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Businesses use public cloud platforms to update legacy infrastructure and applications, access managed services, and adjust capacity as demand changes. The move can also reshape how teams operate and develop products. But cloud adoption does not automatically cut costs or improve performance: the case depends on each workload, the cost of transition, licensing, security needs, and the organization’s ability to manage its new environment.
Why are businesses moving IT infrastructure to public cloud?
For many organizations, the goal is not simply to move servers out of a building. It is to address a specific constraint: aging infrastructure, applications that are difficult to change, limited capacity to support changing demand, or the effort required to maintain the underlying platforms.
Cloud services can give teams access to managed infrastructure and platform services, and let them provision or adjust capacity as needs change. Depending on the workload and architecture, that may reduce the burden of operating some underlying components or make it easier to deliver changes. Those results require suitable designs and operating practices; renting cloud capacity alone does not modernize an application.
AWS describes cloud adoption in terms of several possible transformations: modernizing technology, digitizing or automating processes, changing organizational operating models, and developing new products or revenue models. These are potential outcomes, not automatic effects of migration. A business should connect each proposed move to a clear operational or product goal.
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What should a cloud business case measure?
Compare the current environment with a defined future architecture and expected usage, rather than comparing an on-premises invoice with a cloud price estimate alone. Microsoft’s Azure Migrate business-case guidance, for example, considers total cost of ownership (TCO), year-over-year cash flow, workload readiness, utilization, support status, and modeling assumptions. Its output is an estimate based on discovered information and assumptions, not a guarantee of savings.
Account for both ongoing costs and the work required to reach the target state. AWS guidance identifies cost categories such as:
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- Discovery, planning, program setup, and staff training.
- Cloud foundation or “landing zone” setup, including security and operations controls.
- Application migration, modernization, connectivity, and data transfer.
- Cloud usage during migration, including periods when old and new environments run in parallel.
- Decommissioning, possible stranded assets, and licensing changes tied to the deployment model.
Usage-based billing can align spending with demand, but it does not ensure lower spending. Overprovisioning, unexpected consumption, data-transfer charges, licensing terms, and temporary overlap between environments can change the result. Model low, expected, and high cases using the organization’s own usage and contract data, and assign responsibility for reviewing actual costs after migration.
Microsoft’s and AWS’s cost-planning guidance supports comparing TCO, cash flow, and assumptions. The right level of detail depends on the size of the portfolio and how sensitive the decision is to those assumptions; possible measures include net present value, return on investment, and payback period. Verify licensing against actual contracts rather than assuming existing terms carry over unchanged.
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Which workloads should move, and how?
Workloads differ in their dependencies, business value, technical condition, and tolerance for change. An assessment may point to infrastructure as a service (IaaS) for a relatively direct move, or to a managed platform or other target when the application is suitable for modernization. A lift-and-shift move can address an immediate infrastructure constraint, but it does not by itself remove technical debt or make an application cloud-native.
| Approach | What changes | When to consider it |
|---|---|---|
| Rehost (lift and shift) | Move the workload with relatively limited architectural change. | When a direct move is a practical first step and the workload can run in the target environment. |
| Relocate | Move a workload or environment with limited application change. | When the target arrangement supports the workload and its dependencies. |
| Replatform | Make selected changes, potentially using a managed platform service. | When the workload can benefit from changing some underlying platform operations without a full redesign. |
| Refactor | Make more substantial application changes. | When the expected business value justifies the added engineering and migration effort. |
| Repurchase | Replace an existing application with another product or service. | When replacement fits the business need better than moving or modifying the current application. |
| Retire or retain | Decommission an unnecessary workload, or keep one in its current environment. | When there is no sound reason to migrate every application. |
These are workload strategies described in AWS guidance, not a ranking of platforms. Microsoft’s Azure Migrate assessments also distinguish options such as a PaaS-preferred target, an all-IaaS scenario, and Azure VMware Solution. A target recommendation is only as useful as the discovery data and assumptions behind it.
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Before choosing an approach, assess workload fit and dependencies, engineering effort, operating responsibility, performance and resilience needs, security and compliance obligations, licensing, expected running costs, reversibility, and the business value of changing the application. A complex or highly regulated workload may have different constraints from a straightforward service; do not assume a single migration pattern is right for the whole estate.
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Good planning is iterative: build an inventory, make workload-level decisions, migrate in controlled waves, then revise the roadmap using observed results. AWS portfolio guidance emphasizes inventory, dependencies, prioritization, target architecture, wave planning, and ongoing assessment. Microsoft likewise recommends discovery before preparing a business case and notes that utilization information improves assessment recommendations.
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- Discover the estate. Record applications, infrastructure, utilization, software versions, support status, and dependencies. Identify what each workload does and what relies on it.
- Set priorities with business owners. Weigh business value, readiness, risk, and migration dependencies. Ask of each application: “What is preventing this application from moving to the cloud now?” AWS Prescriptive Guidance uses that question as a planning prompt; an answer may show that migration is not yet appropriate.
- Choose a target and migration approach per workload. Document why the selected approach fits, including the intended architecture and who will operate its components.
- Build the cost case and record assumptions. Include transition, ongoing, overlap, and decommissioning costs, and model how different usage patterns could affect the result.
- Prepare foundations and the migration waves. Put security and operations controls, skills, connectivity, and continuity requirements in place before moving production workloads.
- Test, cut over, and validate. Confirm that the workload and its dependencies operate as intended before retiring old services. Keep continuity needs in view during the transition.
- Review actual outcomes. Compare spend, reliability, and business results with the baseline, then optimize workloads and update the roadmap.
What outcomes do published cloud-migration figures actually show?
Vendor benchmarks can illustrate reported results, but they are not forecasts for every adopter. AWS’s Cloud Value Benchmarking page reports that migrations from on-premises to AWS were associated with a 27% reduction in cost per user, 58% more virtual machines managed per administrator, 57% less downtime, and 34% fewer security events. The page does not provide enough methodological detail to establish how directly those figures apply to a particular organization.
The same AWS benchmarking reports a 37% reduction in time to market for new features and applications, a 342% increase in code deployment frequency, and a 38% reduction in time to deploy new code. These figures are AWS-reported results, not general expectations for businesses moving to any public cloud.
AWS also reports that business agility accounted for 47% of measured benefits—and more than five times the benefits attributed to infrastructure cost reduction—in an IDC 2018 survey of AWS customers. AWS notes that agility is challenging to predict. Treat that finding as a report about that survey’s AWS customers, not proof that agility will outweigh infrastructure savings in another company’s case.
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