Get off end-of-life servers
Move workloads off ageing hardware, unsupported OS versions or a data centre lease that is ending, before the deadline forces a rushed decision.
Learn: are the deadline workloads running on supported infrastructure?
Services / Data & Cloud
Cloud architecture & migration.Move what pays. Leave what doesn't.
We plan migrations from evidence of what you actually run, build the landing zone before anything moves, and migrate in verified waves with rehearsed rollback paths. No big-bang cutovers, no bill surprises, and a platform your team owns.
Waves with evidence. Rollback paths that work. Costs with context.
The business case
A migration should solve a problem, not create a project.
Some migrations are overdue: expiring data centre leases, unsupported software, hardware at end of life. Others are fashionable rather than necessary. We start with what the cloud would actually change for you, and we are direct when the answer is 'not much, yet'.
When this service fits
Infrastructure is ageing or unsupported, costs or reliability are unpredictable, a deadline is approaching, or AI and data plans need infrastructure that does not exist yet. Access to systems, logs and the people who run them is essential.
When something else fits better
If your infrastructure is healthy and your goal is a new product or an AI feature, product or AI engineering is the better starting point. If the goal is analytics rather than infrastructure, data engineering may serve you better.
Where this applies
Different starting points. One disciplined process.
These are example situations, not pre-packaged promises or claims about past results.
Rehost the predictable, rethink the valuable
Lift straightforward systems as-is while redesigning only the parts that benefit from cloud-native patterns, so effort lands where it pays back.
Learn: do the redesigned parts actually show cost or reliability gains?
Reduce the running bill
Right-size instances, storage tiers and idle resources so the cloud bill reflects real usage instead of a migration-sized guess.
Learn: does the monthly spend trend down after optimisation, with nothing broken?
Make disaster recovery real
Replace backups nobody has restored since last year with tested recovery to a second region, with a recovery time the business has actually agreed.
Learn: does the last restore test meet the agreed recovery window?
Prepare the ground for AI
Stand up the data platform, GPU access and networking that AI work needs, so model work does not wait on infrastructure.
Learn: can an AI team get compute and data access without a ticket queue?
Regulated workloads in the cloud
Move systems with privacy or financial obligations while keeping residency, access control and audit evidence intact, verified before go-live.
Learn: can you show where data lives and who accessed it, on demand?
How a migration runs
Small waves, verified, with a way back.
Workloads move from the current environment through a migration checkpoint into a landing zone, where applications run on built-as-code infrastructure. Each wave verifies before the next starts, and the rollback path stays rehearsed until the wave is proven.
What we always include
Discovery from real systems, a landing zone defined in infrastructure code, rehearsed cutovers with measured data integrity, and a documented rollback path for every wave.
What we keep out
Big-bang weekend migrations, rewrites nobody asked for, and lift-and-shift of systems that should have been retired instead.
Assessment & strategy
A migration plan built from evidence, not a diagram slide.
We inventory what actually runs, what depends on what, and what it costs today. The strategy follows the evidence, including the honest conclusion that some things should stay where they are.
Discovery of what really runs
Application inventory, dependency mapping and traffic analysis, so the plan covers the spreadsheet system nobody mentioned until go-live week.
Wave planning
Workloads grouped into migration waves by dependency, risk and business calendar, each wave small enough to verify before the next starts.
Cost baseline & target
What the current estate costs, what the target architecture is expected to cost, and the assumptions behind the estimate, written down.
Stays and goes
A deliberate list of what migrates, what gets retired and what stays on-premises, because the cheapest migration is the one that never happens.
Landing zone & architecture
The destination is built before anything moves.
A landing zone is the account structure, networking, identity and guardrails every future workload inherits. Building it first is what separates a cloud platform from a pile of virtual machines.
Account & project structure
Environments separated, ownership clear and blast radius contained, so one team's mistake does not take down another's production.
Networking & connectivity
VPCs or VNets, private links to data sources, VPN or ExpressRoute where needed, designed for the traffic your systems actually carry.
Identity & access
Roles, federated sign-on and least-privilege defaults wired in from day one, with break-glass access documented and tested.
Guardrails as code
Policy and tagging rules enforced automatically, so the estate stays organised as it grows instead of drifting into a naming free-for-all.
Migration execution
Small moves, verified, with a way back.
Each workload moves through the same discipline: replicate, test against real usage, cut over, and verify. Every wave has a documented rollback path that is actually rehearsed, not theoretical.
Rehearsed cutovers
Trial migrations into staging with real data volumes and real load patterns, so the production cutover repeats something already proven.
Data migration with integrity checks
Databases and files moved with checksums, row counts and reconciliation, so data completeness is measured rather than assumed.
Downtime you agree in advance
Cutovers scheduled around the business, with offline windows and user communication agreed before the maintenance starts.
Rollback paths that work
The old environment kept warm until the new one is verified, with a documented, tested return route if the cutover fails.
Optimisation & operations
The bill and the reliability, both managed after the move.
Migration is not the finish line. After each wave we right-size, automate operations and make cost and health visible, so the platform improves rather than decays.
Right-sizing & reserved capacity
Usage measured after migration, instances adjusted to reality and commitments bought where the maths supports them.
Infrastructure as code
Environments defined in Terraform or Pulumi, reviewed and versioned like application code, so the estate is reproducible.
Monitoring & alerting
Health, performance and cost dashboards with alerts routed to a named owner, so problems surface before users report them.
FinOps habits that stick
Budgets, tagging discipline and a monthly cost review, so spend stays tied to workloads with named owners.
Tools & frameworks
Platform and tooling matched to your reality.
We work across the major clouds and the tooling that keeps migrations repeatable. These are options, not a requirement to use everything on the list.
Cloud platforms
AWSMicrosoft AzureGoogle Cloud
Provider chosen on your workloads, existing licences, team skills and regional requirements, not on fashion.
Infrastructure as code
TerraformPulumiCloudFormation / Bicep
Reproducible, reviewed environments across accounts and providers.
Migration tooling
AWS DMS / Azure MigrateDatabase native replicationrsync-based file transferContainerised rehosting
Matched to workload type, data volume and acceptable downtime.
Networking & connectivity
Transit gatewaysPrivate Link / Private EndpointsCloudflare / CDNSite-to-site VPN
Connectivity between cloud, offices and remaining on-premises systems.
Identity & security
OIDC / SAML federationIAM roles & policiesSecrets managementPolicy engines
Least-privilege access and guardrails enforced by the platform.
Containers & compute
Kubernetes (EKS / AKS / GKE)ECS / Container AppsServerless where it fits
Compute shaped per workload; serverless only where usage patterns justify it.
Observability & FinOps
CloudWatch / Azure MonitorGrafanaOpenTelemetryCost management tooling
Health, performance and spend visible with alerts to named owners.
Data & databases
PostgreSQL / MySQL managed servicesSQL ServerRedisStorage lifecycle tiers
Managed services and tiered storage chosen on access patterns and cost.
Platform choice depends on your workloads, existing licences, team skills and data residency requirements. We recommend after the assessment, not before it.
Delivery approach
From discovery to a platform your team runs.
You work with engineers inside the delivery process. Every wave is visible, verified and approved before the next one starts.
- 01
Assess
Inventory applications, dependencies, data and costs; classify workloads and agree what migrates, what stays and what gets retired.
Output: Discovery report, dependency map, wave plan and cost baseline.
- 02
Design the landing zone
Architect the account structure, networking, identity and guardrails, and validate the design against the first wave's requirements.
Output: Landing zone design and architecture decision records.
- 03
Build & pilot
Build the landing zone as code, then migrate a low-risk pilot workload end to end, proving the process before scaling it.
Output: Running landing zone and a verified pilot migration.
- 04
Migrate in waves
Move workloads in planned waves with rehearsed cutovers, integrity checks and rollback paths, verifying each wave before the next.
Output: Migrated workloads with cutover and verification evidence per wave.
- 05
Optimise & hand over
Right-size, automate operations, set up cost governance and transfer ownership with documentation and pairing.
Output: Optimised estate, runbooks and a team that runs the platform.
What your team brings
A decision-maker, access to systems and logs, the people who know what runs where, and whoever owns the maintenance windows and the budget. For regulated workloads, bring compliance stakeholders into scoping early.
Decisions without surprises
The wave plan, expected downtime, cost assumptions and rollback paths are written down and approved before any workload moves. If discovery changes the plan, the change is agreed with you first.
Handover & ownership
Your platform. Your code. Knowledge that stays.
Everything lives in your repositories and cloud accounts from day one. Handover includes the architecture rationale and the operational practices, so the platform stays healthy after we leave.
A platform built as code
Accounts, networking and environments defined in versioned infrastructure code your engineers can read, review and extend.
Evidence per migration
Every wave has a cutover record: what moved, how it was tested, what the rollback plan was and what verification showed.
Costs with context
A running bill tied to workloads and owners, with the assumptions behind it, so future budget conversations start from facts.
Operational ownership
Runbooks, alert routing and monitoring your team operates, with knowledge transferred during the work rather than at the end.
Delivery does not include unlimited maintenance or a service-level commitment. We can agree ongoing cloud operations support, or hand over fully to your own team.
Related engineering services
Choose the support your next stage needs.
Cloud work often connects to data platforms, modernisation or dedicated engineering capacity.
Questions before starting
The practical details.
Should we even move to the cloud?
Sometimes no, or not everything. We assess what you run, what it costs and what constraints you have, and we are direct when staying on-premises, going hybrid or retiring systems is the better answer. A migration that solves no problem is just risk with a budget.
How long does a migration take?
Small estates with a handful of servers can move in weeks. Larger estates with interdependent systems, data migrations and compliance requirements run in waves over months, with production value delivered along the way rather than at a single big-bang cutover.
Will we have downtime?
Some workloads accept near-zero downtime with replication and staged cutovers; others need a short maintenance window, usually minutes to a few hours. We state the expected downtime per workload in the wave plan, and you approve each window before it happens.
What if something goes wrong after cutover?
Every wave has a documented and rehearsed rollback path, and the old environment stays available until the new one is verified under real usage. If a cutover fails its checks, we go back, fix and retry rather than debugging in production.
How do you keep the cloud bill under control?
We set a cost baseline before migrating, right-size after each wave, and put budgets, tagging and alerts in place so spend maps to named workloads. The first bill after a migration is often higher than the steady state; we plan for that and tell you what normal looks like.
Can you handle regulated data?
Yes, with residency, encryption, access control and audit evidence designed into the landing zone and verified before each wave moves regulated workloads. We work within your compliance obligations and recommend qualified advisers where legal interpretation is needed.
Do we need to rewrite our applications?
Usually not all of them, and often not at all. We rehost what works fine as-is, and reserve re-platforming or re-architecting for systems where the change pays for itself in cost, reliability or capability.
What does handover look like?
Your team owns the infrastructure code, the runbooks, the monitoring and the cost governance. We pair with your engineers throughout the waves so knowledge transfers with the work, and we can stay available for later phases or reviews if useful.
Start with the question
Tell us what your infrastructure cannot support today.
We will plan the move that changes that.
Share what runs today, what is forcing the change, and any deadlines. We will agree a practical first wave.