Migration is not just moving servers. It is moving applications, data, integrations, and operational responsibility without losing control. We plan the migration path, choose the right pattern per workload, stage the cutover carefully, and stay through hypercare until the new environment proves itself under real traffic.
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Migration programs usually do not break because teams picked the wrong cloud. They break because dependencies were underestimated, operational ownership stayed unclear, and risk planning came too late.
of organizations struggle to keep cloud compliance under control when migration work moves faster than governance and operational guardrails.
IBM Global Cloud Study
of organizations say limited cloud capability inside the team slows execution and turns migration planning into a delivery bottleneck.
McKinsey & Company
of cloud migrations run over budget, and 38% miss the timeline once real dependency chains and cutover constraints show up in delivery.
McKinsey & Company
The hard part of migration is not copying workloads. It is protecting uptime, sequencing dependencies correctly, and making sure your team is ready to operate the new environment on day one.
Talk to us about your migration planMost migration problems show up in the gaps — between assessment and execution, between security planning and delivery, between cutover and what the team is left operating. These are the capabilities we bring to close those gaps.
Document every in-scope application, its dependency chain, its owners, and its operational constraints before the migration plan is finalized — plans built on estate assumptions rather than verified facts rarely survive the second wave.
Choose landing zones, network topology, platform services, and wave sequencing before workloads start moving — so the team runs a deliberate execution plan instead of making architecture calls mid-cutover under time pressure.
Assign each application a migration pattern — rehost, re-platform, refactor, or retire — with a documented rationale for each decision, then build a delivery order that works through the portfolio without stalling on modernisation debates mid-programme.
Stage compute, storage, and network moves in dependency order with defined entry criteria, validation gates between waves, and a rollback workflow the team has tested — not just documented.
Design database cutovers around actual downtime tolerance, not best-case assumptions — with replication lag monitoring, pre-cutover validation, and a reconciliation step that confirms data integrity before application traffic follows.
Build the connectivity model, identity trust design, and operational runbooks needed to run on-premises and cloud in parallel for as long as your constraints require — without treating the hybrid period as a temporary exception to be ignored until it breaks.
Bring IAM design, audit logging requirements, encryption standards, and regulatory controls into the migration workstream from the first sprint so security is a delivery input — not a late-stage blocker that pushes your go-live date.
Deploy the provisioning pipelines, configuration standards, observability stack, and day-two runbooks alongside the cloud workloads — so the operating model is functional and tested before the last system leaves on-premises.
Wire cost ownership into the architecture from day one — workload-level tagging, budget thresholds, anomaly detection, and a commitment model staged to activate when spend patterns make reservations genuinely worthwhile.
Use the migration window to test and validate recovery objectives properly — restore backups, run region failover scenarios, measure actual RTO against requirements, and write recovery runbooks before a production incident reveals what was never checked.
Spend the first 60 to 90 days post-cutover tuning performance, tightening alerting, rightsizing overprovisioned resources, and correcting the shortcuts that were made under programme time pressure — before they calcify into permanent technical debt.
Execute structured and unstructured data moves with staged transfers, automated validation logic, and reconciliation reports that give data owners confirmed accuracy — not just a sync job that finished without an error code.
The difference between a migration that goes to plan and one that doesn't usually shows up in the first two weeks — not the last.
Your migration sequence is built from verified dependency maps, team capacity constraints, and risk tolerance — not a vendor playbook applied without reading what you're running.
App transformation decisions are made at the workload level with documented justification — not applied uniformly because a framework calls for it or a partner benefits from the statement of work.
IAM design, audit logging, policy guardrails, and landing zone controls ship before the first workload moves — so security is an input to the programme, not a remediation sprint at the end.
Spend modelling starts before the first workload moves. Tagging taxonomy, workload-level ownership, and anomaly detection are operational before the programme completes — not left as post-migration housekeeping.
Phase 1 of 6
We begin by building a complete picture of everything in scope — applications, infrastructure, integrations, data flows, and the teams responsible for each. Dependency mapping is done at the network and application layer so wave sequencing reflects actual coupling, not assumptions. Gaps found here cost days; gaps found mid-migration cost weeks.
Deliverables: Application and infrastructure discovery report, full dependency map, ownership matrix, migration-pattern classification per workload
With discovery complete, we design the cloud environment your workloads are moving into — account structure, network topology, identity boundaries, security baselines, and shared services. The landing zone is built and validated before the first production workload moves. Governance, tagging, and cost allocation are wired in from this phase, not after go-live.
Deliverables: Target architecture document, landing zone build, IAM and network design, tagging and cost allocation framework, environment onboarding runbook
Each workload is assigned a migration pattern — rehost, re-platform, refactor, or retire — along with a documented rationale. Waves are sequenced by risk tolerance, dependency chains, and business criticality. We build buffer time in between waves deliberately so validation does not get skipped under timeline pressure.
Deliverables: Workload classification register, wave plan with timelines, risk register with blast-radius analysis, rollback and contingency procedures per wave
Waves execute in order with defined entry and exit criteria at each stage. Validation happens before cutover, not as a cleanup task after. Database migrations are proven against downtime tolerances before application traffic moves. Security and compliance controls are checked against the target state before each wave closes.
Deliverables: Wave execution reports, validation checklists per workload, security posture confirmation, database integrity and reconciliation records
Cutovers follow a written runbook with rollback triggers and ownership clearly assigned. During and after go-live we maintain heightened monitoring coverage — not default alerting, but tuned thresholds aligned to how each workload behaves. Hypercare runs until the new environment has proven it can hold real production load across at least one full business cycle.
Deliverables: Cutover and rollback runbooks, go-live monitoring dashboard, hypercare schedule with escalation contacts, incident and resolution log
Once the environment is stable, we run a structured review — rightsizing oversized resources, tightening alert thresholds, reviewing cost attribution, and closing the gaps that accumulated under programme time pressure. The engagement closes with full documentation, architecture decision records, and a FinOps operating model your team can run without us.
Deliverables: Post-migration optimisation report, rightsizing recommendations, FinOps operating model, architecture decision log, team handover workshop
Amazon Web Services
Microsoft Azure
Google Cloud
InfraShift plans and executes cloud migrations for applications, databases, Kubernetes platforms, and integration-heavy environments. The focus is controlled cutover, rollback planning, dependency mapping, observability, security, and post-migration optimization.
Migration risk usually hides in undocumented dependencies, DNS changes, database replication lag, IAM differences, network paths, and monitoring gaps. Teams that move too quickly can land in the cloud with higher cost, weaker visibility, and production behavior they cannot explain.
We map application dependencies, classify workloads by migration pattern, build environment parity, define cutover and rollback checkpoints, and validate production readiness with monitoring, backup, access, and cost controls before traffic moves.
Teams move workloads with less downtime, fewer surprises, and a cleaner cloud foundation. After migration, the environment is ready for rightsizing, autoscaling, incident response, and platform ownership.
For Azure migration services in India, UAE, and Saudi Arabia, we account for business-hour cutovers, local compliance expectations, payment and ERP integrations, and cloud region choices such as Azure UAE North, Azure Central India, and Azure KSA North where applicable.
We reduce downtime with staged replication, rehearsed cutovers, traffic shifting, pre-approved rollback criteria, and observability checks before and after release.
Yes. We support AWS to Azure migration, Azure landing zones, database moves, identity changes, and post-migration FinOps reviews.
Yes. We support on-prem to cloud, cloud to cloud, and hybrid migration programs with staged cutovers and rollback planning.
We map dependencies, group workloads into waves, define validation gates, and prepare rollback triggers before production cutover.
Yes, but the method depends on data size, downtime tolerance, replication options, and application coupling. We plan that explicitly.
Where the workload allows it, yes. When zero downtime is not realistic, we design the smallest safe maintenance window possible.
We usually stay through hypercare, monitoring, and incident support until the new environment has proven itself under real traffic.
Yes. Migration work usually goes faster when we operate as an extension of your engineering team instead of in parallel to it.
Tell us what you're moving, where it's going, and what keeps you up at night — we'll scope an approach that fits your risk tolerance and timeline.
Start the conversationA cross-section of delivery outcomes across cloud migration, platform engineering, DevOps operations, and cost control work.
