Cloud strategy is where expensive mistakes are either avoided or locked in. We assess your workloads, operating model, compliance requirements, and growth plans, then turn that into a practical roadmap covering landing zones, provider fit, governance, migration sequencing, and modernization priorities.
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Most cloud initiatives stall not because of technology — but because the strategy was never defined clearly enough to execute on.
of organizations find cloud compliance too difficult to manage without defined governance and tooling in place.
IBM Global Cloud Study
of organizations cite a lack of cloud talent and capabilities as a major roadblock to successful cloud adoption.
McKinsey & Company
of organizations lack a formal strategy to align cloud and AI initiatives with measurable business outcomes.
PwC Cloud & Digital Survey
These are not edge cases — they are the default state for most teams without a clear cloud strategy. Getting the foundation right first saves months of rework and cost later.
Talk to us about your cloud strategyNot all of these will be in scope for every engagement — we scope to what your situation needs.
Turn the engineering rationale for cloud into something leadership can act on — cost models, risk exposure, estimated ROI, and a delivery sequence that replaces internal conviction with a document they can actually approve.
Survey every application, team, and integration point before any migration sequence is committed — because programmes that skip this step spend their first three sprints correcting assumptions rather than moving workloads.
Set the account model, network baseline, identity design, and shared platform services before the first workload touches the cloud — so the landing zone is already operational rather than still being figured out ten deployments in.
Put tagging taxonomy, cost ownership, policy guardrails, and team accountability in place as delivery foundations — not as remediation tasks that appear in the final sprint when the programme is already running behind.
Build IAM boundaries, blast radius controls, encryption standards, and resilience patterns into the original design — retrofitting all of this into a live environment is slower, costlier, and riskier than just doing it right from the start.
Embed compute sizing decisions, commitment strategy, data transfer costs, and anomaly detection into architecture choices from day one — so the first invoice confirms the model instead of surprising the team.
Assign each workload a migration pattern — rehost, re-platform, refactor, or retire — with a documented rationale for each call, then sequence delivery in an order that keeps production running while the transformation plays out.
Benchmark live cloud environments against reliability, security, cost, and performance criteria to produce an improvement backlog ordered by actual business impact — not the severity scores that tool dashboards apply without understanding your context.
Phase 1 of 6
Before any architecture decision is made, we get the full picture. That means inventorying every application, mapping infrastructure dependencies, reviewing team ownership structures, and surfacing compliance constraints that would otherwise create blockers mid-programme.
Deliverables: Application portfolio register, infrastructure topology map, team ownership matrix, compliance constraints log, initial risk register
With real data from discovery, we design the environment your workloads actually need — not a default template. This covers cloud account structure, network topology, identity and access boundaries, and the shared services layer. Every decision is traceable to a specific workload requirement.
Deliverables: Target architecture document, account and VPC topology, IAM design, provider selection rationale with cost comparison
We define the cloud foundation before anything migrates. That means accounts, guardrails, centralised logging, tagging taxonomy, and cost allocation boundaries all in place before the first workload arrives. You should never be retrofitting governance after go-live.
Deliverables: Landing zone specification, policy-as-code guardrails, tagging and cost framework, environment onboarding runbook
Each workload gets a migration strategy: rehost, re-platform, refactor, or retire. We sequence waves to minimise blast radius and maintain production uptime — prioritising quick wins that build internal confidence while protecting the systems your business depends on.
Deliverables: Workload classification register, wave-by-wave migration plan with timelines, rollback and contingency procedures
High-risk assumptions get a targeted proof-of-concept before full execution begins. Security posture is reviewed against the target architecture. Cost models are reconciled against real provider pricing. Only when assumptions are confirmed do we commit the full delivery schedule.
Deliverables: PoC findings report, security posture review, validated cost model, performance baseline against SLO targets
The engagement closes with a 12-month delivery roadmap, team-level ownership assignments, and a FinOps operating model for day-two operations. We document every architecture decision taken during the programme so your team has the full reasoning — not just the output.
Deliverables: 12-month delivery roadmap with owners, FinOps operating model, architecture decision log, handoff workshop
Bad sequencing, missing governance, and no cost model turn ambitious cloud programmes into expensive fire drills. We give you the architecture, the roadmap, and the controls — so your team executes with confidence instead of improvising under pressure.
Amazon Web Services
Microsoft Azure
Google Cloud
InfraShift helps CTOs, cloud architects, and platform leaders turn cloud ambition into a buildable operating plan. The work covers landing zones, provider selection, workload sequencing, security controls, FinOps guardrails, and the team model needed to operate AWS, Azure, or GCP without drift.
Many cloud programs start with a provider decision before the application estate, compliance boundaries, network dependencies, and operating model are understood. That usually creates rework during migration, weak tagging, fragmented identity, and architecture decisions that are hard to explain to finance or risk teams.
We run structured discovery across workloads, business priorities, compliance needs, current runbooks, incident history, and cost patterns. The output is a target architecture, migration sequence, governance model, platform backlog, and executive roadmap that engineering teams can execute in phases.
Leadership gets a defensible cloud plan, engineering gets a practical backlog, and platform teams get standards for identity, networking, observability, cost ownership, and environment provisioning before production workloads move.
For teams in India, UAE, and Saudi Arabia, strategy work includes region choice, data residency assumptions, support timezone coverage, and hiring constraints. We often help India-based engineering teams build Azure consulting and Kubernetes consulting roadmaps for GCC customers where compliance evidence and predictable delivery windows matter.
Cloud strategy consulting defines the architecture, governance, cost model, workload sequence, and operating model for cloud adoption before implementation starts.
Run it before migration, modernization, or major platform investment, especially when several teams disagree on provider choice, risk, timeline, or ownership.
You get a concrete architecture recommendation, migration sequencing, risk register, cost model, and a delivery roadmap your team can execute.
Yes. We compare providers against your workloads, compliance needs, team skills, and cost profile instead of pushing a default answer.
That is usually the right time to do it. Strategy work is meant to reduce expensive mistakes before build or migration begins.
Most engagements run a few weeks, depending on the number of workloads, stakeholders, and depth of architecture validation required.
Yes. We run working sessions with engineering and leadership so the final plan reflects operational reality and has buy-in.
Yes. We can stay involved for migration, platform engineering, or phased execution after the strategy and roadmap are signed off.
A cross-section of delivery outcomes across cloud migration, platform engineering, DevOps operations, and cost control work.
