Most cloud programmes do not fail technically. They fail because the target architecture, the operating model and the cost model were decided separately. We work with CIOs, CTOs and enterprise architects to decide them together, and to sequence the migration so the business keeps running while it happens.
Cloud consulting is usually commissioned after one of these has already become visible on a budget line or an incident report.
The invoice grows every quarter while the architecture stays as it was on-premises. Lift-and-shift preserved the original design and added a rental cost, and the elasticity that justified the move is unreachable because the application cannot scale horizontally.
The stateless services moved in the first quarter. What remains is the database everything depends on, the batch window nobody can shorten, and the integration nobody documented. Momentum and budget go with it.
Accounts and subscriptions were created as teams needed them. Networking, identity and logging were decided per project, so there is no consistent boundary to secure, audit or bill against.
Controls exist but are not expressed as configuration, so proving them to an auditor, a customer or a regulator is a manual exercise repeated every time it is asked for.
One provider was chosen for infrastructure, another arrived with an acquisition, a third came with a SaaS dependency. The result carries the cost of multi-cloud without the resilience benefit that would justify it.
The platform changed and the operating model did not. Ticket-driven provisioning, manual change approval and on-premises monitoring produce cloud costs with data-centre delivery speed.
What changes commercially when strategy, architecture and operating model are decided together rather than in sequence.
The technical work is rarely the constraint. The decisions around it are.
Cloud platforms are well documented, and most engineering teams can deploy to them competently. What is harder is the set of decisions that sit above the deployment: which workloads should move and in what order, what the target architecture costs at projected volume, where the regulatory boundary sits, and what the operating model has to become for any of it to be sustainable.
Those decisions are expensive to reverse. A landing zone designed around the wrong account boundary is re-platformed, not reconfigured. A migration sequenced without dependency analysis stalls at the first shared database. A cost model that ignores egress and inter-zone traffic is wrong by a margin that shows up quarterly.
We are engaged to make those decisions deliberately and to record why they were made, so they can be re-examined when the constraints change. We do not resell cloud capacity and hold no provider commissions, which means a recommendation to stay on-premises, to consolidate to one provider, or to move a workload back is available to us and costs us nothing to give.
Four commitments that shape every cloud engagement.
The target architecture is modelled for cost at projected volume before it is committed, including the line items that surprise people: egress, inter-availability-zone traffic, managed-service premiums and the price of idle non-production environments.
Migration order is derived from data gravity and integration coupling, not from which team is available. Moving the easy workloads first feels like progress and frequently makes the hard ones harder.
Provisioning, change management, monitoring and on-call are redesigned alongside the architecture. A cloud platform run with data-centre processes delivers cloud costs and data-centre speed.
Where two options are close, we prefer the one that is cheaper to undo. Managed services reduce operational load and increase switching cost; that trade is made explicitly, workload by workload, rather than by default in either direction.
Technology advisory runs through all of these rather than being sold separately. We do not resell cloud capacity, so platform recommendations carry no margin for us.
Workload-by-workload disposition, the business case behind it, and an honest assessment of what your organisation is currently able to operate.
Account and subscription topology, network segmentation, identity, logging and guardrails, expressed as infrastructure as code.
Dependency mapping, wave sequencing, cutover and rollback design, and architectural support while your team executes.
Connectivity, identity federation, data placement and the operational reality of running more than one platform deliberately.
Identity and access design, network boundaries, encryption and key management, and controls expressed as configuration rather than prose.
Policy as code, tagging and account standards, and the evidence trail that regulatory and customer audits actually ask for.
Cost modelling before build, allocation and showback afterwards, rightsizing, commitment strategy and the architectural changes that matter more than any of them.
Platform team structure, self-service boundaries, change management and the on-call model that has to exist for any of it to be safe.
Security controls in the delivery pipeline — policy checks, image scanning, secrets handling and drift detection — so posture is enforced at deploy time, not reviewed quarterly.
Recovery objectives agreed with the business, then designed for and tested, rather than assumed from a replication feature.
Metrics, logs and traces chosen to answer the questions you will actually ask during an incident, with a retention and cost model that survives contact with production volume.
Where ongoing operations are the right answer, we define the service boundary, the responsibility split and the service levels before anyone signs a contract for them.
A defensible position on what moves, what stays, and why.
Cloud strategy is a disposition decision taken per workload, not a single directional statement. For each system we establish whether it should be retained, retired, re-hosted, re-platformed, re-architected or replaced — and what each option costs over a realistic horizon.
That assessment has to include what your organisation can operate today. A target architecture requiring platform-engineering capability the team does not have and is not funded to build is not a strategy; it is a wish. Where the gap is real, we say so and put capability building into the sequence.
The target state, specified precisely enough to build and to cost.
Architecture decisions determine both the capability and the invoice. Compute model, data placement, network topology and the choice between managed and self-operated services set the cost curve for the life of the system, and most of them are difficult to revisit once workloads depend on them.
We specify the target state as component boundaries, data ownership, integration contracts and non-functional requirements stated in measurable terms — then model what it costs at projected volume before anyone commits to building it.
Sequenced by dependency, with a rollback position at every step.
Migration risk concentrates in data and integration, not in compute. We map dependencies before sequencing, because the order that looks efficient on a spreadsheet frequently strands the workloads everything else depends on.
Each wave is designed to leave a working system. Cutover and rollback are specified together, and the migration proceeds only while the rollback position remains real — a plan that cannot be reversed after the first wave is not a plan, it is a commitment.
For estates where some workloads are not moving, and should not.
Hybrid is frequently the correct end state rather than a transitional one. Latency-bound systems, hardware dependencies, data residency obligations and equipment with years of depreciation remaining are all legitimate reasons for a workload to stay where it is.
The engineering problem is the seam. Identity, network path, data consistency and operational tooling all have to work across the boundary, and the boundary is where most hybrid estates are weakest — usually because it was never designed, only arrived at.
Deliberate multi-cloud is defensible. Accidental multi-cloud is expensive.
Most multi-cloud estates were not chosen. They accumulated through acquisitions, team preference and SaaS dependencies, and they carry the full operational cost of multiple platforms without the resilience benefit that would justify it.
Deliberate multi-cloud is a different proposition, and it is sometimes right: regulatory requirements, genuine concentration risk, or a specific capability available on one platform. Our contribution is to make the position explicit, and to be honest that portability has an ongoing cost which is usually paid whether or not it is ever exercised.
Designed in, expressed as configuration, and evidenced on demand.
Cloud security failures are overwhelmingly configuration failures rather than platform failures — over-permissive identity, storage exposed by default, network paths nobody intended, secrets in places they should not be. The controls that prevent these are architectural, and they are cheapest to apply before workloads depend on the current arrangement.
We design identity and access, network boundaries, encryption and key management as part of the target architecture, and express them as code so posture is enforced continuously rather than assessed periodically.
We describe practices, not credentials. Where a formal certification is required, we design toward the control set — we do not represent NG&NR as holding certifications it has not been awarded.
Guardrails that speed teams up, not an approval queue.
Governance fails in one of two directions. Too little, and every team invents its own account structure, tagging and network model. Too much, and provisioning becomes a ticket queue that teams route around, which produces worse governance than having none.
The workable version is guardrails: policy expressed as code, preventive where the risk justifies it and detective where it does not, so teams move quickly inside a boundary that is enforced automatically rather than reviewed manually.
Architecture first, commitments second, rightsizing third.
Most cloud cost programmes start with rightsizing and reserved capacity because those are the visible levers. They are also the smallest ones. The largest savings are usually architectural: a data model that forces cross-zone traffic, non-production environments running around the clock, or a chatty integration paying egress on every call.
We work in that order — architecture, then commitment strategy, then rightsizing — and we put allocation in place first, because cost that cannot be attributed to a team or a product cannot be managed by anyone.
The foundation everything else is deployed into.
A landing zone is the account structure, network, identity, logging and guardrails that workloads land in. Getting it wrong is unusually expensive: an account boundary that does not match the security or billing boundary is re-platformed rather than reconfigured, and by then there are workloads depending on it.
We design it as infrastructure as code so it is reproducible, reviewable and versioned, and so a new environment is a build rather than a project.
The platform changed. The way it is run has to change too.
This is where most cloud programmes underdeliver. The architecture modernises and the operating model does not, so an elastic platform is run with ticket-driven provisioning, change advisory boards timed in weeks, and monitoring designed for fixed infrastructure.
We define the platform team's responsibility boundary, what product teams can do for themselves inside guardrails, and how change and incident management actually work when infrastructure is code.
Security enforced at deploy time, not reviewed quarterly.
Security controls that live outside the delivery pipeline are applied inconsistently and discovered late. Controls inside the pipeline are applied to every change by construction.
We integrate policy checks, image and dependency scanning, secrets handling and drift detection into delivery, and we tune them deliberately — a gate that produces noise teams learn to bypass is worse than no gate, because it also produces false assurance.
Where ongoing operation is the right answer, define it before signing.
Managed services are appropriate when operating the platform is not where your organisation should spend scarce engineering attention. They become expensive when the responsibility boundary is vague, because everything at the seam is disputed at exactly the moment it matters.
Our contribution is advisory and precedes the contract: what is in scope, who holds which responsibility, what the service levels mean in practice, and how the arrangement is exited if it stops working.
Written artefacts, not a verbal readout. Everything below is designed to be circulated, challenged and revisited after we leave.
The standards we apply, and that we leave your team able to apply without us.
An architecture whose cost is discovered in the first invoice was not designed, it was assembled. Egress, cross-zone traffic and idle non-production are modelled up front because they are where estimates are usually wrong.
They reduce operational load and increase switching cost. That trade is worth making often — but it is made explicitly, workload by workload, rather than by reflex in either direction.
Automatic boundaries that let teams move quickly produce better compliance than approval queues, because approval queues are routed around and guardrails are not.
Every platform decision is assessed for what it costs to reverse. That cost is frequently acceptable — but it should be known at the time, not discovered when circumstances change.
Governance that speeds delivery up rather than slowing it down, and the risk categories this engagement is accountable for.
Engaged before significant code exists, when structural decisions are still cheap to change. Produces the target-state architecture, the technology selection rationale, and a sequencing plan the delivery team can execute.
Engaged when delivery has slowed, costs are rising, or a design that fitted the original problem no longer fits the current one. Diagnostic first: we establish what is actually causing the drag before recommending change.
A named architect available as the system evolves, covering design review, technology decisions and course correction. Delivered under a subscription rather than a fixed project scope.
What actually happens, in order.
An overview of your estate and objectives, a review of the current design, and an assessment of compatibility needs. Its purpose is to establish whether there is useful work to do. If there is not, we say so.
Workload inventory, dependency mapping, current cost baseline and an assessment of what your organisation can operate today.
The target state with its cost modelled at projected volume, and the options that were considered and rejected recorded alongside it.
Account topology, network, identity, logging and baseline policy, delivered as infrastructure as code.
Waves, dependencies, cutover design and rollback positions, with each wave standing on its own business case.
Your team migrates. We stay available for design review and course correction, and we work through the operating-model changes alongside it.
We work across the three major hyperscalers and the surrounding toolchain. The right answer is frequently a subset, not all of it.
Organisations and control tower patterns, VPC design, IAM, EKS, Lambda, S3 and RDS, with the cost characteristics of each.
Management groups and subscription topology, virtual network design, Entra ID, AKS, Functions and Azure Storage.
Project and folder hierarchy, VPC and shared VPC design, GKE, Cloud Run and Cloud Storage.
Cluster topology, workload isolation, ingress and the operating model a cluster requires around it.
Declarative provisioning, module structure, state management and drift detection.
Choosing between functions, containers and virtual machines per workload on cost and operational grounds.
Address planning, segmentation, private connectivity, egress control and the routing behaviour of failure.
Least-privilege role design, workload identity, federation and the elimination of static credentials.
Storage class selection, lifecycle policy, and the data-gravity consequences of placement.
Metrics, logs and traces chosen for incident questions, with a retention and cost model that survives production volume.
Recovery point and time objectives agreed, designed for, and tested rather than assumed.
Policy as code, posture management, image and dependency scanning, and evidence generation.
Sector rarely changes the engineering. It changes the constraints the engineering has to satisfy — residency, availability, audit and the cost of downtime.
Patient data residency, clinical system interoperability, and platforms that cannot take an outage window.
IndustryRegulatory reporting, evidenced controls, and core systems where recovery objectives are contractual.
IndustryClaims and policy platforms on ageing infrastructure, with batch windows that constrain the migration sequence.
IndustrySeasonal load where elasticity is the point of the move, and catalogue and inventory data with real gravity.
IndustryOperational technology that stays on-premises, and the hybrid seam between plant systems and enterprise platforms.
IndustryReal-time tracking and partner integration where latency and egress are direct operating costs.
IndustrySharply seasonal load, student information systems, and constrained operating budgets.
IndustryData residency and sovereignty, procurement constraints, and long-lived legacy estates.
IndustryNetwork-scale data volumes and availability expectations measured in minutes per year.
IndustryGrid and asset telemetry, regulatory reporting, and operational systems with no acceptable downtime window.
We do not resell cloud capacity, licences or infrastructure, and we hold no provider commissions. A recommendation to consolidate, to stay on-premises or to move a workload back costs us nothing to give.
The target architecture is costed at projected volume before it is built, including the line items that are usually missed.
Cloud architecture expertise is needed intensively and intermittently. Engaging it hourly avoids a significant fixed cost for a need that is not continuous.
Every engagement has a named architect who owns the technical outcome and remains the point of contact for its duration.
Written artefacts you can act on without us: a workload disposition assessment, a target architecture with its cost model, a landing zone design as infrastructure as code, a dependency-sequenced migration plan with rollback positions, and decision records explaining why each significant choice was made.
It depends per workload, and the answer is frequently different across one estate. Lift-and-shift is defensible when there is a hard deadline such as a data centre exit, or when the workload is a candidate for retirement anyway. It is a poor default, because it preserves the original architecture and adds a rental cost, and the elasticity that justified the move stays out of reach.
We assess disposition per workload rather than applying one strategy across the estate.
In this order: allocation, architecture, commitments, rightsizing.
Allocation comes first because cost that cannot be attributed to a team or product cannot be managed. Architecture comes next because the largest savings are usually structural — egress, cross-zone traffic, storage class, and non-production environments running around the clock. Commitment strategy and rightsizing come last; they are the most visible levers and the smallest.
Whichever fits the constraints. Data residency, existing skills, licensing position, specific managed-service requirements and commercial terms usually decide it, and those differ per organisation.
We do not resell cloud capacity and hold no provider commissions, so the recommendation is independent counsel rather than a sales channel.
Deliberate multi-cloud can be, for regulatory requirements, genuine concentration risk, or a capability available on only one platform. Accidental multi-cloud rarely is: it carries the full operational cost of several platforms without the resilience benefit that would justify it.
Portability also has an ongoing cost that is paid whether or not it is ever exercised. We make the position explicit either way.
It is the account structure, network, identity, logging and guardrails that workloads are deployed into. It matters because it is unusually expensive to change later: an account boundary that does not match the security or billing boundary is re-platformed rather than reconfigured, and by then workloads depend on it.
It depends on estate size, data gravity and how much of the integration is documented. A single application is materially shorter than a data centre exit.
Rather than quote a duration we cannot stand behind, the readiness assessment produces a wave plan with dependencies, so the timeline follows from the estate rather than from an assumption.
Usually your team executes and we provide architecture, sequencing and design review. This is deliberate: the team that runs the platform afterwards should be the team that built it. Where you need additional delivery capacity, we scope that separately and honestly.
Yes, as architecture. We design identity, network boundaries, encryption and key management, and express controls as configuration so evidence is generated by operation rather than assembled before an audit.
We describe practices, not credentials. We do not represent NG&NR as holding certifications it has not been awarded, and we will not imply a certification status we cannot evidence.
Then we say so. Latency-bound systems, hardware dependencies, residency obligations and equipment with depreciation remaining are all legitimate reasons to stay. Hybrid is frequently the correct end state rather than a transitional one, and because we do not resell cloud capacity, recommending against a migration costs us nothing.
Cloud consulting is enterprise architecture applied to a specific platform decision. Where an engagement spans the wider estate — how capabilities are distributed, where systems should live, how the portfolio evolves — that is enterprise architecture consulting, and the two are frequently sold as one engagement.
Pricing depends on the work and the seniority required. We offer one-time consultations and ongoing support through subscription plans. Pricing is transparent and includes GST, with no hidden charges. The first consultation is free.
Request a free cloud assessment
Start with a free consultation: an overview of your estate, a review of the current architecture, and an honest assessment of what would actually help — including whether a migration is the right move at all.
No cost, no obligation. Pricing is transparent and includes GST.