Cloud migration, planned as one clean leap.
Move workloads off the datacentre, or between clouds, without the drift and downtime that sink most migrations. We assess every workload against the 7 Rs, lay proper landing zone foundations, and re-platform to AWS or Google Cloud in waves, each one reversible, each one tested. Cloud-agnostic, infrastructure-as-code, no reseller lock-in.
Built for scale-ups and established engineering teams.
Cloud migration earns its place when the platform you are on is holding the business back, or when a datacentre lease, an acquisition or a cost ceiling forces the question. These are the situations where a planned move pays for itself, whether you are a fast-growing product company or an established business modernising off older infrastructure.
Leaving a datacentre or colo
A lease is ending or the hardware refresh is due, and the case for owning racks no longer holds. You need a clean exit onto cloud without carrying the old estate over as-is.
Cloud-to-cloud moves
An acquisition, a pricing change or a strategic decision means moving from one provider to another. You want the move designed deliberately, not lifted blindly.
Escaping a stalled lift-and-shift
A previous rehost copied the datacentre into the cloud and the bill went up while nothing got better. You need modernisation, not another straight copy.
Cost and reliability under pressure
Spend and incidents are both climbing on the current platform. Managed services, autoscaling and proper foundations give you something you can defend.
Growth outpacing the platform
Traffic and team size have outgrown a single region or a hand-built estate. You need networking, identity and guardrails that scale with the business.
Setting up for what comes next
Containers, Kubernetes, data platforms and AI workloads are on the roadmap. The migration should land you on foundations those can build on cleanly.
Assess every workload, then move in waves.
The two most common ways migrations go wrong are a blanket lift-and-shift that carries every problem into the cloud, and a big-bang cutover that leaves no way back. We avoid both. Each workload gets a deliberate strategy from the 7 Rs, foundations are laid before anything moves, and the migration runs in reversible waves so it can pause, roll back or resume without drama.
Principles we hold to on every migration.
- Every workload is assigned an R (rehost, replatform, refactor, repurchase, retire, retain or relocate) on evidence, not by default.
- Landing zone foundations come first: accounts and projects, networking, identity and access, and guardrails, all as code.
- Stateless workloads move first to prove the path; data and stateful services are planned separately with backups and restore drills.
- Rollback is tested, not assumed. If a wave misbehaves, traffic returns to the source platform in minutes.
- Cloud choice follows workloads, not partner quotas, and everything ships as infrastructure-as-code your team can read and own.
What a cloud migration covers.
7 Rs assessment & wave plan
Workload inventory, dependency mapping and a strategy per workload, turned into a ranked, scheduled migration plan with a clear cost and risk picture.
Landing zone foundations
Multi-account or multi-project structure, networking, IAM, logging and guardrails as code, so the estate is governed from the first workload in.
Re-platforming & modernisation
Managed databases, queues and object storage in place of self-run equivalents, and containerisation where a workload should become a modern service.
Data migration & cutover
Replication, backfill and a rehearsed cutover strategy for data stores, with a short, agreed window only where a workload genuinely needs one.
Zero-downtime waves
Traffic shifting behind DNS, load balancers or replication, health gates, error-budget checks and a tested rollback for every wave.
Handover or managed run
Runbooks, observability and team pairing for a clean handover, or an agreed managed operating model. You own the code either way.
Migration is one engagement within a broader cloud transformation. Where the modern target is containers, it flows naturally into Kubernetes migration, and the platform choice is often AWS or Google Cloud, with self-service built on top through platform engineering.
Our cloud migration process.
Four phases, planned backwards from a safe cutover. The architecture review confirms exact scope, target platform and timeline before anything moves.
Assess
Workload inventory, dependencies, statefulness and constraints, each mapped to one of the 7 Rs, ending in a concrete wave plan.
Foundations
Landing zone stood up as code: accounts or projects, networking, IAM, logging and guardrails, ready before the first workload moves.
Migrate in waves
Re-platform and cut over one wave at a time, with data handled explicitly, health gates and a tested rollback at every step.
Operate & own
Handover with runbooks and infrastructure-as-code, or an agreed managed operating model. Everything lives in your repositories.
The tools we actually use.
No reseller agreements and no partner quota. Recommendations follow your workloads. Typical building blocks on a migration:
Target platforms
Amazon Web Services and Google Cloud, with hybrid or on-premises kept in the picture where data residency or existing hardware requires it.
Infrastructure as code
Terraform or OpenTofu for accounts, networking and services, with modular, reviewed, version-controlled definitions from day one.
Landing zone & identity
Multi-account or multi-project structure, VPC and interconnect design, IAM and SSO, plus guardrails and policy-as-code for governance.
Data migration
Native replication, database migration tooling and object-storage transfer, with backfill, validation and a rehearsed cutover per data store.
Modern targets
Managed databases and messaging, serverless where it fits, and Kubernetes on EKS or GKE where a workload should become a modern service.
Observability & cost
Metrics, logs and traces wired before cutover, with cost visibility and right-sizing so the new estate is defensible on both counts.
Cloud migration FAQ.
What is cloud migration?
Cloud migration is the process of moving applications, data and infrastructure from where they run today, whether that is an on-premises datacentre, colocation, or another cloud, onto a cloud platform such as AWS or Google Cloud. Done well, it is not a copy-paste of servers but a planned re-platforming: each workload is assessed, the target architecture is designed around it, and the move is executed in waves with a tested rollback so the business keeps running throughout.
What are the 7 Rs of cloud migration?
The 7 Rs are seven strategies for each workload: rehost (lift-and-shift as-is), replatform (small optimisations on the way, such as a managed database), refactor or re-architect (redesign for the cloud, often containers or serverless), repurchase (move to a SaaS product instead), retire (switch off what is no longer used), retain (leave it where it is for now), and relocate (move whole environments without changing them, for example VMware to the cloud). We assign an R per workload during discovery rather than applying one blanket strategy to everything.
How do you migrate without downtime?
We move in incremental waves rather than a single big-bang cutover. The target environment runs alongside the source, workloads move a few at a time, and traffic shifts gradually behind DNS, load-balancer or replication-based strategies while health and error budgets are watched. Data is migrated with replication and a short, agreed cutover for stateful stores, and every wave has a tested rollback. Most services move with no user-visible downtime, and the few that need a window get a short, scheduled one arranged in advance.
Should we go multi-cloud?
Usually not by default. Multi-cloud adds real cost in networking, identity, tooling and the skills your team has to keep sharp on two platforms. It earns its place for specific reasons: a regulatory or resilience requirement, a workload that is genuinely better on another provider, or an acquisition that already runs elsewhere. We help you make that call on evidence, and where you do run more than one cloud, we keep the design deliberate with infrastructure-as-code rather than accidental sprawl.
Which cloud should we choose?
The choice is led by your workloads, team and constraints, not by a partner quota. We hold no reseller agreements, so the recommendation is honest. AWS has the broadest service catalogue and the deepest ecosystem; Google Cloud is strong on data, analytics and Kubernetes with GKE. We weigh your existing skills, the managed services each workload needs, data residency and cost, then recommend the platform that fits, or a pragmatic split if the evidence supports one.
Planning a move to the cloud?
Start with the readiness scorecard, or book a free 30-minute architecture call. A senior engineer reviews your workloads and returns a ranked, wave-by-wave migration plan.