AWS Migration
Lift-and-shift, re-platforming, and database migrations — with a clear sequence and rollback plan at every step. We've run migrations on everything from single VMs to multi-terabyte data warehouses.
The state of most cloud migrations
- The dependency map exists in someone's head — and that someone is on PTO during the cutover
- "Rollback plan" means redeploying the old version — which itself was never tested under load
- Database migrations are the part nobody wants to own — and the part that decides if cutover works
- Validation is "let's see if it works in prod" — there's no automated comparison against baseline
- Performance and cost end up worse on AWS than on-prem — because nobody right-sized after cutover
- The deadline is real (data-center exit, M&A integration, vendor contract end) and slipping costs money
What "safe migration" actually means
A safe migration has three properties: every workload's dependencies are documented, every cutover has a tested rollback, and every result is validated against a baseline. Most migrations skip all three.
We do all three. The boring part of migration is what separates the ones that finish from the ones that linger.
Wherever you're coming from
Azure to AWS migration
Workload-by-workload mapping from Azure services to their AWS equivalents — AKS to EKS, Azure SQL to RDS or Aurora, Entra ID integration — with a landing zone built before the first workload moves. Replatform where it pays; rehost where it doesn't.
GCP to AWS migration
GKE to EKS, BigQuery to Redshift or Athena, Cloud Functions to Lambda. We map the service model differences honestly — including the places GCP concepts don't translate one-to-one — before committing to a cutover plan.
Virtual machine migration
VMware and bare-metal estates rehosted with AWS Application Migration Service (MGN): block-level replication, launch testing against a live copy, and cutovers measured in minutes. Rehost first, modernize on AWS afterward.
Database migration
Oracle, SQL Server, MySQL, and PostgreSQL to RDS, Aurora, or DynamoDB using DMS with continuous replication and Schema Conversion Tool where engines change. Near-zero-downtime cutovers with a tested fallback.
On-premises and colo exits
Full-estate moves driven by a lease or contract deadline. Dependency-mapped wave plans, network cutover sequencing, and the discipline to hit a date that isn't movable.
Windows & SQL Server on AWS
Windows Server and SQL Server estates moved with licensing worked out up front — BYOL versus license-included — and a path to trim the license bill later via modernization to Linux or managed services where it makes sense.
Migration confidence, not migration surprises
- Migration strategy — re-host, re-platform, or re-architect
- Dependency mapping across all workloads
- Rollback plan documented and tested before go-live
- Database migration — RDS, Aurora, DynamoDB, or hybrid
- Cutover orchestration and validation scripts
- Post-migration WAF review within 30 days
Migration Strategies
VMs and apps as-is, fastest path to AWS
Minor refactoring for managed services (RDS, ElastiCache)
Full modernization for cloud-native patterns
Keep some workloads on-prem, migrate others
Aligned to AWS Prescriptive Guidance — Assess, Mobilize, Migrate & Modernize
AWS publishes a three-phase migration model in their Prescriptive Guidance — the same model used by Migration Acceleration Program (MAP) engagements. We work to that model, with a fourth ongoing step for post-cutover validation and right-sizing.
Readiness, business case, and estate inventory
Full estate discovery — applications, dependencies, data volumes, traffic patterns, compliance scope. TCO modeling against AWS, migration strategy per workload (re-host, re-platform, re-architect, retain, retire), and a defensible business case before any migration plan is built.
Landing zone, patterns, and pilot
Build the AWS landing zone (Organizations, Control Tower, networking, security baseline). Define migration patterns per workload group. Train your team on the tooling. Run a pilot migration of a non-critical workload to validate runbooks before touching production.
Wave-based execution with rollback at every step
Workloads migrated in waves, ordered by dependency and risk. Re-platform or re-architect where the WAF review justifies it. Each wave has a documented rollback procedure tested before go-live. Database migrations (RDS, Aurora, DynamoDB) handled with replication and cutover scripts you keep.
Confirm against baseline and right-size
Post-cutover, we run automated validation suites against your pre-migration baseline. Performance, cost, and reliability are confirmed before declaring done. A WAF review within 30 days catches anything the migration introduced. Then handoff — you operate, we step back.
What you walk away with
- Every workload migrated with a documented, tested rollback path — no cutover surprises
- A full dependency map — every workload, every database, every external integration accounted for
- Performance and cost validated against your pre-migration baseline — no "we'll measure that later"
- Cutover runbooks and validation scripts your team owns — reusable for future workloads
- A post-migration Well-Architected review within 30 days — confirming the new environment holds up across all six pillars
- A right-sized AWS bill — we don't declare migration done until cost is matched to actual usage
Migration is not a weekend project
We'll scope your migration, identify the riskiest pieces, and give you a realistic timeline. No sugar-coating, no surprises.
Start a Migration AssessmentFrequently asked questions
How long does an AWS migration take?
It depends on estate size and entanglement, which is why we start with the Assess phase: one to two weeks that produce a wave plan with real dates. A single workload or database can move in weeks; a first wave typically lands within one to three months; full estate exits are wave-planned across quarters — with dates set honestly in the Assess phase, not discovered later.
Will we have downtime during the migration?
Cutovers are designed around replication — AWS Application Migration Service for servers, DMS for databases — so the switch itself is typically minutes inside a planned window, not hours. Every cutover has a documented, tested rollback before go-live.
Do you migrate from Azure or GCP, or only from on-premises?
Both. Cloud-to-cloud moves (Azure to AWS, GCP to AWS) follow the same assess-mobilize-migrate structure as data-center exits — the difference is in service mapping, identity integration, and how much replatforming pays for itself on day one.
Which migration strategy is right for us — rehost, replatform, or refactor?
Per workload, not per company. The assessment scores each workload against the 7 Rs (rehost, replatform, refactor, repurchase, relocate, retain, retire). Most estates land on rehost-first for speed with targeted replatforming where a managed service removes real operational load.
Do we have to modernize while we migrate?
No — and usually you should not. Coupling a rewrite to a migration deadline is how migrations stall. We rehost or lightly replatform to hit the date, then modernize on AWS afterward with the pressure off.
What does a migration cost?
The Assess phase produces a fixed-scope, fixed-price proposal per wave — you see costs, timeline, architecture, and risks before committing to execution. No open-ended time-and-materials, no change orders.
Related: Well-Architected Review · AWS Modernization · Cost Optimization