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AWS Cloud Migration Services: Tools, Strategy, And Costs

Vikas Singh
Vikas Singh
February 24, 2026
Clock icon11 mins read
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Introduction

Your engineering team is juggling three things at once: aging on-premises infrastructure that costs too much to maintain, pressure from leadership to cut downtime risk, and a cloud modernization roadmap that keeps slipping. Sound familiar? AWS migration services exist precisely for this situation. They give organizations a structured set of tools and support options to move workloads, databases, and infrastructure into AWS without treating it as one giant, chaotic lift.

So what actually falls under that umbrella? At its core, AWS migration services cover native AWS tools like Migration Hub, Application Migration Service, and Database Migration Service, plus partner programs and professional consulting support. Companies evaluate them when they need a repeatable, lower-risk path to cloud rather than a DIY approach that stretches internal teams past their limits.

This article walks through five decision areas that determine whether your migration succeeds: which strategy fits your workload, which tools handle the actual move, how to set up security and compliance from day one, what the real costs look like, and how to choose between self-executing and partner-led delivery models.

What AWS migration services include

AWS migration services cover far more ground than most teams expect going in. The full scope runs from initial environment discovery through post-migration cost tuning, and knowing where each piece fits saves you from treating this like a simple server-copy exercise.

At the broadest level, AWS migration tools and services fall into three delivery models: native AWS capabilities you operate yourself, AWS-led professional services, and partner-managed migration programs. Each serves a different buyer profile and project complexity.

The table below maps the six core service categories across all three delivery models so you can see the big picture before getting into individual tools.

Service CategoryWhat It CoversWho Typically Owns DeliveryWhen It Fits
Assessment and discoveryEnvironment scanning, dependency mapping, application inventory, migration wave planningCustomer using native tools, or partner-led workshopsEvery migration, regardless of size or complexity
Landing zone setupMulti-account structure, VPC design, IAM policies, logging and compliance guardrailsAWS Professional Services or certified partnerBefore any workloads move, not after
Server migrationReplication of physical, virtual, or cloud-based machines to EC2Customer self-service for lift-and-shift, partner for complex portfoliosRehost and replatform strategies
Database migrationHomogeneous and heterogeneous database transfers with minimal downtimeCustomer-managed for straightforward moves, partner for schema conversion projectsAny migration where data continuity is non-negotiable
Cutover and validationCutover runbooks, rollback planning, user acceptance testing, go-live coordinationShared between internal teams and delivery partnerFinal phase of every migration wave
Post-migration optimizationRight-sizing, auto-scaling configuration, cost governance, cloud-native transitionsCustomer engineering team, optionally with partner or AWS supportOngoing after each migration wave completes

One thing worth calling out explicitly: this table is your orientation map, not your implementation guide. The sections that follow go deeper on specific tools and execution patterns. The point here is that AWS migration services are a pipeline, not a product. You do not buy a single thing and get migrated. You move through phases, and different people own different phases depending on your internal capacity and the complexity of what you are moving.

If your team is running a greenfield workload with a handful of servers, you can cover most of this yourself using native AWS capabilities. If you are untangling a legacy monolith with shared databases and compliance obligations, that landing zone setup and cutover coordination column starts looking like strong candidates for outside help.

AWS migration services strategy: roadmap, migration waves, and the 7 Rs migration strategy

A solid AWS migration strategy doesn't start with tools. It starts with knowing exactly what you're moving, why, and in what order. Most migration failures trace back to skipping that discipline.

The practical roadmap breaks into five stages: assessment and mobilization, pilot wave, production migration waves, cutover, and post-migration optimization. You run these in sequence because each stage validates assumptions before you commit the next batch of workloads.

Assessment and mobilization is where AWS Application Discovery Service earns its keep. Deploy agents on your servers to capture real performance data, network connections, and process dependencies. Don't guess at dependencies. Map them. A web server that quietly calls a licensing service on port 8443 can break your migration if you move them in separate waves without accounting for that connection.

Once you have that dependency map, you build migration waves. Group tightly coupled applications together. Put lower-risk, lower-complexity workloads in your first wave to validate your runbooks before you touch anything critical.

The 7 Rs migration strategy gives you a decision framework for each workload, not just a taxonomy:

StrategyUse it whenAvoid it when
RehostSpeed matters most, deadline pressure is realYou need performance improvements immediately
ReplatformQuick win possible, like moving to RDSApp logic tightly coupled to OS-level configs
RefactorModernization ROI is clear, app needs to scaleTimeline is short or codebase is poorly documented
RepurchaseA SaaS alternative covers 90 percent of your use caseHeavy customization that SaaS can't support
RetireApp has no active users or duplicates another systemBusiness hasn't confirmed the decommission
RetainCompliance or licensing blocks cloud deploymentYou're just avoiding migration work
RelocateVMware-heavy environment, bulk server move neededYou want to modernize, not just shift

A concrete example: Take a three-tier application with a SQL Server backend, a .NET application layer, and an IIS frontend. Your discovery phase reveals the app tier calls a legacy reporting service that nobody documented. That dependency shows up in the Application Discovery Service network graph. You add that reporting service to the same migration wave or you provision it in AWS first.

You rehost the IIS and .NET layers using AWS Application Migration Service. For SQL Server, you evaluate replatforming to Amazon RDS for SQL Server to drop the DBA overhead, keeping the app code unchanged. The reporting service gets retired entirely because the business confirms it hasn't been used in 14 months.

Before cutover, you run load tests against the replicated environment and verify replication lag is under acceptable thresholds. Your cutover runbook documents every step: freeze writes on the source database, let DMS sync the final transactions, flip DNS, and validate application health endpoints. For the frontend, you run a blue-green deployment that keeps the old environment live until your monitoring confirms the new one is clean.

Common blockers at this stage include license portability issues for SQL Server, firewall rules that weren't captured in discovery, and on-premises Active Directory dependencies that need AWS Managed AD or a trust relationship before the application layer can authenticate.

Optimization comes after stabilization, not before. Right-size instances based on 30 days of actual CloudWatch data, then layer in auto-scaling where traffic patterns justify it.

AWS migration tools compared: Migration Hub, Discovery Service, AWS Application Migration Service, AWS Database Migration Service, DataSync, and Snowball

Not all AWS migration tools do the same job. Using the wrong one for your workload adds complexity, cost, and risk. Here's a direct comparison of the core tools so you can match the right one to your actual situation.

ToolBest Use CaseWorkload or Data TypeDowntime ProfileReplication MethodTypical ComplexityCommon Limitations
Migration HubPortfolio tracking and status visibilityAll workload typesNo downtimeAggregates data from other toolsLowDoes not move anything itself
Discovery ServiceDependency mapping before migrationOn-premises servers and VMsNo downtimeAgent-based or agentless scanLow to mediumAgentless mode misses process-level dependencies
AWS Application Migration ServiceServer lift-and-shiftPhysical, virtual, or cloud serversMinutes at cutoverContinuous block-level replicationMediumNeeds agent on every source server
AWS Database Migration ServiceDatabase moves with minimal interruptionRelational and NoSQL databasesNear-zero with CDCContinuous change data captureMedium to highHeterogeneous migrations require Schema Conversion Tool separately
DataSyncOnline file and object transferNFS, SMB, S3, EFS, FSxMinimal, incremental syncsScheduled or continuous sync tasksLowNot suited for databases or active transaction logs
SnowballOffline or edge transferLarge unstructured datasets, backupsExtended, planned windowPhysical appliance shipmentMediumTurnaround time is days, not hours

When each tool actually gets chosen

Migration Hub matters most when you are running parallel workstreams and need one place to see what has moved, what is in-flight, and what is stuck. Without it, large migrations turn into spreadsheet chaos.

Discovery Service is the first tool you deploy. Before you can plan migration waves or identify which servers move together, you need dependency maps. Agent-based discovery gives you network connection data and process-level detail. Skip this step and you will break applications mid-migration because you missed a hidden dependency.

AWS Application Migration Service handles the heavy lifting for server migrations. A retail company migrating 200 mixed Windows and Linux servers uses it to replicate continuously while keeping production running, then cuts over application by application during low-traffic windows.

Database modernization scenarios are where AWS Database Migration Service earns its complexity. Moving Oracle to Aurora PostgreSQL requires schema conversion first. The Schema Conversion Tool analyzes stored procedures, data types, and triggers, flags what needs manual rewriting, and generates the conversion scripts. Plan for a review cycle before you even start data replication.

Large file estates with hundreds of terabytes over reasonable bandwidth? That is a DataSync job. A media company migrating a video archive to S3 runs DataSync tasks on a nightly schedule for weeks before cutover, so the final sync window is measured in gigabytes rather than petabytes.

Snowball solves the bandwidth problem entirely. If transferring your data over the network would take six weeks, AWS ships you physical appliances, you load them on-premises, and ship them back. An energy company migrating seismic data archives too large for practical network transfer uses exactly this pattern. The tradeoff is lead time: factor several days for shipping on each end.

These AWS migration tools work best as a coordinated set rather than standalone choices. Discovery feeds Migration Hub. Application Migration Service reports status back to the hub. Database Migration Service runs alongside server replication so application and data layers land in AWS at the same time.

AWS migration services for landing zone, networking, security, and compliance

Before a single production workload moves, your AWS foundation needs to be complete. Not mostly done. Not "good enough for now." Fully built, tested, and validated. Rushing this step is the single most common reason migrations turn into expensive recovery projects.

Start with your account structure. AWS Control Tower gives you a governed multi-account landing zone with pre-built guardrails, centralized logging, and identity baselines without hand-coding every policy. If your governance requirements are highly custom, you can build the same structure manually using AWS Organizations plus Terraform or CloudFormation, but expect significantly more implementation time. Either way, the architecture separates migration staging accounts from production accounts with hard IAM boundaries, not just naming conventions.

Your IAM design matters more than most teams realize. Use permission boundaries on all IAM roles to cap what engineers can grant themselves during migration sprints. Service control policies at the organizational unit level enforce non-negotiable controls, such as blocking public S3 buckets or requiring encryption, regardless of what individual account admins configure. Every privileged action should route through roles with MFA enforcement, not long-lived access keys.

Logging belongs in a dedicated security account from day one. CloudTrail, Config, and VPC Flow Logs all feed into centralized S3 buckets with object lock enabled. AWS Key Management Service handles encryption key management, with separate customer-managed keys for production, staging, and shared services. This separation matters for audit scoping, not just security.

Compliance control mapping across common frameworks:

Control AreaHIPAAPCI DSSSOC 2
Encryption at restRequired (PHI data)Required (cardholder data)Required by most trust criteria
Audit logging retention6 years minimum1 year (3 months online)Defined by audit period plus buffer
Vulnerability managementRequiredQuarterly scans plus penetration testingCommon Criteria CC7.1
Access reviewPeriodic review requiredQuarterly for privileged accessCC6.3 ongoing review
Evidence retention6 years1 year minimumPer audit engagement scope

Pre-migration security checklist:

  • Multi-account landing zone deployed with organizational unit hierarchy
  • Service control policies enforcing encryption and logging requirements
  • Centralized CloudTrail and Config logging to a locked security account
  • KMS customer-managed keys provisioned per environment
  • IAM permission boundaries applied to migration execution roles
  • VPC CIDR ranges validated against on-premises address space
  • DNS resolution strategy documented for hybrid connectivity
  • Migration staging VPCs fully segmented from production VPCs

Now, connectivity. Your choice of hybrid network architecture directly affects migration throughput, and you need to pick the right one before replication agents start running.

Use Direct Connect when you're moving terabytes of data and need consistent, predictable bandwidth. A 10 Gbps Direct Connect circuit lets Application Migration Service replicate dozens of servers concurrently without fighting for internet bandwidth. Latency stays low and consistent, which matters for database replication lag during continuous sync.

VPN is the right call for lower-volume migrations or as a redundant backup path alongside Direct Connect. Performance varies with internet conditions, so don't plan your cutover timeline around VPN throughput for large datasets.

Transit Gateway becomes necessary when you're managing multiple VPCs across accounts and need centralized routing control. It replaces a mess of individual VPC peering connections with a single hub that enforces routing policies at scale. For most mid-sized migrations with five or more accounts, Transit Gateway simplifies operations and makes DNS resolution across accounts predictable.

VPC peering works fine for simple two-account scenarios, typically connecting a migration staging account directly to a production account during cutover. Once you add more accounts or need transitive routing, peering becomes unmanageable.

The staging-to-production segmentation piece is non-negotiable for regulated workloads. Replicated servers in your migration staging VPC should never have direct network paths to production databases until you explicitly open them during validated cutover windows. Security groups and network ACLs both need to reflect this boundary, not just routing tables.

AWS migration cost: pricing, fees, and sample estimates by migration size

AWS migration cost hits you from two directions at once: the one-time expense of actually executing the move, and the ongoing monthly AWS run-rate you inherit the moment workloads go live. Conflating the two is how budgets blow up. Keep them separate in your planning.

Where the one-time costs come from

Discovery and assessment tools like Application Discovery Service are low-cost, but the engineering hours to interpret dependency maps and assign migration strategies are not. Budget real time here, not token effort.

Replication costs during the migration itself include the staging EC2 instances and EBS volumes that Application Migration Service spins up in your account. These run continuously until cutover, so a slow migration is a more expensive one.

Data transfer out of your on-premises environment into AWS is free inbound. What catches people is transfer between AWS regions, transfer between Availability Zones, and NAT gateway charges once workloads are live. DataSync charges $0.0125 per GB moved, which sounds trivial until you are pushing 50 TB.

Partner and professional services fees vary the most. A certified AWS migration partner for a mid-sized engagement typically bills $150 to $250 per hour for architects and engineers. Fixed-price packages exist for commodity lift-and-shift work but rarely apply to anything with real complexity.

Post-cutover optimization, right-sizing instances, setting up auto-scaling, and transitioning rehosted workloads to managed services, adds weeks of engineering that most first-time budgets omit entirely.

Direct charges versus ongoing run-rate

Direct migration charges are finite. Ongoing AWS infrastructure costs are not, and they are what you will actually live with for years.

A t3.medium in US East runs around $0.04 per hour on-demand. General-purpose SSD storage on EBS costs roughly $0.10 per GB per month. Outbound internet traffic starts at $0.09 per GB for the first 10 TB. Reserved Instances and Savings Plans can cut compute costs by up to 72 percent for steady-state workloads, but you need at least 30 to 60 days of post-migration data before committing. Buying reservations against over-provisioned instances is a common and expensive mistake.

Sample estimates by migration size

These numbers are illustrative, not quotes. Your actual costs depend on your environment, chosen strategies, and how much application refactoring your workloads require.

Small migration: 10 to 20 servers, mostly rehost

Discovery and planning takes roughly two to three weeks of engineering time, call it $15,000 to $25,000 for external help or internal equivalent. Replication staging costs run $500 to $1,500 depending on how long you keep the staging environment active. Data transfer for a typical 5 to 10 TB dataset runs a few hundred dollars inbound. Post-cutover optimization adds another $5,000 to $10,000 in engineering. Target AWS run-rate for 15 rehosted servers lands around $3,000 to $6,000 per month before Reserved Instance pricing.

Mid-sized migration: 50 to 150 servers, mixed rehost and replatform

Partner engagement fees typically run $80,000 to $200,000 for this scope. Database migrations using DMS add replication instance costs of $500 to $2,000 per month during the migration window. Staging and testing environments double your compute bill temporarily. Post-migration optimization for right-sizing and auto-scaling configuration adds $20,000 to $40,000 in professional services. Monthly AWS run-rate typically lands between $25,000 and $60,000 depending on instance types and data transfer volume.

Enterprise migration: 300+ servers, multi-application with refactoring

Total migration cost routinely reaches $500,000 to several million dollars when you factor in architecture redesign, multiple migration waves, parallel team workstreams, and extended dual-operation periods. Monthly AWS run-rate for enterprise-scale environments varies so widely that any single number is misleading. The AWS Pricing Calculator is the right tool for modeling your specific architecture. For a deeper walkthrough on structuring that estimate and avoiding the common traps, see our cloud cost estimation guide.

The pattern across all three scenarios is the same: labor and professional services dominate one-time costs, and compute plus data transfer dominate the ongoing bill. Teams that want to reduce waste after cutover should also build in a plan for post-migration optimization, especially once real usage data starts replacing pre-migration assumptions.

How to choose the right AWS migration services: native tools, AWS MAP, partners, or internal teams

Four delivery models exist for AWS migration services, and picking the wrong one costs you either money or months.

Here is how each option actually works:

Delivery ModelWhat it doesWhat it does NOT do
Internal team + native AWS toolsRuns migrations using MGN, DMS, DataSync, Migration HubProvides external expertise, architectural review, or funding
AWS Professional ServicesDesigns architecture, leads complex transformations, trains internal staffExecutes day-to-day migration work at scale for mid-market budgets
AWS Support plansReactive technical guidance, operational advice, TAM access at Enterprise tierManages your migration or writes your runbooks
AWS Partner (MSP or SI)Handles end-to-end execution, brings proprietary tooling, waves-based deliveryReplaces your internal ownership of the migrated environment post-launch

Where AWS MAP fits into this picture. The AWS Migration Acceleration Program is a funding and support framework, not a separate tool or service team. Qualifying organizations receive AWS credits to offset migration costs, access to prescriptive migration guidance, and in some cases co-investment from AWS toward professional services engagements. MAP eligibility typically requires working with an AWS Partner who holds Migration Competency status. If your partner does not mention MAP during scoping, ask directly, because the credits can be substantial on larger migrations.

AWS Professional Services is rarely involved in straightforward lift-and-shift projects. Their engagements make sense when you are modernizing a core platform, navigating a regulated industry with complex compliance requirements, or running a transformation that needs AWS's internal architectural resources. For most commercial migrations, a qualified AWS Partner covers the same ground at lower cost.

Checklist for selecting a migration partner:

  • Holds AWS Migration Competency or is enrolled in MAP as a partner
  • Has delivered migrations in your industry or with similar workload types
  • Quotes a discovery phase before committing to a fixed scope
  • Can show reference customers willing to take a call
  • Defines clear handoff criteria and post-migration support terms

Common engagement models to ask about:

  • Fixed-scope assessment: a bounded discovery and planning engagement, typically two to four weeks, that produces a migration roadmap, wave plan, and cost model
  • Wave-based execution: structured delivery where lower-risk applications migrate first, with each wave informing the next
  • Fully managed migration: the partner owns execution end to end, including cutover coordination, with your team in an oversight role

When your internal team is enough. If your environment is under 50 servers, your applications are largely stateless, and you have at least one engineer with hands-on AWS experience, native tools plus AWS Support at Business tier will get you there. The native tooling is genuinely capable. MGN handles server replication without drama. DMS manages most database moves without requiring a specialist.

Outside expertise reduces real risk when your environment includes legacy databases with heavy stored procedure logic, SAP workloads, mainframe dependencies, or compliance requirements that demand documented architectural review. Getting the landing zone wrong also has lasting consequences, and that is the area where experienced partners earn their fees fastest. If you're weighing internal capability gaps, these common AWS cloud migration challenges are often a good reality check before committing to a delivery model.

Conclusion

Getting a migration right comes down to a sequence of decisions, not a single tool or vendor choice. Define your scope clearly, apply the 7 Rs to every workload, match each application to the right AWS migration services, and validate your landing zone and security controls before you move a single server. Then build a cost model grounded in actual discovery data, not vendor estimates.

Before you kick off your first migration wave, run through these three steps:

  • Inventory your workloads using Application Discovery Service or equivalent tooling to capture dependencies and performance baselines
  • Classify each application by the 7 Rs so your team makes deliberate strategy choices instead of defaulting to lift-and-shift for everything
  • Run a pilot wave with defined rollback criteria so you prove your cutover process on lower-risk workloads before touching anything business-critical

If you want a structured starting point, Brilworks offers a migration readiness assessment and roadmap workshop designed specifically for engineering teams navigating complex portfolios. No sales pitch, just a clear picture of where you stand and what needs to happen next.

FAQ

AWS Cloud Migration Services are a comprehensive suite of tools, programs, and professional services offered by Amazon Web Services to help organizations move applications, data, and infrastructure from on-premises environments or other clouds to AWS. AWS Cloud Migration Services include native tools like AWS Migration Hub, Database Migration Service, and Server Migration Service, plus partner and consulting services.

AWS Cloud Migration Services include AWS Migration Hub for tracking migrations, AWS Application Migration Service for lift-and-shift, AWS Database Migration Service (DMS) for database transfers, AWS DataSync for data migration, AWS Snow Family for offline data transfer, and AWS Schema Conversion Tool. These AWS Cloud Migration Services tools cover virtually every migration scenario from simple to complex.

The cost of AWS Cloud Migration Services varies by approach: many AWS native migration tools are free or low-cost (you pay only for AWS resources used), while professional AWS Cloud Migration Services from partners range from $50,000-$500,000+ depending on migration complexity. Total costs include assessment, migration execution, AWS infrastructure, and post-migration optimization.

WS Cloud Migration Services support the 7 R's migration strategies: Rehost (lift-and-shift), Replatform (lift-tinker-and-shift), Refactor/Re-architect, Repurchase (move to SaaS), Relocate (VMware), Retain (keep on-premises), and Retire (decommission). Professional AWS Cloud Migration Services help determine the optimal strategy for each workload.

Migration timelines using AWS Cloud Migration Services vary widely: small applications may migrate in weeks, medium workloads take 2-4 months, and enterprise-wide transformations require 6-18+ months. The duration of AWS Cloud Migration Services depends on application complexity, data volume, dependencies, testing requirements, and chosen migration strategy.

Vikas Singh

Vikas Singh

Vikas, the visionary CTO at Brilworks, is passionate about sharing tech insights, trends, and innovations. He helps businesses—big and small—improve with smart, data-driven ideas.

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