Move a system you cannot afford to break.
We migrate the codebase, not just the infrastructure. That is what lets a ten-year-old production system reach the cloud without the outage, the surprise bill, or the six months of regression nobody planned for.
The system that runs fine today is the one that fails on the way to the cloud.
A cloud migration is not risky because the cloud is hard. It is risky because the system being moved is older than the people moving it, and most of what it really does was never written down. Three patterns cause the majority of failed moves.
The system gets moved before it is understood.
Hidden dependencies, an undocumented integration, a scheduled job no one remembered. None of it shows up in an infrastructure diagram. It shows up as an outage the week after cutover, when the system is already live on the cloud and there is no going back to check.
A big-bang cutover with no rollback.
Everything moves in one weekend, the old environment is decommissioned, and the first bad hour is unrecoverable. When something behaves differently on the new platform, there is nothing to fall back to and the incident runs until it is fixed in production.
Lift-and-shift onto a VM, and you get the bill without the benefit.
The most common failed move is the one that looks like a win: copy the servers onto cloud VMs and call it done. Now you pay cloud prices for a data-center design and get none of what you moved for, no elasticity, no managed services, no reliability gain. Over-provisioned boxes that were free to ignore on-premise become a monthly line item that climbs until finance asks what changed.
We understand the codebase, then map it onto the cloud
The outcome you want: the system behaves the same on the other side, and it actually uses the cloud instead of just sitting on it. Both depend on the same first step that most migrations skip, understanding the system before touching it.
This is the difference between migrating a codebase and lifting-and-shifting infrastructure. Moving servers is the easy part. The work is reading the application, what talks to what, where the data lives, and which pieces are self-managed today, then deciding what each piece should become on the cloud rather than assuming it moves across unchanged.
It runs on our four-phase engineering method, Understand, Plan, Implement, Verify, the same discipline behind AI-assisted development. The output is a target-state design and a cutover plan you can read, typically inside the first few weeks and before you commit to the move.
This is also where migration and modernization part ways. If a component needs to be reshaped rather than moved, we say so and treat it as modernization. Everything that can move stays in production the whole time.
- Dependency and integration mapping. Every external service, database, queue, and scheduled job documented, so nothing is stranded on the old platform after the move.
- Target-platform mapping. Which self-managed pieces become managed services on Azure, AWS, or Google Cloud, what gets right-sized, and what moves as-is for now.
- Data footprint and migration plan. What data moves, in what order, how it replicates during the move, and how it is checked for integrity once it lands, planned before the first byte is copied.
- Network and security cutover plan. Connectivity to what stays behind, identity and secrets, encryption, and the DNS and traffic switch, designed up front rather than improvised at cutover.
- Cutover and rollback risk map. What has to move together, where the move is fragile, and where each rollback point belongs.
One system usually needs more than one path
There is no single right way to move a system, and there is no template that decides it for you. The comprehension pass does. Once we understand how each part actually behaves, we pick the path that fits that part, and it is normal for one system to use three or four of these at once.
Rehost
Move the component as-is onto cloud infrastructure. Right when the code is sound and the goal is to exit a data center on a deadline. Fastest path, but a starting point rather than a destination: on its own it does not deliver the cloud's benefits, which is what the next section is about.
Replatform
Keep the application, swap the plumbing underneath: a managed database, a managed queue, a container platform. Right when small changes to how the system runs remove most of the operational load without touching the code that works.
Re-architect
Reshape the component for cloud-native scale or to make it AI-ready. This is application modernization, not just a move, and we say so before you sign up for the extra work.
Rebuild
Some parts are cheaper to rebuild than to carry across. Right when the code is a dead end but the capability still matters. If most of the system is like this, start with Legacy Application Modernization instead.
Retire
The comprehension pass often finds features nobody uses and services nothing calls. Moving them is money spent on dead weight. We flag them so you can switch them off instead of paying to host them.
Retain
Not everything should move yet. A component with a hard compliance or latency tie to where it lives may stay put for now, connected cleanly to the parts that do move, and revisited on its own timeline.
Getting the cloud benefit, not just a cloud bill
Moving onto the cloud is not the same as using it. The move only pays off if the system comes out cheaper to run, able to scale with demand, and more reliable. So realizing that value is part of the migration, not a project you are sold afterward.
Right-size as it lands
On-premise, an over-provisioned server was a sunk cost you ignored. On the cloud it is a meter running every hour. We match compute and storage to real usage as each component moves, so the bill reflects what you actually run.
Adopt managed services
Where it fits, a database you patch becomes a managed database, a queue you run becomes a managed queue, a mounted disk becomes object storage. The cloud runs the plumbing so your team stops spending nights on it.
Make scaling elastic
The workloads that spike, month-end jobs, campaign traffic, batch runs, get autoscaling so capacity follows demand. You pay for the peak only when there is a peak, instead of sizing every day for the worst hour of the year.
Decommission the old estate
Once cutover holds, the source environment is shut down on a plan, not left running "just in case." Paying for two copies of the same system is the quiet way a migration never shows a saving.
One honest line: everything above happens during the move itself. Where a component needs a deeper cloud-native redesign instead, breaking a monolith into event-driven or containerized services, that is modernization, not a move, and it is what the next section is about. Keeping the bill and reliability tuned in the years after go-live is ongoing Cloud Services.
The assessment tells you which, before you pay to move anything
Sometimes the honest answer to "move my system to the cloud" is "this is really a modernization." The same comprehension pass decides which of these three you are actually looking at, so you never pay to move something you should have rebuilt, or rebuild something that only needed to move.
The code is sound
Move it as-is
The application does its job and the code is healthy. It just needs to run somewhere better. This is a migration in the plain sense: rehost or replatform, verified against real behavior, moved without downtime.
You are on the right page.The move is the moment
Modernize as you move
The system works, but the move is the right time to re-architect part of it for cloud-native scale or to make it AI-ready. That is modernization done during the migration, not a separate project later.
AI-Driven Application Modernization →The stack is a dead end
Modernize first, then move
The stack is out of support or cannot be hired for. A lift-and-shift would just relocate the problem and its bill. The honest move is to modernize onto a supportable footing first, then migrate cleanly.
Legacy Application Modernization →A move you can watch, and stop, at every step
If any step misbehaves, you are back on the old system in minutes, not filing a restore ticket and waiting. The whole method is built so there is always a way back until the moment you decide there is no need for one. The hardest part is almost never the servers, it is the data, so that is where most of the plan goes.
Assess and plan
Comprehension first, then a migration plan: the path per component, the data-migration order, and the cutover risk map. You approve it before anything moves.
Build the target
The environment is stood up as infrastructure-as-code: networking, identity and secrets, encryption, and the managed services each component will use, reproducible and reviewable, not clicked together by hand.
Migrate incrementally
Component by component, never the whole system in one weekend. Each piece moves, gets checked, and settles before the next one follows.
Run in parallel and verify
The migrated system runs beside the live one, with data kept in sync and reconciled between the two, and is verified against real behavior before any traffic switches.
Cut over with rollback
Traffic is switched over, by DNS or load balancer, when the evidence says it is safe, with a rollback path held open until the new system has proven itself in production.
Engagements are scoped to defined milestones, not open-ended time and materials. Once the system is live, ongoing run, scaling, and cost control move to Cloud Services, and ongoing ownership of the code moves to Application Maintenance. The move is the start of the relationship, not the end of it.
Moving a manufacturer's service and reporting system off aging Windows infrastructure, across every office
A European industrial manufacturer stuck on a legacy Windows-based service and reporting system that could not scale or reach its international offices
The situation: A manufacturer of industrial mechanical components ran its parts-servicing and reporting on an aging Windows-based system. It was hard to maintain, could not scale, would not integrate cleanly with the company's SAP ERP, and could not be deployed across offices in other countries. The system worked, but it was trapping the business on infrastructure it had outgrown.
What AnAr did: We mapped the system, then moved it to a cloud-native platform, re-architecting the parts that needed it as we went. This was migration and modernization in one engagement: the SAP ERP integration was built in, the interface was rebuilt for a multilingual global workforce, and the whole system was deployed across international offices from a single cloud footing.
Why teams trust us to move a system that cannot go down
We are a Microsoft Partner (Azure AI) and run production migrations to Microsoft Azure, AWS, and Google Cloud. The target platform is chosen to fit your system, not our preference.
We map the codebase before it moves.
Comprehension-first is not a slogan. We recover the business rules, dependencies, and edge cases from the code itself before a single component moves, so the migration plan is built on what the system really does. Most vendors move the servers and find out the rest in production.
Incremental and reversible, never big-bang.
Components move one at a time, run in parallel with the live system, and get verified against real behavior before traffic switches. A rollback path stays open at every step, so a bad hour is a step back, not an outage.
150+ projects. 95% client retention. 12 years of delivery.
Clients stay with us for years, which is the point: we are still there after cutover, running and maintaining what we moved. The track record is real and verifiable, not a logo wall.
We migrate codebases, not just infrastructure.
Our engineers read applications for a living, with AI-assisted comprehension as standard practice on every engagement. That is what lets us move a ten-year-old system safely instead of only moving the parts a diagram can see.
What leaders ask before a migration
If your question is not covered below, a migration assessment is the fastest way to a specific answer for your system.
Can you migrate a system your team did not build?
Yes. It is the common case, not the exception. We do not start by moving servers. We start by mapping the system: dependencies, integration points, the data, and the business rules buried in the code.
Only once we understand what the system really does do we plan the move. That order is what makes a migration safe rather than a bet that nothing important was undocumented.
How do you migrate without downtime?
We move incrementally, not in one big-bang weekend. Components move one at a time, the migrated system runs in parallel with the live one, and each piece is verified against real behavior before any traffic switches to it.
Cutover happens when the evidence says it is safe, and even then a rollback path stays open until the new system has proven itself in production.
How long does a cloud migration take?
Honestly, it depends on the system, and any firm that quotes a number before seeing your code is guessing. What is consistent is the shape: a few weeks to map the system and produce the migration plan, then a phased move where components go one at a time rather than all at once.
The assessment is what turns "it depends" into a real timeline. Once we understand the dependencies and the data, we can tell you which parts move quickly, which need care, and roughly how long the whole move runs, before you commit to it.
What happens if something breaks after cutover?
You go back. A rollback path is part of the plan at every step, so a problem after cutover is a step back to a known-good state measured in minutes, not an incident that runs until it is fixed live.
Because we verified behavior against the old system before switching, most differences are caught in the parallel-run stage, before your users ever see them.
How do you keep the cloud bill from ballooning after the move?
A lift-and-shift copies old inefficiencies straight onto metered infrastructure, so we do not do that blindly. As each component moves, we right-size it, retire what nothing uses, and model the spend so the bill is understood before it arrives.
Ongoing spend control, once the system is live, is part of Cloud Services, where cost optimization is a standing discipline rather than a one-time cleanup.
Is our data safe during the move, and does our compliance posture survive it?
Yes, and it is planned for from the start rather than patched afterward. Data is encrypted in transit and at rest throughout the move, stays in the region you require, and the migrated system is checked for data integrity before any traffic switches to it. Nothing is copied to a place it should not be.
Where you carry an obligation like SOC 2, HIPAA, or GDPR, the controls that satisfy it are mapped during the assessment and carried onto the target platform, so cutover does not quietly break your compliance posture. Only the engineers assigned to your engagement can see your code and data.
Is this a migration or an application modernization, and how do you decide?
The comprehension pass decides, and it is the same pass either way. Sometimes the code is sound and only needs to move. Sometimes the move is the right moment to re-architect part of it, and sometimes the stack is a dead end that should be modernized before any move at all.
We tell you which of the three you are actually looking at, so you never pay to move something you should have rebuilt. See AI-Driven Application Modernization for modernizing as you move, or Legacy Application Modernization for modernizing first.
What happens once the system is live on the cloud?
The move is the start of the relationship, not the end. Ongoing run, scaling, reliability, and cost control move to Cloud Services. Ongoing ownership of the application, feature work, patching, and support, moves to Application Maintenance.
Because the same team migrated the system, that handover carries the understanding with it rather than starting from a blank page.
When is migration not the right answer?
When the stack itself is out of vendor support, cannot be hired for, or has decayed past the point where moving it is worth the effort. Migrating it then just relocates the problem and its bill onto the cloud. We will tell you that directly rather than move a dead end.
In that case the honest sequence is to modernize first, then move. Start with Legacy Application Modernization or AI-Driven Application Modernization, and the migration follows cleanly once the system is on a supportable footing.
Is our source code and IP protected?
Yes. Your source code is your IP. Confidentiality terms are agreed in writing before any code is shared, and visibility is limited to the engineers assigned to your engagement.
Tell us what needs to move
A short note is enough to start. We begin every migration with an assessment of the system, so you get a real read on what the move involves, and whether it is a move at all, before any commitment.
Come to us with:
- An aging system that has to move off a data center or old infrastructure
- A cloud bill that climbed after a lift-and-shift and needs undoing
- A migration that stalled because no one fully understands the system
- A move you suspect is really a modernization, and want an honest read
You will speak with engineering, not sales. The first reply comes from someone who can answer technical questions about your system, within one business day.
Send a Message
A few details so the right engineer follows up.
Routed to the right engineer
We read what you sent and route it to someone who works in that area, not to a sales queue.
A reply within one business day
You get a substantive response from an engineer, with first thoughts on the move where they are clear.
An assessment to go deeper
We set up time to look at the system, map what the move involves, and agree how best to work together.
Once it is live, run and scale it with Cloud Services →
If the move is really a rebuild, see AI-Driven Application Modernization → or Legacy Application Modernization →