloud migration
AWS presents Transform as a collaborative enterprise workbench. Agents can interpret project context, propose next actions, and execute permitted steps through connected AWS services and tools. A typical program follows a sequence like this:
- Collect and normalize inventory. Import existing discovery information or run AWS Transform discovery to identify servers, applications, dependencies, operating systems, utilization, and relationships.
- Analyze dependencies. Use dependency information to group systems that must move together and to identify network, identity, storage, and database requirements.
- Model scenarios. Compare migration approaches, target services, timing, and assumptions before committing to a wave plan.
- Plan migration waves. Organize workloads into batches with prerequisites, owners, validation checks, and rollback considerations.
- Prepare the landing zone. Create or configure the account, identity, logging, security, networking, and governance foundations required by the selected waves.
- Build or migrate the network. Translate connectivity requirements into target network resources and routing decisions, with review for security boundaries and operational ownership.
- Execute the selected transformation. Rehost servers, containerize source code for ECS or EKS, or apply another modernization path supported by the workflow.
- Validate and hand over. Check application behavior, performance, connectivity, security controls, and operational monitoring before production cutover.
Agents can reduce coordination and manual preparation across these stages, but they cannot infer facts that are absent from the inventory. An undocumented dependency, an incorrect utilization value, or an assumption about licensing can produce a neat-looking plan that is still wrong. Treat agent output as an auditable proposal and execution aid, not as an automatic approval.
What does AWS Transform automate, and what remains human work?
The service is best understood as automation with checkpoints. It can analyze data, draft plans, generate configurations, and perform approved operations. Humans still define the boundaries within which those operations are allowed.
Rank #2
Work that agents can accelerate
- Combining discovery data and identifying likely application or infrastructure dependencies.
- Comparing rehost, modernization, and containerization scenarios.
- Creating migration-wave proposals from dependency and readiness information.
- Preparing landing-zone and network configurations for review.
- Coordinating replication, testing, and cutover tasks in supported rehosting workflows.
- Applying repeatable organization-specific steps through custom agents built with the Agent Builder Toolkit.
Decisions that require customer ownership
- Whether an inventory source is complete and accurate enough to drive a migration decision.
- Which business constraints, maintenance windows, data-residency rules, licensing terms, and recovery objectives apply.
- Which proposed changes are approved for a production account and which require a separate change-control process.
- How application owners validate functionality, performance, security, and rollback readiness.
- Who owns the resulting accounts, networks, operating systems, data, and day-two operations.
This distinction is important for governance. “Agentic” describes how the service reasons across tasks and tools; it does not remove authorization, review, or accountability.
Assessment: inventories, assumptions, and cost scenarios
AWS’s May 22, 2026 assessment announcement describes a flexible intake model. You can use RVTools exports, configuration-management database (CMDB) data, AWS Transform discovery output, and third-party discovery exports. Multiple sources are useful when no single inventory covers every environment, but they also make reconciliation and timestamp management important.
Assessment features support customizable what-if assumptions, side-by-side comparisons, and total-cost-of-ownership (TCO) analysis. The announced modeling includes Amazon EC2, Amazon FSx, Amazon S3, SQL Server on EC2, virtual desktops, and other Cloud Value Framework pillars. These outputs are planning models, not quotes or guarantees: the result changes when utilization, licensing, storage growth, support choices, exchange rates, discount assumptions, or target architecture changes.
| Assessment input or feature | How it is used | Decision it can inform |
|---|---|---|
| RVTools export | Supplies virtual-environment configuration and utilization data. | Which virtual machines are candidates for rehosting and how they may size on the target. |
| CMDB data | Adds ownership, application, business, and relationship context. | Wave grouping, accountability, and dependency validation. |
| AWS Transform discovery | Provides discovery and dependency information from the migration environment. | Readiness analysis, sequencing, and network planning. |
| Third-party discovery export | Brings existing assessment data into the scenario model. | Comparison of alternative inventories and assumptions. |
| What-if assumptions | Lets teams vary target services, utilization, timing, and other model inputs. | Sensitivity analysis and a more defensible TCO range. |
For a credible assessment, record the source and collection date for every inventory, resolve duplicate hostnames and stale records, and label estimates separately from measured values. Run at least one conservative scenario in addition to the expected case so that underreported utilization or growth does not create an undersized target.
AWS Transform MGN: direct control and an agentic rehosting path
On June 8, 2026, AWS announced that AWS Application Migration Service is now named AWS Transform MGN. The announcement describes two ways to work: a direct MGN console experience for controlling replication and cutover, and an agentic workflow that connects discovery, wave planning, landing-zone setup, network creation, and rehosting or containerization.
Free tools Windows power users keep installed
One-click scans. No signup required.
The direct console path is useful when an operator needs precise control over replication settings, staging areas, test launches, cutover timing, and rollback actions. The agentic path is useful when those operations are part of a larger plan and the team wants a guided sequence across multiple services. The underlying choice is operational, not a claim that one path is universally safer.
When evaluating a rehosting wave, confirm source operating-system support, replication-agent prerequisites, network throughput, security-group rules, storage mapping, boot behavior, application test steps, and the exact cutover and rollback procedure. A successful replication job does not prove that an application is production-ready; application owners still need functional and performance validation.
Building custom transformation agents
The Agent Builder Toolkit is aimed at organizations that need transformation behavior specific to their business or delivery model.
Professional-services organizations
A services firm can encode its discovery questionnaire, architecture guardrails, evidence requirements, and sign-off process. This can make projects more consistent across consultants, but the firm must maintain versioned instructions, test unusual environments, and disclose where an agent’s recommendation requires an architect’s judgment.
Independent software vendors
An ISV can embed transformation steps in an existing product or workflow. The integration should define which AWS accounts and APIs are reachable, how customer data is isolated, how failures are surfaced, and how customers approve changes. Embedding an agent does not transfer operational responsibility away from the ISV or the customer.
Enterprise teams
An enterprise can turn internal standards into reusable agents: account naming, required tags, network patterns, security checks, data-classification rules, or application-readiness gates. Keep those standards in source control, require peer review for changes, and retain a human approval step for production mutations.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Where can teams access AWS Transform?
AWS’s launch materials describe access through the web console, command-line interface, integrated development environments, a Visual Studio extension, agent skills, and Model Context Protocol (MCP) integration. These entry points serve different users:
- Web console: visual project coordination, review, and operational control.
- CLI: scripting, repeatability, and integration with existing automation pipelines.
- IDE and Visual Studio access: code-focused modernization and developer review.
- Agent skills: reusable capabilities that can be composed into transformation tasks.
- MCP integration: a way to connect compatible orchestration clients and tools under defined permissions.
Before standardizing on an access method, test identity federation, least-privilege policies, audit logging, network paths, and the exact feature set exposed in your target AWS Region. Availability can differ by capability and region.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsPerformance claims and how to interpret them
AWS’s Migration Launch Guide reports that, in its first year, AWS Transform migrated tens of thousands of virtual machines, processed more than 4.5 billion lines of code, and saved 1.69 million hours of manual effort. The guide also describes modernization as “up to 5x faster” and cites customer-reported operating-cost reductions of “up to 70%.” These are AWS-reported or customer-reported figures, not independent benchmarks or guaranteed outcomes.
Use those numbers as directional context rather than a business case. A fair internal baseline should measure your own discovery duration, planning effort, wave throughput, defect rate, rollback frequency, and post-cutover operating cost. Separate labor savings from infrastructure savings, and document whether a result came from automation, architecture change, pricing commitments, or workload retirement.
Pricing, regions, and compliance: verify before committing
The materials available for this overview do not establish a single AWS Transform price or a complete regional eligibility matrix for every capability. Costs may involve the service itself, underlying AWS resources, data transfer, storage, logging, and any custom-agent infrastructure. Obtain current pricing details for the exact features, accounts, and regions in your design.
The June 8, 2026 naming announcement says AWS Transform MGN retains the listed compliance certifications and is available in commercial and US GovCloud regions. Treat that as a dated announcement, not a substitute for current service documentation. Verify the certification scope, feature-level regional availability, data-processing location, and GovCloud-specific limitations before a regulated migration.
AWS identifies migration consulting and professional-services organizations as potential users of the agent-building toolkit, but no referral, commission, or participating-provider arrangement is established here. Any commercial relationship should be confirmed through current AWS partner documentation and a written statement of terms.
Is AWS Transform a fit for your migration?
AWS Transform is a strong candidate when a program has many workloads, fragmented inventory sources, repeated migration patterns, or a need to connect assessment with execution. It is less likely to be a quick answer for a single, well-understood application whose team already has a tested deployment path.
Quick Recap
Choose a pilot when
- You can provide a representative inventory, including dependencies and ownership data.
- You have a non-production wave with measurable success criteria.
- Security and platform teams can review the permissions and generated configurations.
- You are prepared to compare agent recommendations with an existing manual baseline.
Delay broad rollout when
- Asset records are stale, contradictory, or missing business owners.
- Critical dependencies are undocumented or cannot be observed safely.
- There is no agreed rollback, validation, or production-change process.
- Your target region or compliance requirements have not been confirmed for each needed capability.
A practical adoption sequence
- Define the boundary. Decide whether the first project is assessment only, rehosting, containerization, or a custom-agent experiment.
- Prepare evidence. Gather RVTools, CMDB, discovery, and application-owner data; label collection dates and confidence levels.
- Set assumptions explicitly. Record utilization, growth, licensing, availability, recovery, and cost assumptions before comparing scenarios.
- Pilot one wave. Select workloads that are representative but reversible, and measure effort, defects, and validation time.
- Establish controls. Use least-privilege roles, approval gates, logging, versioned agent instructions, and documented rollback.
- Review the economics. Compare modeled TCO with observed AWS consumption and labor, then update assumptions before scaling.
- Scale patterns, not blind automation. Reuse proven agents and runbooks while retaining exception handling for workloads that do not fit the pattern.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
