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Cloud engineering, with the bill in the design
Migration and modernisation for systems already carrying load, then the operational work that follows: capacity that tracks demand, backups you have actually restored, and enough telemetry to explain why last Tuesday was slow.
The interesting decisions are made before you migrate
Lifting a system into the cloud unchanged is the fastest option, and it often costs more per month than the servers it replaced. Rewriting it around managed services costs less to run but takes longer and carries more risk while it is in flight. Most estates need a different answer for each workload, and working out which is which is the actual job.
So we start with what you run today: instance sizes and utilisation, storage tiers, egress, licence terms, and the batch job that only matters on the last day of the month. That becomes a migration order, a projected monthly figure for each option, and a rollback plan for anything touching customer data. The bill is a design output — architecture decisions and cost decisions are the same decisions, and treating them separately is how a migration quietly doubles its run rate.
After the move the work is operational: right-sizing once real load is visible, scaling policies tied to a metric that leads demand rather than trails it, restores rehearsed instead of merely configured, and logs, metrics and traces joined up well enough to explain an incident afterwards. We can run that alongside your team, or hand it over with runbooks and infrastructure as code in your own accounts.
The problem is rarely the technology
A monthly bill nobody can attribute to a team. A cluster running three copies of everything for a service with modest traffic. A backup job that has never been restored. An incident where the only evidence anyone can find is a screenshot in a chat thread.
None of that is exotic, and none of it is fixed by a larger instance type. It gets fixed by treating cost, capacity, recovery and visibility as part of the design rather than as things you will get to once the migration is finished.
Migration without a rewrite you can't afford
Modernisation, one workload at a time
A bill you can attribute to a team
Capacity that tracks demand
Backups that have been restored
The work that starts once the strategy deck is closed
Five things, in the order they usually matter. Migration first, because until a workload has moved nothing else is real. Then whatever modernisation that particular service can justify. Then cost, capacity and resilience, which are not a phase — they are the thing you do every month for as long as the system runs. Where a piece of this is not worth doing for a team your size, we will say so.
Migration, modernisation, and the operations that follow
Each of these ships with a rollback path and a projected monthly cost, agreed before the work starts.
Migration
Inventory first, then a move order that starts with the workloads nobody would miss at three in the morning. Rehost what is fine as it is, replatform what is close, and leave the one or two systems that genuinely need rewriting until there is budget to do it properly.
Modernisation, in moderation
Containers, managed databases and queues where they remove work. Service meshes, microservice fleets and multi-region active-active usually do not — for a team under a dozen engineers they add more operational surface than they take away. We will tell you which parts of cloud native are worth it for you.
Cost engineering
Tagging so spend can be attributed, right-sizing against measured utilisation, storage lifecycle rules, and commitment cover for the baseline once it is predictable. Most of the saving comes from switching things off and choosing the right storage class, not from clever architecture.
Scaling and autoscaling
Policies tied to a signal that leads demand — queue depth, concurrent requests, jobs waiting — rather than CPU after the fact. With load testing, so the first time you meet the ceiling is not during a launch, and floors and caps set so a runaway loop cannot scale you into a five-figure night.
Resilience and observability
Backups verified by restoring them, recovery objectives written down and rehearsed, failover you have practised on a normal Tuesday, and logs, metrics and traces correlated well enough to answer why something was slow without guessing.
Public, private or both — and what each really costs
Public Cloud
The right default for most workloads: elastic, quick to start, and priced so that idle capacity is your problem rather than the provider's. The savings come from switching things off and picking the right storage class, not from the discount page.
Private Cloud
Dedicated capacity where data residency, licence terms or a regulator make it necessary. The monthly figure is steadier and easier to forecast — in exchange you own capacity planning and the hardware refresh cycle again.
Hybrid Cloud
Common, and usually sensible: the ERP stays where it is, new services go to the cloud. The part to watch is the link between them. Latency across that boundary shapes your architecture, and egress across it is where hybrid bills go wrong.
Cloud-Based Disaster Recovery
Cloud as the second site for systems that live elsewhere — far cheaper than a matching data centre standing idle. It only counts once you have failed over deliberately and measured how long it took to come back.
DRaaS — Recovery You Can Rehearse
A managed recovery target with an agreed limit on how much data and time an outage can cost you. Worth buying when running your own standby would cost more than the outage it prevents; not worth it for systems that can be rebuilt from a backup in an afternoon.
What working with us on cloud actually looks like
Written by people who operate it
The migration plan comes from the same engineers who will be on the call when a cut-over does not go to plan. Architecture advice from someone who has never carried a pager is worth less, and usually costs more to run.
A number attached to every option
Each design choice arrives with a projected monthly figure. If an approach saves engineering time but doubles the bill, you hear that before it is built rather than at the end of the first quarter.
Sized for your load, not a reference diagram
Reference architectures are drawn for companies far larger than most. We start from your traffic, your data volume and the size of your team, and leave out the tiers you would only be running for their own sake.
Portable where portability is cheap
Managed services remove real work and are usually worth the lock-in. We keep the boundary where switching would genuinely hurt — data formats, the deployment path, anything holding state — and let the rest lean on the provider.
Handover, not dependency
Runbooks, dashboards and infrastructure as code, in your accounts and your repository. You should be able to stop working with us and have nothing break, which is a low bar that a surprising amount of consulting work fails.
Security designed in
Least-privilege roles, encryption in transit and at rest, managed secrets and audit logging as part of the build rather than a later pass. Systems are designed to support obligations such as GDPR; the scope of that work is agreed per engagement.
Four steps, and a number at the end of each
- 01
Inventory and baseline
What runs, on what, costing what. Current spend broken down by workload, utilisation measured over a period that includes your busiest day, dependencies, licence terms and data volumes. Almost every unpleasant surprise later is something that was missed here.
- 02
Plan and estimate
A move order, a chosen path per workload — rehost, replatform, rebuild, or leave it exactly where it is — and a projected monthly cost for each. Plus the rollback for anything touching customer data, agreed in writing before any of it starts.
- 03
Migrate in slices
One workload at a time, each with a cut-over window, a verification checklist and a way back. When the first real bill arrives we compare it against the estimate and adjust the plan, rather than adjusting the explanation.
- 04
Operate and tune
Right-sizing once real load is visible, scaling policies corrected against actual traffic, restore drills on a schedule, and a monthly look at spend by tag. Run alongside your team, or handed over with runbooks when you would rather own it.
Bring your current bill and an architecture diagram. We will come back with which parts are worth changing, which are fine as they are, and roughly what each option would cost per month.
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