Lift-and-shift without an operating model
Workloads move, but identity, networking, backup, and deployment remain informal. The bill rises while change still feels risky.
Cloud engineering for systems that stay available
Cloud is not a destination. It is an operating model. We design accounts, networks, identity, and workloads so teams can deploy with confidence, recover from failure, and understand what they are spending.
Overview
What does cloud engineering involve?
Cloud engineering is the design, build, and operation of the infrastructure applications run on in AWS, Microsoft Azure, or Google Cloud: account and network structure, identity, compute, storage, deployment automation, resilience, and cost controls. Done well, it gives teams a platform they can change safely and a bill they can explain.
It overlaps with DevOps but is not the same job. Cloud engineering decides what the platform is — landing zone, network, security boundaries, recovery design. DevOps engineering decides how change moves through it. Most programmes need both, and we scope them separately so each has a clear owner.
The problem
Where cloud estates usually start to strain
Environments that only a few people understand
Critical paths live in undocumented consoles. New engineers cannot reproduce infrastructure, and reviews become guesswork.
Availability planned after an outage
Single points of failure, untested restore procedures, and unclear ownership appear only when a region, zone, or vendor service fails.
Capabilities
What our cloud engineering work includes
Architecture and landing zones
Account or subscription structure, network topology, identity boundaries, and baseline controls that match how teams actually ship software.
Migration and modernization
Workload assessment, sequencing, cutover planning, and a clear choice between rehost, replatform, and rebuild — not a single recipe for every system.
Environments defined as code
Landing zones and environments built as code with our DevOps practice, so production is reproducible and never assembled by hand.
Resilience and recovery
Availability targets, failover patterns, backup policy, and restore drills that leadership can understand without a diagram decoder.
Security and access
Least-privilege identity, secrets handling, network controls, and audit trails that fit existing security review, not a parallel shadow process.
Performance and cost
Right-sizing, storage lifecycle, reserved capacity where it is justified, GPU or managed model capacity for AI workloads sized from measured demand, and tagging that makes owners visible.
How we treat a cloud programme
A typical engagement produces a documented landing zone, workload placement rules, and an operations baseline. Compute, data, and integration sit behind shared identity and observability. Disaster recovery is a tested procedure, not a checkbox on an architecture review.
- Start from workloads, data sensitivity, and operational ownership — not from a preferred vendor slide.
- Make the current estate visible: accounts, dependencies, blast radius, and what is already automated.
- Design the smallest landing zone that teams will actually use, then expand it.
- Move systems in waves with explicit rollback, not a single weekend that cannot fail.
- Leave monitoring, access, and cost reports in the hands of the people who will run the platform.
Decision guide
Rehost, replatform, or refactor?
A cloud migration strategy is chosen per workload, not per programme. These are the common options and when each one is the honest choice.
| Approach | What changes | Choose it when | Watch for |
|---|---|---|---|
| Rehost (lift and shift) | Servers move largely as they are. | A hard deadline — a data-centre exit or contract end — matters more than optimisation. | Running costs can rise, and old operational habits move with the servers. |
| Replatform | Selected components become managed services: databases, queues, load balancers. | You want less operational work without rewriting the application. | Hidden coupling to the old platform, such as file paths and scheduled jobs. |
| Refactor or rebuild | The application is redesigned around cloud-native services. | The system is strategic and its current design blocks change or scale. | The longest timeline; it needs product ownership, not only infrastructure work. |
| Retain or retire | The system stays where it is, or is switched off. | It has low value, is hard to move, or is already being replaced. | Retained systems still need connectivity, monitoring, and an owner. |
Most estates use several of these at once. The inventory decides the mix.
Where this typically applies
First production landing zone
A growing product team needs isolated environments, guarded deployments, and a cost view that finance can read.
Multi-account cleanup
Years of organic growth left unused resources, inconsistent IAM, and no shared network pattern.
Regulated workload placement
A subset of systems needs stricter isolation, encryption, and evidence for internal audit.
Integration and implementation
- Identity providers and existing directory services
- CI/CD and artefact registries
- On-premises or colocated systems that will remain for a period
- Observability and security tooling already in use
Industry context
Trade-offs
Implementation challenges to plan for
Managed services versus portability
Managed databases and queues reduce operational work but deepen dependence on one provider. We decide per component and write down the exit cost instead of defaulting to either extreme.
Resilience has a price
Active-active, multi-region designs add infrastructure and data-consistency work. Many systems are better served by a tested restore into a second region with an agreed recovery time.
Landing-zone scope
Too little structure and accounts sprawl; too much and teams route around the controls. We start with the smallest set of guardrails people will actually use, then extend it.
Cost visibility is not cost reduction
Tagging and dashboards make spend visible. Savings come from owners with budgets and from architecture changes: rightsizing, storage lifecycle rules, and switching off idle environments.
Security, scale, and the day after launch
Security
Access is designed around roles people already have. Secrets do not live in tickets. Changes are attributable.
Scalability
Auto-scaling is used where load is variable. Persistent systems get capacity planning instead of hope.
Maintainability
Infrastructure is code, reviewed like application code. Runbooks describe the unusual cases.
How an engagement usually runs
01
Assess
Inventory, risk, cost, and the real constraints of the teams who will operate the platform.
02
Design
Target architecture, migration waves, and the controls that must exist before cutover.
03
Build
Landing zone, automation, and the first production-shaped environment.
04
Migrate
Controlled moves with rehearsal, monitoring, and a defined rollback.
05
Operate
Handover with dashboards, access reviews, and a backlog for cost and reliability.
FAQ
Cloud Engineering: frequently asked questions
When should a company migrate to the cloud?
When there is a concrete driver: a hardware refresh or data-centre exit, a hosting contract ending, capacity you cannot add quickly, or teams blocked by slow provisioning. Cost alone is a weak reason — workloads moved unchanged can cost more in the cloud. Start with an inventory and a business case per group of workloads.
How long does a cloud migration take?
It depends on how many workloads there are, how tightly they are coupled, and how much is modernized on the way. A landing zone and a first, low-risk wave come first; the rest of the estate moves in planned waves. We give an estimate after the inventory — a date set before dependencies are known is a guess.
What is a cloud landing zone?
A landing zone is the pre-configured foundation that workloads are deployed into: the account or subscription structure, network layout, identity and access model, logging, and security guardrails. Building it before the first production workload is what keeps a cloud estate from becoming a collection of one-off environments.
How much does a cloud migration cost?
The main cost drivers are the number of workloads and how tightly they are coupled, how much is modernized rather than moved as-is, data volumes and transfer, compliance requirements, and how much of the work your own team takes on. Running costs after the move depend on architecture choices, not only on the provider’s price list. We scope cost after a short inventory rather than quoting a figure up front.
Do you work only on one cloud?
No. We design for AWS, Microsoft Azure, and Google Cloud when the workload and the team’s existing skills justify it. Multi-cloud is a cost, not a default.
Can you migrate without rewriting everything?
Yes. Many programmes start with a safer rehost or replatform, then modernize the systems that actually benefit from a rebuild.
How do you keep cloud costs under control?
By making spend attributable through account structure and tagging, giving each cost an owner with a budget, and changing the architecture where it moves the number: rightsizing, autoscaling, storage tiers, commitment discounts where usage is stable, and scheduling non-production environments.
Will you take over day-to-day operations?
We can support a handover or an initial operate period. Long-term managed operations are scoped only when both sides agree that is the right model.
Keep exploring
Related services and insights
Start with cloud engineering
If this is the constraint you are carrying, describe the current systems and what must not break. We will tell you what a first useful step looks like.