Cloud & Operations
Cloud Migration Services
Moving to the cloud does not make a system better or cheaper on its own. The value is in the target architecture you migrate towards, not in the act of moving VMs. We design that first, then move.
What Cloud Migration means in practice
Who it’s for: Organisations leaving an ageing data centre, hitting the ceiling of on-premises hardware, or consolidating a sprawl of clouds, who want the move to reduce cost and risk rather than quietly increase both.
A cloud migration is one of the few pieces of engineering where the naive version and the good version look almost identical on day one and diverge sharply over the following year. Lift a fleet of virtual machines out of a data centre, run them unchanged on rented equivalents, and the demo works: everything is “in the cloud”. The bill arrives a month later. Because a machine that sat in a rack you already owned is now metered by the hour: provisioned for peak, running at idle most of the time, paying retail for storage and egress that used to be free. A straight lift-and-shift very commonly costs more than the estate it replaced, not less. The cloud is not automatically cheaper. It is a different cost model, and moving into it without changing how the workload is shaped means you have carried your on-premises inefficiencies across and started paying rent on them.
So we treat migration as an architecture problem before it is a moving problem. The first work is understanding the estate you actually have: the servers everyone knows about and the three nobody documented, the dependencies that only reveal themselves when something breaks, the data volumes, the traffic patterns, the compliance obligations, and the true current cost including the people who keep it alive. From that we decide, workload by workload, what should happen to each one: some get rehosted as they are because they are low-value and near end-of-life, some get replatformed to a managed service, some get refactored to actually use the cloud, some get replaced by a product, some get switched off because nobody could name who uses them, and some stay exactly where they are because moving them would be expensive and pointless. That per-workload decision (the “six Rs”), is the substance of the work.
We migrate to and between AWS, Azure and Google Cloud, chosen on where the workload fits rather than on a preferred badge, and the target is always a deliberate architecture rather than a mirror of the old one. That means cost governance from the first day, because a migration with no one watching spend is a migration that discovers its budget through an invoice. It means a phased cutover that keeps the business running rather than a big-bang weekend that bets the operation on everything working at once. And it means being honest when the answer is that a given workload should not move, or should stay hybrid. A straight recommendation you are far more likely to get from engineers who operate cloud systems than from anyone paid on how much you migrate.
What you get
- A full assessment of the existing estate, inventory, dependencies, data volumes, traffic patterns, compliance obligations and the true current cost, so decisions are made on what is really there, not on a diagram that is two years stale
- A per-workload migration strategy across the six Rs (rehost, replatform, refactor, repurchase, retire, retain), with the reasoning and the cost implication written down for each, including the ones we recommend not moving
- A target-state architecture designed to use the cloud deliberately (the managed services, networking, identity and scaling model), rather than a like-for-like copy of the data centre that just happens to run somewhere else
- A phased migration and cutover plan that minimises downtime and keeps a working rollback at every step, so no single failure takes the business offline
- A data migration approach that moves data safely and verifiably, with validation that source and target actually match before anyone relies on the target
- Cost governance from day one (tagging, budgets, alerts and a right-sizing pass), so spend is visible and controlled during and after the move rather than discovered on an invoice
- Infrastructure and target environments captured as code, so what you migrate onto is reproducible, reviewable and recoverable rather than clicked together once by whoever ran the project
What Cloud Migration does for you
Cost that goes down instead of quietly up
The default outcome of a thoughtless migration is a higher bill, because a lifted machine is provisioned for peak and metered at idle, and storage and egress that were free on-premises are now line items. We design the target to fit the workload, right-sized instances, managed services that scale to zero when idle, storage tiered by how it is actually accessed, and we put tagging, budgets and alerts in place before the first workload moves, so the economics are engineered and watched rather than discovered after the fact.
Scale you can reach without a purchase order
The concrete thing the cloud gives you that a data centre cannot is capacity on demand. The ability to absorb a launch, a seasonal peak or a growth curve without procuring, racking and provisioning hardware weeks ahead. We migrate towards architectures that can actually use that elasticity, so the workload grows and shrinks with demand instead of being permanently sized for the worst day of the year, which is where much of the real saving and the real agility come from.
Resilience and recovery you can rely on
A well-designed cloud target makes redundancy and disaster recovery achievable in ways that are expensive or impossible with single-site on-premises hardware, multiple availability zones, managed database failover, backups and recovery that are tested rather than assumed. We build that in as part of the target architecture, so the migration is also the moment your recovery story stops being a document nobody has ever exercised and becomes something that has actually been proven to work.
Why teams choose us for Cloud Migration
- You want engineers who will tell you plainly when a workload should not move, or should stay hybrid, rather than a partner whose incentive is to migrate as much as possible, because operating cloud systems for a living makes us allergic to the ones that only look good until the bill lands.
- You have been burned, or fear being burned, by a lift-and-shift that increased cost, and you want the value to come from a deliberate target architecture and real cost governance, not from the act of moving VMs from one place to another.
- You need the move done without stopping the business. A phased cutover with verified data and a working rollback at every step, rather than a big-bang weekend that bets the whole operation on everything succeeding at once.
- You want the choice between AWS, Azure and Google Cloud made on where your workloads actually fit and what they will genuinely cost to run, with the trade-offs shown honestly, instead of a default badge chosen before anyone looked at your estate.
What Cloud Migration includes
The concrete pieces of work this covers, scoped to what your problem actually needs.
Estate assessment and dependency mapping
We inventory what you actually run (the documented systems and the ones that surface only when something breaks), and map the dependencies between them, because the workload nobody remembered is exactly the one that takes an unplanned service down mid-migration. Alongside the technical picture we establish the real current cost, including hardware, licensing, hosting and the operational effort of keeping it alive, so every later decision has an honest baseline to be measured against rather than a hopeful guess.
Migration strategy: the six Rs, per workload
Each workload gets a deliberate decision, not a blanket policy. Rehost (lift-and-shift) where speed matters and the workload is near end-of-life and not worth reworking; replatform where a managed database or runtime removes real operational burden for modest effort; refactor where the workload is worth changing so it genuinely uses the cloud; repurchase where a SaaS product does the job better than anything you would maintain; retire the things nobody could name an owner for; and retain (deliberately not moving), what would cost more to migrate than it is worth, or what belongs on-premises for latency, compliance or economics. We write the reasoning and the cost implication down for each.
Target-state architecture design
The point of the migration lives here. We design what the estate should look like once it is in the cloud: the networking and segmentation, the identity and access model, which workloads become managed services, how compute scales with demand, how data is stored and tiered, so the result uses the platform deliberately rather than reproducing the data centre with a monthly invoice attached. This is the difference between a migration that pays for itself and one that merely changes where the servers live.
Data migration and validation
Moving data safely is the part with the least room for error, because a corrupted or incomplete dataset discovered after cutover is a very bad day. We plan the move around the data’s size, its rate of change and how much downtime the business can tolerate, bulk transfer with a final sync, change-data-capture for near-zero-downtime cutover, or a staged migration where both run in parallel, and we validate that the target genuinely matches the source, by counts, checksums and spot reconciliation, before anything is allowed to rely on it.
Cost governance and FinOps
Cloud spend is easy to start and hard to see, so we build the controls before the workloads arrive: consistent tagging so cost can be attributed to teams and systems, budgets and alerts so a runaway is caught in hours rather than at month end, and a right-sizing discipline that matches provisioned capacity to real usage instead of the peak-shaped guesses carried over from on-premises. Commitment-based discounts are applied only once usage is understood, never speculatively. The aim is an environment whose economics are visible and governed continuously, not audited in a panic after a surprising invoice.
Provider selection across AWS, Azure and Google Cloud
We work across all three and choose on fit rather than familiarity: the services a workload actually needs, the identity and licensing you already own, the data-residency options in the regions you must operate in, and the genuine run cost of the equivalent architecture on each. Where a multi-cloud or hybrid answer is right, because different workloads suit different platforms, or because some systems should stay on-premises. We design for that deliberately rather than pretending a single badge is always the answer.
Where it fits
Exiting an ageing data centre
A lease is ending or the hardware is due for a refresh nobody wants to fund, and the estate has to leave the building. The trap is treating this as a deadline-driven lift-and-shift and arriving in the cloud with every inefficiency intact and a higher bill. We use the forced move as the moment to decide each workload’s fate deliberately, what gets rehosted to hit the date, what gets replatformed or refactored because it is worth it, what gets retired, and what needs a hybrid answer, so you leave the data centre with an architecture that fits the cloud rather than a copy of the room you just vacated.
Breaking through an on-premises scaling ceiling
The business has outgrown its hardware: launches, seasonal peaks or steady growth now require procuring and racking equipment weeks in advance, and capacity is either short when it is needed or idle and expensive when it is not. We migrate the workloads that actually benefit from elasticity towards architectures that scale with demand, so you can absorb the peak without owning hardware for it year-round, while being clear about the workloads whose load is flat and predictable, where the cloud’s elasticity buys nothing and the decision rests on other grounds.
Consolidating a sprawl of clouds
Acquisitions, shadow projects and years of drift have left you spread across several clouds and accounts, with duplicated services, inconsistent security postures and a bill split across places nobody fully reconciles. We map what runs where and what it costs, then consolidate deliberately, standardising identity, networking and security, removing duplication, and moving workloads to where they genuinely fit, so the estate becomes something one team can govern, secure and account for, rather than a set of islands each maintained by whoever happened to build it.
Rescuing a lift-and-shift that increased cost
A previous migration moved everything as-is and the cloud bill came out higher than the data centre it replaced, leaving the business wondering what it bought. We work out precisely why: the oversized instances running at idle, the storage on the wrong tier, the egress nobody modelled, the always-on services that could scale to zero, and fix it by replatforming and refactoring the workloads where the saving is real, applying right-sizing and cost governance, and turning off what should never have moved. The goal is to make the cloud version genuinely cheaper to run, which the original move promised and did not deliver.
How we approach Cloud Migration
We start from the estate and the numbers, not from a target platform. Before recommending where anything goes, we build an honest picture of what exists and what it actually costs today, including the operational effort and the hardware refresh you are trying to avoid, because you cannot judge whether a migration saves money without knowing the real baseline it is measured against. Only then do we take each workload in turn and choose its strategy on its merits: how much value it holds, how much life is left in it, how tightly it is coupled to everything else, and what the cloud version would genuinely cost to run. That per-workload discipline is what separates a migration that pays for itself from one that simply relocates the problem and the bill.
From there we sequence the move so the business never stops and there is always a way back. We migrate the low-risk, loosely-coupled workloads first to prove the target architecture, the networking and the cost model on something that cannot hurt much if it stumbles, then work towards the critical systems with that learning banked. Data moves with verification, not hope: we confirm the target matches the source before anything cuts over to it. And because the engineers designing the migration are the ones who will operate the result, cost governance, monitoring and the target-state design are built in from the start rather than bolted on once the invoices start to sting.
How the engagement runs
We open with assessment, because every good decision downstream depends on an honest picture of the estate and its true cost. We inventory the workloads, map the dependencies between them, measure the data volumes and traffic patterns, capture the compliance and residency obligations, and establish what the current setup genuinely costs to run: hardware, licences, hosting and the people keeping it alive. That baseline is what lets us say, workload by workload, whether a migration saves money or simply moves it, and it is the part a rushed project skips and later regrets when the dependency nobody mapped takes a service down.
From the assessment we produce a per-workload strategy across the six Rs and a target-state architecture, with the cost implication written down for each decision, so you approve a plan rather than discover one. Then we migrate in phases: the low-risk, loosely-coupled workloads first to prove the target architecture, the networking, the identity model and the cost governance on something that cannot badly hurt, then the more critical systems with that learning banked. Data moves with validation, each phase keeps a working rollback, and cutover for each workload happens only once the target has been proven to match the source and to behave under real load. Nothing bets the whole business on a single weekend.
How we architect the target
The target architecture is where a migration earns or wastes its money, so we design it as its own deliberate thing rather than as a snapshot of the data centre. We decide the network topology and segmentation, the identity and access model, which workloads become managed services and which stay as compute you run, how each tier scales with demand, and how data is stored and tiered by how it is actually used. The whole target is captured as infrastructure as code, so the environment you migrate onto is reproducible, reviewable and recoverable (not something assembled once by hand and understood by one person), and so the same definitions can stand up the staging environment you validate against before cutover.
We phase the move against that target so the design proves itself incrementally. Loosely-coupled, low-value workloads go first and validate the networking, the security model and the cost assumptions before anything critical depends on them; tightly-coupled systems move together or behind a temporary integration so a half-migrated dependency chain never leaves the business in an inconsistent state. Where the honest answer is hybrid. A workload that should stay on-premises for latency, data gravity or economics, talking to systems that have moved. We design that boundary deliberately, with the connectivity and identity to make it work, rather than forcing everything across for the sake of a tidy diagram.
Security, compliance and data residency
A migration is a period of unusual exposure, because data is in motion and two environments are live at once, so we treat security as part of the plan rather than a review at the end. Data in transit is encrypted over private connectivity or an encrypted channel (never copied across the open internet in the clear), and access to both the source and the target during the move is scoped to least privilege, time-limited and logged, so the migration itself does not become the weak point an attacker walks through. Credentials and keys for the move live in a managed secret store, are rotated, and never sit in a script, a ticket or someone’s laptop.
Compliance and data residency are decided before anything moves, not discovered after. Where data is legally required to stay in a particular jurisdiction, we choose regions and design the architecture so it demonstrably does: during the migration as well as after it, since a temporary staging copy in the wrong region is still a breach of residency. The target is built secure by default: least-privilege identity and access, network segmentation, encryption at rest, audit logging and the configuration a compliance review will ask for, all captured as code so the posture is reviewable and reproducible rather than a set of console settings someone hopes are still correct. The environment you land on should pass an audit because it was built to, not because it was hurriedly hardened before one.
Signs it’s time
- A data centre lease is ending, or a hardware refresh is due, and buying another five years of on-premises equipment is the decision you are trying not to make
- On-premises capacity has become the ceiling. You cannot scale for a launch, a season or growth without procuring and racking hardware weeks in advance
- You have ended up on several clouds through acquisitions, shadow projects or drift, and the duplication, the inconsistent security and the split bill have become a problem worth consolidating
- An earlier lift-and-shift has left you paying more in the cloud than you did in the data centre, and you need someone to work out why and fix the architecture rather than just the invoice
Our working method
The organising belief is that the value of a migration comes from the architecture you migrate towards, not from the act of moving, so the decisions that matter, which of the six Rs applies to each workload, what the target looks like, and what it will genuinely cost to run, come first and are made on real numbers rather than enthusiasm. We measure the current estate honestly before we recommend anything, because you cannot claim a saving without a baseline, and we are willing to conclude that a workload should not move, or should stay hybrid, when that is what the numbers say. Cost governance is treated as engineering, not an afterthought, because an ungoverned cloud environment discovers its budget through an invoice.
We migrate in phases with a working rollback at every step and validate data before anything relies on it, because a big-bang cutover and an unverified dataset are the two failure modes that turn a migration into an incident. And because the engineers who plan the move are the ones who will operate the result, the target is built the way something has to be built when you are the one on call for it: monitored, cost-governed, reproducible as code, and honest about the workloads that were never going to be cheaper in the cloud. We would rather talk you out of moving something that should stay put than bill you for running it in the wrong place for years.
Technologies we build it with
Chosen per problem, not per fashion. This is the stack we most often reach for on this work.
How we deliver
- 01
Discover
We map the system, the constraints and the business it serves, including the parts nobody documented.
Architecture brief
- 02
Architect
Decisions get made, written down and defended before a line of production code exists.
Decision records
- 03
Build
Short cycles against working software. You see progress in the product, not in a status deck.
Shipping increments
- 04
Operate
Monitoring, incident response and iteration. The system is alive, so the engagement is too.
Runbooks & SLOs
Want a straight answer on Cloud Migration?
A short call with a senior engineer, before you write a brief. If Cloud Migration is the wrong answer for your situation, we will say so and tell you what we think is right.
What changes
A move that earns its cost
A target architecture and a per-workload strategy where the cloud version is genuinely better or cheaper to run, not a relocated data centre paying rent on its old inefficiencies.
Cutover without the outage
A phased migration with verified data and a working rollback at every step, so the business keeps running and no single failure takes it offline.
Spend under control from day one
Cost governance, right-sizing and visibility built in from the start, so the new environment is affordable during the move and stays that way after it.
Industries we serve
Domain knowledge changes what gets built. A few of the sectors we know before the first meeting.
How pricing works
- A fixed-scope assessment as a first engagement. The estate inventory, dependency map, per-workload six-Rs strategy, target-state outline and a cost model comparing the current baseline against the projected cloud run cost, priced on the size and complexity of the estate, so you get a defensible plan before committing to the move itself.
- A fixed-scope migration for a well-understood estate, quoted once the assessment has established what moves, how and in what order, so you are pricing a known plan rather than an open-ended “move everything” with no boundary.
- A monthly senior engagement for a large or phased programme, where workloads move over time, the target architecture evolves, and you want continuity and someone genuinely on call for the environment rather than a one-off handover.
- A focused cost-and-architecture rescue for an existing cloud estate. A right-sizing and cost-governance pass, and the replatforming or refactoring of the workloads where a prior lift-and-shift left the bill higher than it should be, priced by the assessment.
Typical timeline
- 01
Assessment and strategy
Two to four weeks building the estate inventory, mapping dependencies, measuring data and traffic, capturing compliance obligations and the true current cost, and producing the per-workload six-Rs strategy, target-state architecture and cost model. The plan you approve before anything moves.
- 02
Foundation and first workloads
Two to four weeks standing up the target as code (networking, identity, security baseline and cost governance), and migrating the low-risk, loosely-coupled workloads first to prove the architecture, the data-migration approach and the cost assumptions on systems that cannot badly hurt.
- 03
Phased migration
Workload group by workload group, on a cadence set by risk and coupling, each with validated data, a working rollback and a cutover that happens only once the target is proven to match the source and behave under real load. Duration scales with the size of the estate.
- 04
Optimisation and decommission
Once workloads are running in the cloud, a right-sizing and cost-governance pass against real usage, applying commitment discounts where usage now justifies them, decommissioning the retired systems and the old environment, and handing over the documentation and runbooks your team needs to operate it.
What working with us actually means
We operate what we build
Because we run cloud systems for a living, we are allergic to the migration that looks fine on cutover day and becomes an expensive problem once the bills and the outages arrive. The target we design has cost governance, monitoring and reproducibility built in from the start, because we know what it is like to be the one on call for an environment that was moved in a hurry and never made operable.
Honest about when not to move
Our incentive is a migration that works, not a maximal one. We will tell you plainly when a workload should stay on-premises, when a lift-and-shift will cost you more than the data centre, and when hybrid is the right answer. The straight advice you are far more likely to get from engineers who operate cloud systems than from anyone paid on migration volume.
Senior engineers only
A migration is full of decisions that are cheap to get wrong and costly to unwind. The dependency nobody mapped, the data moved without validation, the instance sized by a guess, the residency obligation noticed too late. The people planning and running yours have done this on estates where those mistakes had consequences, and design to avoid them. No juniors learning cutover and data migration on your production systems.
Multi-cloud, chosen on fit
We work across AWS, Azure and Google Cloud and pick on where your workloads genuinely belong and what they will really cost to run, not on a default badge. Where consolidating clouds or designing a deliberate hybrid is the right call, we do that too, with the trade-offs shown to you honestly rather than hidden behind a platform preference.
How to engage us
Three ways to work with us on this, chosen to fit the problem, not our margin.
- Dedicated team A standing team that works only on your product, in your rituals and your tooling. Best when the roadmap outlives the project. Ongoing product development
- Staff augmentation Named senior engineers embedded into your existing team, reporting into your leads. Best when you know what to build and need capacity. Filling a capability gap
- Software outsourcing A defined outcome delivered end-to-end by an accountable team. Best when you want the result owned, not just the hours filled. Outcome-owned delivery
Related services
Part of Cloud Engineering. Other work we do alongside this.
Weighing the options
The decisions people are usually making at the same time as this one.
Common questions
Will moving to the cloud save us money?
Not automatically, and a naive migration frequently costs more. A machine that sat in a rack you already owned becomes metered by the hour once it is in the cloud: provisioned for peak, running at idle most of the time, and now paying for storage and egress that used to be effectively free. A straight lift-and-shift carries those inefficiencies across and starts charging rent on them. The saving is real but it comes from a deliberate target architecture: right-sized compute, managed services that scale down when idle, storage tiered by access, and cost governance watching spend, not from the act of moving. We build a cost model during the assessment that compares your true current baseline against the projected cloud run cost per workload, so you decide with numbers rather than hope, and we will tell you where the honest answer is that a workload should not move.
What are the “six Rs” and why do you decide them per workload?
The six Rs are the possible fates of a workload in a migration: rehost (lift-and-shift it unchanged), replatform (move it onto a managed service with modest change), refactor (rework it to genuinely use the cloud), repurchase (replace it with a SaaS product), retire (switch it off because nobody needs it), and retain (deliberately leave it where it is). A blanket policy (“lift-and-shift everything” or “refactor everything”), is wrong precisely because workloads differ: a low-value system near end-of-life is not worth refactoring, while a lifted, always-on database may quietly cost more than replatforming it to a managed one. We decide each workload on its value, its remaining life, how tightly it is coupled to everything else, and what the cloud version would genuinely cost to run, and we write the reasoning and the cost implication down for each, including the ones we recommend not moving.
How do you migrate without taking the business offline?
By phasing the move and keeping a working rollback at every step, rather than betting everything on a single big-bang weekend. We migrate the low-risk, loosely-coupled workloads first to prove the target architecture, the networking and the cost model on systems that cannot badly hurt if they stumble, then work towards the critical ones with that learning banked. Tightly-coupled systems move together or behind a temporary integration so a half-migrated dependency chain never leaves you inconsistent. For the data, the cutover technique is chosen by how much downtime the business can tolerate. A bulk transfer with a final sync, change-data-capture for near-zero-downtime, or running both in parallel, and each workload only cuts over once the target has been proven to match the source and to behave under real load.
Should everything move to the cloud?
No, and we will say so. Some workloads should stay on-premises or in a hybrid arrangement, because their latency requirements suit local hardware, because data gravity makes moving the data impractical, because a flat, predictable load gets nothing from the cloud’s elasticity and would simply cost more, or because a residency or compliance obligation is better met where the data already sits. A good migration is a set of deliberate per-workload decisions, and “retain” is one of the six legitimate outcomes. We design hybrid boundaries properly when that is the right answer (the connectivity, the identity, the security across the divide), rather than forcing everything across for the sake of a tidy “all-in” diagram, which is a common way to spend money moving something that was fine where it was.
How do you make sure our data arrives intact and stays compliant?
Data is the part of a migration with the least room for error, so we move it with verification rather than hope. We plan the transfer around the data’s size, its rate of change and the tolerable downtime, encrypt it in transit over private or encrypted connectivity, and validate that the target genuinely matches the source (by row counts, checksums and spot reconciliation), before anything is allowed to rely on it. Compliance and data residency are decided before the move, not after: where data must legally stay in a jurisdiction, we choose regions and design so it demonstrably does, throughout the migration as well as after, since even a temporary staging copy in the wrong region breaches residency. Access to both environments during the move is least-privilege, time-limited and logged, so the migration window itself does not become the exposure.
Thinking about Cloud Migration?
Tell us the problem in your own words, not in requirements. A senior engineer reads it and comes back with a straight view on whether Cloud Migration is the right answer here, or what would be.
- 01A senior engineer reads it. Not a form queue, and not an account manager.
- 02We reply either with questions or with a straight answer that we are not the right fit.
- 03If it looks like a fit, a technical call with the person who would actually run the delivery.
- 04Then scope, effort and risk in writing, before anyone signs anything.