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1Scan for outdated or missing drivers - takes under a minute2Clear out junk files and repair common Windows errors3Fix the driver behind crashes, sound loss and screen glitchesTreat an AI-generated cloud migration plan as a proposal, not as evidence. Before implementation, verify its workload facts against current organizational records, confirm each migration choice with the people accountable for the workload, and require a target design, test criteria, cutover conditions, and rollback decision that your organization can actually execute.
Cloud-provider guidance from Google Cloud, AWS, and Microsoft supports these validation practices for migration plans generally; it does not establish how accurate AI-generated plans are or guarantee that any checklist will catch every error.
What evidence should you gather first?
Build a trusted evidence packet for each workload before reviewing the plan’s proposed design. Use current organizational records and mark anything that is stale, missing, or inferred rather than letting fluent generated text fill the gap.
- Application and infrastructure inventory, including versions, configurations, and accountable owners.
- Dependency map covering upstream and downstream systems, integrations, identity services, and data flows.
- Business goals, service-level requirements, downtime tolerance, data classification, and applicable security or compliance obligations.
- Source-environment configuration, network assumptions, operating procedures, backup and recovery arrangements, and support responsibilities.
- Current performance and functional results, plus the cost baseline and the assumptions behind it.
Google Cloud’s migration-plan validation guidance emphasizes checking inventory currency, source-data reliability, and assessment gaps. AWS’s portfolio assessment guidance likewise frames discovery, analysis, and planning as iterative work that includes technical assessment and target design. Those recommendations make a useful distinction for an AI draft: label each material statement as a verified fact, an owner-confirmed assumption, an unresolved question, or a proposed decision. That labeling is a practical review method, not an AI-specific procedure prescribed by either provider.
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Does the plan cover the right workloads and dependencies?
Review scope one workload at a time. Confirm which components are included, which are deliberately excluded, and whether the proposed migration benefit follows from the business goal. Check the actual dependency map rather than relying on a generated diagram or component list.
- Confirm upstream and downstream integrations, data movement, and any sequencing constraints.
- Verify who owns the workload and its configuration, and how configuration changes will be made during migration.
- Check downtime limits, clustering or redundancy, and any special transfer or cutover requirements with the service owner.
- Ask whether retaining a workload in place is a valid option, and what would justify deferring its migration.
Google Cloud specifically highlights downtime windows, redundancy, configuration updates during migration, and the extra complexity of pursuing zero downtime. Microsoft advises relating business drivers to migration strategy while screening out choices that conflict with security, compliance, or operational constraints.
Portfolio assessment is not necessarily a one-time spreadsheet exercise. AWS gives an indicative planning sequence in which initial discovery typically starts in the first five weeks, prioritized application assessment spans weeks six and seven, and portfolio analysis and migration planning occurs in weeks eight through fourteen. AWS notes that actual timing depends on program organization; these ranges are not a universal schedule.
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Is the migration strategy justified for each workload?
Require a workload-specific reason for the selected strategy, the alternatives considered, expected changes to code and operations, assumptions about service equivalence, and the consequences of retaining or deferring migration. Microsoft’s migration guidance distinguishes these common strategies:
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| Strategy | What it means | Review question |
|---|---|---|
| Rehost | Move with minimal changes. | Will the move carry existing performance, reliability, or architecture problems forward? |
| Replatform | Make limited changes to use a platform service. | Are the service’s features, data behavior, and integrations sufficient for this workload? |
| Refactor | Change code while preserving external behavior. | What code changes and regression tests are required to preserve that behavior? |
| Rearchitect | Redesign the workload to use cloud-native capabilities. | Does the expected benefit justify the greater design and delivery change? |
| Replace | Move to a different product or solution. | Does the proposed replacement meet the workload’s functional and operational needs? |
| Rebuild | Build the workload again in the target environment. | What functionality, data, and integrations must be recreated and verified? |
| Retire | Remove a workload that is no longer needed. | Have owners confirmed that dependencies, retained data, and required records are addressed? |
| Retain | Keep a workload where it is for now. | What constraint or business reason supports retaining it, and when should the decision be revisited? |
The Microsoft guidance says strategy depends on the desired degree of change, workload characteristics, complexity, timeline, readiness, integration complexity, and constraints. Treat a provider-to-provider service mapping in the plan as a hypothesis: verify feature, performance, data, and integration requirements rather than assuming every source component has a direct counterpart.
Is the target foundation secure and ready?
A target architecture diagram is not enough. Confirm that the landing zone or equivalent target foundation is prepared for this workload and that controls cover both the cloud environment and the application being moved.
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- Foundation: Check account or subscription structure, network design and segmentation, and required connectivity.
- Access and data: Review identity and access, encryption, and the handling of classified or regulated data.
- Detection and prevention: Verify preventive controls, logging, monitoring, and alerting.
- Workload layers: Review service configuration, operating-system protection and patching, and application or database configuration.
- Integration: Confirm that security and operational services the application depends on are identified and connected.
AWS’s secure-migration guidance organizes review across infrastructure, cloud services, operating systems, and applications or databases. It also calls for identifying integrations during assessment. Review security at two levels: workload-specific vulnerability assessment and penetration testing, and assessment against cloud security best practices or benchmarks. AWS names the Well-Architected Framework and CIS benchmarks as examples; it also lists AWS Trusted Advisor, Prowler, AWS Service Screener, and AWS Self-Service Security Assessment as possible tools. Check each tool’s current support and appropriate scope before relying on it; inclusion in that guidance is not an endorsement or guarantee of coverage.
Record findings, remediation decisions, and exceptions, and obtain sign-off from the relevant security stakeholders. AWS explicitly recommends documenting remediation exceptions and securing the respective stakeholders’ approval.
Can the organization operate and deploy the target workload?
Check whether the proposed operating model exists in practice, not just in the architecture description. Review the CI/CD pipeline and lifecycle tooling for compatibility with the target cloud, including whether provisioning or deprovisioning steps need to change.
Rank #4
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- Confirm runbooks, support ownership, identity integrations, and incident-response responsibilities.
- Verify that monitoring, backup, restore, and operational alerting fit the target environment.
- Review infrastructure-as-code coverage and the accuracy of records for workloads, relationships, and configuration changes.
- Check that surrounding network components are part of the deployment and validation plan. A rehost may still require deployment and validation of VPCs, subnets, security groups, network ACLs, or load balancers.
A list of standard cloud services in a generated plan does not establish that the organization can deploy, secure, support, or recover the workload with them. Require the relevant platform and workload owners to confirm the actual procedures and responsibilities.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What must pass before production cutover?
Set acceptance criteria before execution so that test results can be judged against an agreed baseline rather than against an impression that the migration “looks right.” Microsoft’s guidance calls for evaluating the migrated workload against functional, performance, security, and cost requirements set against the baseline.
- Capture the baseline. Record current functional behavior, integration paths, performance results where relevant, security requirements, and the agreed cost comparison basis.
- Define pass thresholds. Specify which user-visible functions, integrations, service levels, and security checks must pass, who evaluates them, and what result blocks cutover.
- Repeat comparable tests. Run minimal functional tests for basic application paths and integrations. For performance-sensitive workloads, repeat the same test suite used for the baseline; AWS warns that results from different tools do not provide the same assurance for comparison.
- Validate the migration mechanics safely. Where appropriate, perform a test cutover or use an isolated clone to verify the workload starts and connects in the target environment. AWS says a server test cutover is essential to confirm that its migration service can create a bootable clone. It recommends an isolated subnet, particularly for Windows workloads connected to Active Directory, to protect live systems and data.
- Agree the traffic and recovery decision. Document cutover conditions, who can authorize production redirection, the rollback trigger, and the recovery action before traffic moves.
Do not make zero downtime a default requirement. Google Cloud advises weighing the business benefit against the added migration complexity and designing redundancy when a workload genuinely needs zero or near-zero downtime.
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How should you compare competing plans?
Use the same review criteria for each alternative and have the workload owner, platform or architecture reviewer, and security reviewer assess the evidence relevant to their responsibilities. Adapt the criteria to the organization’s requirements rather than treating them as a universal scorecard.
| Comparison area | What to compare |
|---|---|
| Business fit | Whether the plan advances the stated goal and whether each workload belongs in scope. |
| Strategy and change | Per-workload strategy, amount of code and operational change, and alternatives considered. |
| Evidence confidence | Inventory currency, dependency confidence, verified facts, and unresolved assumptions. |
| Target compatibility | Architecture, service capabilities, data behavior, and integration fit. |
| Risk and controls | Downtime and cutover risk, security and compliance coverage, and documented exceptions. |
| Readiness and testing | Operational and CI/CD readiness, baseline quality, acceptance criteria, and rollback approach. |
| Cost and open issues | Cost assumptions against the agreed baseline, plus unresolved dependencies or decisions. |
What should the review record contain?
Keep a traceable decision record for each workload. It should make clear which assertions are supported by organizational evidence and who has accepted the remaining risk.
- The inventory and dependency sources used, with their dates or known limitations.
- The selected strategy, the alternatives considered, and the owner-approved rationale.
- Target architecture and control findings, including exceptions, remediation owners, and security sign-off.
- Baseline measures, test results, acceptance decisions, cutover authorization, and rollback criteria.
- Unresolved questions, assigned owners, and decisions that must be revisited before implementation.
This review can reduce unsupported assumptions in the proposal, but it cannot establish plan-specific truth without the organization’s inventory, dependency evidence, obligations, and acceptance criteria. The provider guidance cited here describes general migration validation; it does not report trials or accuracy measurements for AI-generated plans.
Quick Recap
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