07
Applications moved from ageing servers to containers and cloud platforms one rehearsed wave at a time, on a governed landing zone, with GitOps delivery and a rollback at every stage.
Every stage keeps a way back
Your servers are ageing or expensive to run, and you want to move without downtime surprises.
Sound familiar?
You are modernizing a regulated estate: containerizing workloads, standing up a governed landing zone, or migrating to OpenShift or Kubernetes under change control, with auditors watching.
Sound familiar?
What you can hold the work to, in plain terms.
Accounts, networks, identity, policies and clusters defined in Terraform and Git, reproducible in every environment.
Workloads move in rehearsed waves, each with entry criteria, a cutover plan and a tested rollback.
CI pipelines, signed images and GitOps delivery, so a release is a merge rather than an event.
Tagging, budgets and guardrails from the first day, with FinOps reviews that tie spend to value.
Workloads move into a governed foundation, and every change after that arrives through Git.
Deliver lane: Git holds infrastructure and application code; CI builds, tests and scans, then signs each image and produces an SBOM; Argo CD syncs to the cluster and detects drift; OpenShift or Kubernetes runs each environment with rolling updates. Land lane: the current estate of virtual machines and ageing hosts moves in migration waves (rehost, replatform, refactor, retire), each passing a go/no-go gate with a rehearsed way back, into a landing zone with identity (SSO, least-privilege roles, break-glass access), network (hub and spoke, private endpoints, egress control), guardrails (policy as code, tagging, budgets and alerts), security and central audit logging, and separate production and non-production workloads.
The disciplines inside this service, and the detail we work to in each.
01
Every application placed on a path, with its dependencies, risks and cost understood before anything moves.
02
A governed foundation of accounts, identity, networking and guardrails, defined as code.
03
Workloads containerized and run on OpenShift or Kubernetes, with platform services your teams can use.
04
Paved roads for delivery teams: pipelines, templates and self-service within guardrails.
05
Waves executed under change control, rehearsed and reversible.
06
The platform handed over running, observable and affordable, with the people who operate it trained on it.
Not everything should move, and nothing should move the same way by default. Every workload in the plan gets one of seven treatments, with the reason written down.
| Treatment | Choose it when | What changes | Watch for |
|---|---|---|---|
| Retire | Choose it whenNobody uses it, or another system already does its job. | What changesIt is switched off and its data archived. | Watch forRetention rules for what is archived. |
| Retain | Choose it whenA regulator, a contract or a dependency keeps it in place for now. | What changesNothing, until a review date set in the plan. | Watch forLatency to the workloads that did move. |
| Rehost | Choose it whenA deadline matters more than change, and the application is stable. | What changesThe same virtual machine runs in the cloud. | Watch forCarrying old costs and patching habits into the new platform. |
| Relocate | Choose it whenA VMware estate must leave its hardware quickly. | What changesWorkloads move, unchanged, to a managed VMware service. | Watch forLicence cost, and a second move later. |
| Replatform | Choose it whenSmall changes buy a real gain, such as a managed database or a container image. | What changesThe code stays; the runtime and operations change. | Watch forTesting the new runtime as carefully as new code. |
| Refactor | Choose it whenThe application must scale, release often or be split apart. | What changesIt is re-architected for containers and managed services. | Watch forCost and time, justified only by the business case. |
| Repurchase | Choose it whenA SaaS product now does the job better than the custom system. | What changesData moves to the product and the old system is retired. | Watch forData migration, integrations and training. |
Each treatment is costed in the plan, so the order of the waves follows value and risk, not convenience.
Every stage ends with a document you keep and a gate you can check.
Applications, dependencies, risks and cost.
Exit gate: Every workload has a treatment, an owner and a wave.
You receiveInventory and migration plan
Identity, network and guardrails in place, as code.
Exit gate: Identity, guardrails and logging tested, all built from code.
You receiveLanding zone ready
One representative workload moved and verified end to end.
Exit gate: The pilot workload is live, its rollback rehearsed and signed off by you.
You receivePilot sign-off
The rest, in waves, each rehearsed and reversible.
Exit gate: Each wave passes its go/no-go checks before the next begins.
You receiveWorkloads migrated
Runbooks, alerts, cost reviews and handover.
Exit gate: Runbooks, alerts and dashboards accepted by the team that will run them.
You receiveOperations handover
Written down before work starts, so nothing is assumed.
The public frameworks we measure the work against, and the platforms we run it on.
Client cases name the industry and the stack, never the client.
OpenShift 3 to OpenShift 4, two-site DR, then a year of 24x7 managed service
Pilot and reference architecture for automated DR drills
13 months of DevOps, back end and data work on a serverless AWS data lake
Assessment, proof of concept and cloud strategy
A fixed, small first engagement, then the model that fits the rest.
A first engagement
A time-boxed assessment of your applications and infrastructure, ending in a plan your review board can approve.
Dedicated team
Long programs such as a platform migration
A monthly rate per engineer
Time and materials
Ongoing improvement, support and discovery work
Billed for the time used
Fixed price
Defined projects: a website, an assessment, a migration stage
One price for that scope
Yes. Recent work includes platform migrations for banks.
OpenShift suits organisations that want a supported, opinionated platform with strong defaults for security and operations. Managed Kubernetes, such as EKS or AKS, suits teams that want flexibility and already run the surrounding tooling. The assessment recommends one, with the trade-offs.
By rehearsing. Each wave is rehearsed on a copy, cut over in an agreed window with data replication in place, and kept reversible until you sign off.
It can, when workloads are lifted without change. The cost model is part of the assessment, and tagging, budgets and rightsizing are in place from the first day.
Before a wave starts, three things are agreed in writing: what triggers a rollback, how long the rollback window stays open, and which way data syncs if traffic goes back. The pilot rehearses it, so a real rollback is never the first attempt.
Plain-language articles on cloud transformation, with their sources.
Cloud19 min read
Serverless computing runs your code only when events arrive, scales it to zero and bills per use. How it works, the platforms, limits, costs and 2026 trends.
Updated
Cloud17 min read
What 5G and 5G-Advanced are, how 6G differs, and the 6G timeline as of 2026: first specifications in 3GPP Release 21, launches expected around 2030.
Updated
Cloud17 min read
A quantum circuit is qubits, gates and measurements. How circuits are designed and compiled for real chips, and why error correction decides what they can run.
Updated
Cloud15 min read
Quantum computers should help with chemistry and materials, not everyday IT. What the evidence shows, vendor roadmaps and why post-quantum crypto starts now.
Updated
Cloud16 min read
A quantum computer uses qubits and interference to beat classical machines on a few problems, not all. How it works, what it is good at, and its state in 2026.
Updated
The same engineers answer for each of these.
Tell us what you run and what is getting in the way. You get a reply within 24 hours.
