Cloud Migration

Cloud migration, planned before it is executed

A migration that goes wrong rarely fails during the move. It fails afterwards — when the monthly bill is higher than the servers it replaced, when an application that ran fine on one machine is now three services with latency between them, or when nobody can say which workload is costing what. The planning stage is where those outcomes are decided.

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Not everything should move, and not everything should move the same way

The honest first output of a migration project is an inventory with a decision against each workload: lift and shift as-is, re-platform onto managed services, rewrite properly, or leave where it is. Applications with a hard dependency on specific hardware, or with a license that punishes virtualization, sometimes belong exactly where they are.

Lift and shift is fastest and produces the smallest immediate benefit — you now rent the same inefficiency by the hour. Re-platforming onto managed databases, queues and object storage is usually where the operational savings actually come from. We mark which is which before any workload moves.

Cost modeling before the bill arrives

Cloud pricing punishes assumptions. Egress charges on a data-heavy application, per-request costs on a chatty architecture, and over-provisioned instances sized from peak load rather than typical load are the three that most often turn a migration into a budget conversation.

We model the expected monthly cost as part of planning, with the drivers named, so the number that arrives after cutover is one you have already seen. Where the model shows the cloud is more expensive for a given workload, that is worth knowing before the move, not after.

Cutover without a weekend of held breath

The migration plan includes the rollback plan. For each workload we agree the sequence, the data synchronization approach, what runs in parallel and for how long, and the specific conditions under which we abandon the cutover and return to the old environment.

Databases usually move with replication running until the moment of switch rather than a copy-and-pray export. Stateless services move behind a load balancer that can shift traffic gradually and shift it back.

What you are left running

Infrastructure defined as code rather than as a set of console clicks nobody remembers, containerized with Docker and orchestrated with Kubernetes where the workload justifies it, with CI/CD pipelines, monitoring and backups configured before handover — not as a follow-up project.

We work across AWS, Azure and Google Cloud. Which one is right usually follows your existing licensing, your team's skills and your compliance requirements rather than a feature comparison.

What we already build

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Questions we get asked

Before you
brief anyone.

The answers are the same ones we give on a first call — including where the honest answer is "it depends, and here is what it depends on".

How long does a cloud migration take?

The inventory and planning stage is measured in weeks and the execution depends entirely on what that inventory finds. A handful of stateless applications is quick; a monolith with a large database and hardware dependencies is not. We do not quote a migration before the inventory exists.

Will our costs go down?

Sometimes, and not automatically. Lift and shift often costs more than the servers it replaced. Savings usually come from re-platforming onto managed services and right-sizing to real load. We model the expected bill during planning so you see the number before you commit.

Can you migrate without downtime?

For most workloads, yes — replication for databases and gradual traffic shifting for stateless services. Some cutovers genuinely require a window, and where that is the case we say so during planning rather than discovering it on the night.

AWS, Azure or Google Cloud?

Usually decided by your existing licensing, your team's skills and your compliance obligations, not by a feature table. We work with all three and will recommend against a platform your team cannot operate.

What happens to our old environment?

It stays available through an agreed parallel-running period with a documented rollback path, and is decommissioned only once the new environment has been running cleanly under real load.

Do you handle the cloud environment afterwards?

Yes — monitoring, patching, backups and cost review, as part of the maintenance stage of our process rather than a separate engagement.

A practical first step

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