There is no single best cloud model for every business. Choose separately for each workload, based on its purpose, compliance and data-location requirements, existing dependencies, availability needs, total operating cost, and your team’s ability to run it. Use the least complicated arrangement that satisfies those requirements; add environments or providers only when they solve a defined business need.
First, separate deployment models from service models
A deployment model describes where cloud infrastructure is provisioned and who it is for. A service model describes what you consume and how much of the technology stack you manage. Public, private, community, and hybrid are deployment models; software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS) are service models. They are different choices, not competing labels. The U.S. General Services Administration’s Cloud Information Center presents NIST’s cloud framework as having four deployment models and three service models.
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What each deployment model means
Public cloud
Infrastructure is provisioned for general use and operated at a provider’s premises. It can spare a business from owning and maintaining its own datacenter, but it does not transfer responsibility for its data, identities, or configuration to the provider.
Private cloud
Infrastructure is provisioned for the exclusive use of one organization. It may be on the organization’s premises or elsewhere, and it may be operated by the organization, a third party, or both. Exclusive use alone does not establish that a private cloud is more secure or less expensive.
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Community cloud
Infrastructure is provisioned for organizations that share concerns such as mission, security requirements, policy, or compliance. It is worth considering only if the arrangement meets the participating organizations’ procurement and operating needs.
Hybrid cloud
Distinct environments are connected so data or applications can move between them. A common arrangement connects on-premises systems with public-cloud services. That connection can address a real dependency or workload need, but requires integration and cross-environment operations.
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Multicloud and hybrid multicloud
Multicloud means running significant workloads across multiple cloud providers. It may be planned, or arise when teams select providers independently. Hybrid multicloud combines hybrid and multicloud arrangements; the categories can overlap. More providers are not automatically better, so identify the concrete reason for each one and establish decision ownership.
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Record the answers for each workload rather than selecting one model for the entire business. Google Cloud’s deployment archetype guidance frames deployment decisions around availability, cost, performance, and operational efficiency.
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- Business outcome: What capability or measurable result does the workload support? A deployment should serve an identifiable business purpose.
- Compliance and data location: Identify applicable legal, regulatory, contractual, sovereignty, and internal controls. Establish which locations and processing arrangements are acceptable for both stored data and the workload’s operation.
- Dependencies: Note on-premises hardware, latency-sensitive systems, specialized software, and data that would be costly or difficult to move. These constraints can make a connected or on-premises component necessary.
- Availability and performance: Specify outage tolerance, recovery objectives, required geography, and response time. These are workload requirements to validate against the actual architecture, not assumptions to make from a model’s name.
- Full operating cost: Include migration, connectivity, support, staffing, resilience, security operations, and ongoing usage over the period that matters to the business. No model is a universal cost winner; provider prices and workload economics need to be assessed for the specific case.
- Operating capability: Name who governs accounts, identity, networking, security, monitoring, incident response, and workload operations. Microsoft recommends defining an operating model and documenting responsibilities; its operating-model guidance distinguishes centralized, shared-management, and decentralized approaches.
Match the arrangement to the requirement
| Approach | Consider it when | Check before committing |
|---|---|---|
| Public cloud with one provider | The provider’s services, regions, controls, and economics meet the workload’s requirements, and the business can manage its security and operations responsibilities. | Confirm the specific service and location meet requirements; document customer responsibilities for data, identities, and configuration. |
| Private cloud | A documented requirement calls for exclusive-use infrastructure or particular control characteristics, and the organization can fund and operate that environment. | Compare total operating cost and operating capability; do not assume private means inherently more secure or cheaper. |
| Hybrid | Systems must remain on premises, or the workload has a requirement for a connected split across environments. | Plan for integration, data movement, latency, recovery, and operations across both environments. |
| Multicloud | A specific workload has a concrete reason to use more than one provider. | Assign governance and ownership so provider choices do not fragment across teams without an explicit business reason. |
| Community cloud | Organizations share mission, security, policy, or compliance concerns that the arrangement addresses. | Verify that procurement, operating responsibilities, and the actual controls suit all participants. |
Use the same workload-specific criteria to compare candidates: compliance and data residency, availability and recovery, performance and latency, total cost over the relevant period, migration effort, dependencies, operational complexity, security responsibilities, and available staff expertise. A short written comparison can expose a poor fit before procurement.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Account for cloud operating and security responsibilities
Choosing where infrastructure runs does not settle who manages each technical layer. Microsoft’s shared-responsibility guidance says customers own their data and identities across IaaS, PaaS, and SaaS. Responsibility for applications, network controls, operating systems, and infrastructure shifts with the service type.
A concrete IaaS example is Amazon EC2: AWS says customers manage the guest operating system, patches, installed applications, and security-group configuration. With more abstracted services, AWS operates more of the underlying layer, while customers still manage data, classification, encryption choices, and access permissions. See AWS’s shared responsibility model.
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Do not treat cloud-first as a rule without exceptions
For a new workload, public cloud can be a sensible starting point when it meets documented requirements. But a strict cloud-first policy can add complexity, redundancy, or performance costs when it forces a workload into an unsuitable design. Google Cloud’s hybrid and multicloud patterns guidance notes that regulation or data privacy rules can constrain where some workloads run. Keep a workload on premises or use a different arrangement when its requirements justify that choice; record the reason and review it as dependencies and requirements change.
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