Cloud, API & Platform Engineering · Cloud migration
Moving to the cloud without betting the business
We move applications, servers and databases from on-premises hardware, colocation or aging hosting into AWS, Azure or Google Cloud — with an inventory first, a rehearsed cutover and a rollback plan if anything misbehaves.
- Dependency mapping
- Workload-by-workload strategy
- Data migration and sync
Overview
What decides whether a migration goes smoothly
A cloud migration succeeds or fails in the assessment. Before anything moves, you need to know what each server actually does, what talks to it, how much data it holds, how long it can be offline and who signs off when it is back. That inventory almost always turns up systems nobody listed: a file share accounting relies on, a scheduled export, a license server. Finding them in planning costs hours; finding them on cutover night costs much more.
The core decision is the path for each workload. Rehosting moves servers largely as they are and is fastest, but carries old inefficiencies along. Replatforming swaps pieces such as the database for managed services with modest change. Refactoring rebuilds for the cloud and costs most up front. Some systems are better replaced with SaaS or simply retired. Most estates use a mix, and we help you choose per system rather than by slogan.
A good migration feels uneventful to your customers: short, announced windows, validated data, no lost records and an old environment switched off only when everyone agrees. Internally, the success test is just as plain: every system is accounted for, nothing important was left behind on old hardware, and the new environment is documented, monitored and owned.
Who it’s for
Built for teams like yours
- 01
Businesses leaving their server room
Companies with on-site servers nearing end of life, renewals or a lease change, wanting to move into the cloud instead of buying another round of hardware.
- 02
Teams on aging hosting
Organizations running on colocation, legacy VPS or a hosting provider being retired, needing applications and databases moved with minimal disruption to customers. Deadlines are often fixed, so planning starts early.
- 03
Companies switching clouds
Businesses moving between AWS, Azure and Google Cloud for pricing, skills or platform reasons, and wanting a structured plan instead of a rushed copy. Service equivalents are mapped one by one.
Why it matters
Most migration risk is in what nobody wrote down
The hard part of a migration is rarely the copy itself. It’s the cron job on an old server, the hard-coded IP address, the license tied to specific hardware and the report that runs once a quarter. We inventory and map dependencies before moving anything, so those surprises surface in planning instead of on cutover night.
Then we choose a path for each workload — rehost, replatform or refactor — and migrate in waves, starting with lower-risk systems so the approach is proven before your critical ones move.
Every engagement includes
- Migration assessmentinventory, dependency map and readiness review of every system in scope.
- Migration planwaves, sequencing, downtime windows and owners agreed with your team in writing.
- Landing zonesecure target accounts, networking and identity built in code before anything moves.
- Migration executionservers, applications and data moved wave by wave with validation at each step.
- Cutover supportengineers on hand during each go-live window, including after-hours windows when needed.
- Decommission & handoverold infrastructure retired safely and the new environment documented end to end.
Features
How a careful migration runs
- 01
Dependency mapping
An inventory of servers, applications, data flows and scheduled jobs, including the undocumented connections that cause outages.
- 02
Workload-by-workload strategy
Each system assigned to rehost, replatform, refactor, replace or retire, with the reasoning written down.
- 03
Data migration and sync
Database replication or staged transfers that keep source and target in sync until the moment of cutover.
- 04
Rehearsed cutovers
Dry runs in a staging environment, timed checklists and agreed go or no-go criteria before production moves.
- 05
Rollback ready
A tested path back to the original environment if validation fails during or after the cutover window.
- 06
Post-move optimization
Right-sizing, managed services and cost tuning once real cloud usage data replaces the original estimates.
In practice
Migrations we plan and run
Moving line-of-business servers
Windows and Linux servers running accounting, ERP or custom applications moved into cloud virtual machines with backups, monitoring and access controls rebuilt properly along the way. Licensing is checked before moving so nothing stops working after the switch.
Database moves with low downtime
Large databases replicated continuously to a managed cloud service, so the final switch takes minutes of read-only time rather than an overnight copy. Data is validated before and after the switch so nothing is lost.
File shares and storage
Departmental file servers moved to cloud storage or managed file services, with permissions mapped, sync tested and users given clear instructions for the change. Old shares stay read-only for a period in case anything was missed.
Data center exit
A full estate moved in planned waves against a fixed deadline, with each wave rehearsed, validated and signed off before the next begins. Progress is tracked against the exit date so slippage shows up early.
Process
How we work
- 1
Discovery
We collect server, application and network data with discovery tools and interviews, then build a dependency map showing what talks to what, how often and why. Undocumented connections are confirmed with system owners.
- 2
Path per workload
Each system is assigned rehost, replatform, refactor, replace or retire, with effort, risk and downtime estimates, and grouped into migration waves your team approves. Waves are sequenced so dependent systems move together.
- 3
Pilot wave
A low-risk system moves first to prove the landing zone, tooling, runbooks and validation checks, and lessons are folded into the plan before critical workloads. Timings from the pilot make later estimates more reliable.
- 4
Wave cutovers
Each wave follows a timed runbook with data sync, freeze, switch, smoke tests and business sign-off, and a go or no-go call at each checkpoint. If checks fail, the runbook’s rollback steps are followed without debate.
- 5
Stabilize and retire
After cutover we watch performance and costs, tune sizing, confirm backups restore, then decommission old hardware and wipe data under an agreed process. Licenses and contracts tied to the old environment are flagged for cancellation.
Deliverables
What you receive
- Discovery data and server inventory
- Dependency map across applications and networks
- Per-workload migration path with reasoning
- Wave plan with downtime windows and owners
- Timed cutover runbooks for every wave
- Data validation and sign-off records
- Decommissioning checklist and data-wipe confirmation
Tools & methods
Migration tooling
- AWS Application Migration Service
- AWS DMS
- Azure Migrate
- Google Migrate to VMs
- rsync
- Robocopy
Target platforms
- AWS
- Microsoft Azure
- Google Cloud
- Terraform
- Amazon RDS
- Azure SQL
Methods
- Dependency mapping
- Wave planning
- Cutover rehearsals
- Checksum validation
- The 6 Rs
FAQ
Frequently asked questions
Anything else about Cloud migration? Ask us directly.
Some downtime is usually unavoidable for the final switch, but it can often be kept short. Database replication, lowered DNS time-to-live values and rehearsed runbooks shrink the cutover window, and we schedule it for your quietest hours. You’ll know the expected window for each system before it moves.
Let’s work together
Have a project in mind?
Book a strategy call and we’ll show you exactly how to turn your goals into a system that generates consistent results.