Cloud Workload Migration Services

Depends on workload count and complexity. A mid-market migration of 30–80 workloads is typically 8–16 weeks. Large enterprise migrations of 500+ workloads run 6–12 months. Discovery and planning are the first 4 weeks regardless.

Migration moves a workload to the cloud. Modernization changes the workload itself - refactoring to cloud-native services, breaking up monoliths, replacing legacy DBs. The 7Rs framework covers both: Rehost is pure migration; Refactor is modernization.

Depends on the workload architecture. Stateless apps can be migrated with near-zero downtime via blue/green cutover. Stateful systems with dependency chains have a planned cutover window we work to minimize. We tell you the expected window per workload during Discovery.

Yes. vSphere and VCF environments to VMware Cloud on AWS, Azure VMware Solution, and Google Cloud VMware Engine. We also identify replatform candidates where moving off VMware to native cloud services makes more economic sense long-term.

We evaluate each workload on time pressure, cloud-native fit, expected lifetime, and TCO. Rehost wins when there's a hard cutover deadline. Replatform is the default for ~60% of workloads. Refactor is reserved for workloads where the cloud-native return justifies the rewrite.

Discovery and planning are fixed-fee. Execution is typically a blend of fixed-scope waves plus T&M for workloads where scope is harder to lock in. The pre-cutover TCO model includes our fees so you see total cost of the migration plus the projected cloud bill.

Three things. (1) TCO modeling per workload before cutover, so the bill is no surprise. (2) FOCUS-aligned tagging set up at day-1 cutover, not as a year-2 cleanup. (3) Fintropy baseline scans before and after, plus a 90-day post-cutover cost review built into the engagement.

Yes. We design target architectures that maintain in-scope boundary controls, plan cutovers to preserve audit trails, and coordinate with your compliance team on attestation. Some workloads end up classified as Retain rather than migrated - and we'll tell you when that's the right call.

Workload migration is the process of moving an application, service, or data system from one computing environment to another - typically from on-premise infrastructure to a cloud platform (AWS, Azure, or GCP), between clouds, or from a legacy environment to a modernised stack. It covers the full lifecycle: discovery, dependency mapping, TCO modelling, cutover execution, and post-migration validation.

Enterprise workload migration is the structured migration of large-scale, business-critical application portfolios - typically 50 or more workloads with complex dependencies, compliance requirements, and multi-team coordination. It differs from simple lift-and-shift in that it requires formal 7Rs classification per workload, wave-based cutover planning, pre-migration TCO modelling, and FinOps governance from day one to prevent the post-migration cost spikes that affect most large-scale programmes.

Cloud modernization reduces IT cost through three levers: (1) replacing capex hardware refresh cycles with opex cloud subscription, (2) eliminating on-prem maintenance/support contracts on legacy systems, (3) enabling demand-elastic infrastructure that scales to actual use vs sized for peak. Realistic outcome: 20–40% TCO reduction on modernized workloads over 3 years, depending on starting architecture. The savings are larger when refactoring is part of the modernization, not just rehosting.

Per-wave fixed-scope migrations typically range $25K–$250K depending on workload complexity, dependencies, and target architecture (rehost vs refactor). A 200-server datacenter migration in 4–8 waves typically runs $200K–$800K all-in including discovery, runbook authoring, cutover support, and post-cutover stabilization. We price waves individually after a 1-week discovery so scope and cost are locked before execution begins.

Realistic timeline: 6–12 months end-to-end for a 200-server estate. Breakdown: 4–6 weeks discovery & wave planning, 4–8 waves at 4–6 weeks each, 4–8 weeks of post-cutover stabilization. The variable is application complexity, not server count - a heterogeneous estate with legacy middleware extends; a homogeneous VMware estate with modern apps compresses.