AWS Cloud Migration Services - Complete Blog Package

Moving workloads to AWS is not simply an infrastructure relocation project. It requires business-case validation, application discovery, dependency mapping, workload classification, landing-zone preparation, migration-wave planning and post-cutover measurement.

Effective AWS cloud migration services bring these activities together in one delivery plan. The objective is to determine what should move, why it should move, which migration path each workload should follow and how the organization will control cost, security, downtime and operational risk.

This guide presents a seven-stage framework for planning an enterprise AWS migration, including data center, application and Azure-to-AWS migration scenarios.

What are AWS cloud migration services?

AWS cloud migration services cover the assessment, planning, movement, validation and ongoing management of applications, infrastructure and data moving to Amazon Web Services. The scope may include data center migration, virtual machine migration, application and API migration, database movement, Azure-to-AWS migration, identity and network architecture, landing-zone design, cost forecasting, cutover planning and post-migration monitoring.

A migration provider should not begin by assuming every workload belongs in AWS. The assessment must also identify applications that should be retained, retired or replaced. This prevents teams from paying to move technical debt or low-value systems that no longer support a business requirement.

1. Define the business problem and workload scope

The first stage is to establish why the migration is being considered. Common reasons include a data center contract renewal, unsupported infrastructure, rising licensing costs, reliability concerns, acquisition-related consolidation or a need to support new analytics and AI programs.

Each objective should become a measurable migration outcome. A data center exit can be measured by workloads removed before the facility deadline. Reliability can be assessed through availability and recovery targets. Cost control requires comparing a current-state baseline with the forecast and actual AWS expense. Application risk can be tracked through the number of unsupported systems removed.

The inventory should cover servers, applications, databases, interfaces, identities, certificates, network connections, batch jobs and external dependencies. Missing a scheduled process or third-party interface can create more cutover risk than missing a server.

2. Assess applications, infrastructure and dependencies

A migration assessment establishes the current-state baseline. It documents resource utilization, software versions, licensing, business criticality, recovery requirements and application dependencies.

AWS Migration Evaluator can use an agentless collector or existing inventory data to support a directional business case. It helps compare the current environment with possible AWS configurations and projected costs. Its discovery information can also support server dependency mapping in AWS Migration Hub.

Assessment work should collect infrastructure and utilization data, group servers by business application, identify upstream and downstream connections, record business owners, document compliance requirements, establish recovery baselines and identify remediation needed before migration.

For an Azure-to-AWS migration, the assessment should also examine Azure-native dependencies. Applications using Microsoft Entra ID, Azure Functions, Azure SQL, Service Bus or Azure Monitor may require service mapping and application changes rather than direct relocation.

3. Select a migration path using the 7 Rs

AWS defines seven migration strategies: retire, retain, rehost, relocate, repurchase, replatform and refactor or re-architect. The right strategy should be selected for each application rather than applied to the portfolio as a whole.

Retire applies when an application no longer provides sufficient business value. Retain is appropriate when regulation, specialized hardware or unresolved dependencies block movement. Rehost moves an application with few changes. Relocate transfers a supported platform without redesigning its applications. Repurchase replaces the current system with another product. Replatform introduces limited changes, such as moving a database to Amazon RDS. Refactor changes the application architecture when the expected business value justifies the added effort.

AWS advises that refactoring is generally not the default choice for a large migration because changing many applications during the move introduces additional complexity. A practical program may first rehost or replatform selected workloads and plan deeper application changes separately.

Which workloads should move first? A strong first wave normally contains low-to-moderate-risk applications with understood dependencies, engaged owners and representative technical patterns. The first wave should test the delivery method without placing the most critical system at unnecessary risk.

4. Prepare the AWS services and target architecture

The target architecture should be ready before production migration waves begin. A landing zone establishes the AWS account structure, identity model, network connectivity, logging, security policies and operating controls. AWS Control Tower can support multi-account governance, account provisioning and centralized oversight.

The design should address AWS Organizations and account structure, identity and access management, network segmentation, centralized audit records, encryption standards, backup policies, resource tagging, cost allocation, monitoring and incident-management integration.

The workload determines which migration services are appropriate. AWS Application Migration Service may support server rehosting, while AWS Database Migration Service may be considered for suitable database movements. Migration Evaluator supports business-case planning, and Migration Hub may appear in established environments for discovery and dependency information.

AWS now redirects the former Migration Hub product page to AWS Transform. Teams should therefore confirm current product availability, capability names and regional support during architecture planning rather than copying an older tool list into a new statement of work.

5. Deliver the migration in controlled waves

A migration wave is a group of related applications, infrastructure and data moved under one coordinated plan. The seven delivery stages are: define outcomes and scope; assess assets and dependencies; assign a 7 Rs strategy; prepare the landing zone; move workloads in waves; validate and cut over; then measure operational results.

Each wave should have entry criteria, an accountable business owner, technical runbooks, a change window, validation tests and a rollback decision point. The plan should also account for shared components. Moving an application before its authentication service, file-transfer process or reporting database is ready can create avoidable disruption.

For data center migration, teams should group workloads by dependency rather than simply by server location. For application migration, every wave should include infrastructure, code, data, integration and business-testing tasks.

6. Apply security and governance before cutover

Security should be designed into the landing zone and workload plan before data is moved. Required controls may include least-privilege access, encryption, centralized logging, vulnerability management, network inspection, backup policies and separation between production and nonproduction environments.

The migration team should document who can approve and perform migration actions, how privileged access is reviewed, which data requires encryption or residency controls, where audit records are stored, how findings are handled before cutover and which policies apply at account, platform and workload levels.

Governance also covers ownership. Every migrated application needs an identified business owner, technical owner, cost center, support process and recovery requirement.

7. Control migration cost and downtime

Migration cost should be evaluated using measured utilization rather than source-server specifications alone. An oversized source environment can produce an inflated AWS forecast if every server is mapped directly to an equivalent configuration.

The business case should include migration labor, temporary parallel environments, network and data-transfer charges, software licensing, AWS consumption, backup resources, monitoring, application remediation and post-migration cost reviews.

Downtime planning should define the cutover sequence, data replication approach, outage window, business approvals and rollback threshold. Zero downtime should not be promised without a tested architecture and workload-specific evidence.

Info Services reports that one industrial IoT engagement reduced AWS spend by 30% after its architecture was redesigned around microservices, machine-learning operations and a new data platform. This published result supports the value of continuing cost review after workloads are running on AWS.

Validate, cut over and preserve a rollback path

Technical migration completion is not the same as business acceptance. Validation should test application functions, integration flows, security controls, data reconciliation, performance, backups, monitoring and recovery procedures. Business owners should approve the results before the source environment is retired.

A rollback plan should define the event that triggers rollback, who makes the decision, how replicated data is handled, how traffic returns to the source, how long the source remains available and what evidence is required before another cutover attempt.

After cutover, teams should compare actual AWS cost, performance, incidents and availability against the baseline established during assessment.

Migration proof: moving an IoT platform from VMware to AWS

In a published Info Services engagement, a three-tier IoT platform running on VMware was experiencing reliability concerns and increased application downtime.

The AWS architecture used services including Amazon ElastiCache, Amazon RDS, Amazon DynamoDB, Amazon Athena, Amazon QuickSight, Amazon Kinesis and Amazon Redshift. External storage was moved to Amazon S3, while the security design included AWS Identity and Access Management, AWS Key Management Service, AWS WAF and Amazon Inspector.

This case illustrates why application migration planning must cover more than compute. The work involved storage, databases, analytics, security, application administration and operating requirements.

The public case study does not provide a migration timeline or cutover-downtime figure. Those details should not be added to marketing content unless they are confirmed and approved by the client.

Validate, cut over and preserve a rollback path

Technical migration completion is not the same as business acceptance. Validation should test application functions, integration flows, security controls, data reconciliation, performance, backups, monitoring and recovery procedures. Business owners should approve the results before the source environment is retired.

A rollback plan should define the event that triggers rollback, who makes the decision, how replicated data is handled, how traffic returns to the source, how long the source remains available and what evidence is required before another cutover attempt.

After cutover, teams should compare actual AWS cost, performance, incidents and availability against the baseline established during assessment.

Migration proof: moving an IoT platform from VMware to AWS

In a published Info Services engagement, a three-tier IoT platform running on VMware was experiencing reliability concerns and increased application downtime.

The AWS architecture used services including Amazon ElastiCache, Amazon RDS, Amazon DynamoDB, Amazon Athena, Amazon QuickSight, Amazon Kinesis and Amazon Redshift. External storage was moved to Amazon S3, while the security design included AWS Identity and Access Management, AWS Key Management Service, AWS WAF and Amazon Inspector.

This case illustrates why application migration planning must cover more than compute. The work involved storage, databases, analytics, security, application administration and operating requirements.

The public case study does not provide a migration timeline or cutover-downtime figure. Those details should not be added to marketing content unless they are confirmed and approved by the client.

Build an evidence-based AWS migration plan

A defensible migration plan begins with workload facts rather than assumptions. It should show the current environment, application dependencies, selected workload paths, landing-zone requirements, migration waves, cost baseline, cutover controls and success measures.

Info Services provides AWS assessment, migration planning, workload migration and ongoing support backed by published AWS delivery experience.