09.03 · Foundations

Deployment Models

Public, private, hybrid, community — four ways to decide who shares the underlying infrastructure with you.

Service model (IaaS / PaaS / SaaS / FaaS) tells you how much of the stack the provider runs. Deployment model tells you who you share the underlying infrastructure with. These are independent choices — you can run IaaS in a public cloud, in a private cloud, in a hybrid arrangement, or in a community cloud. Almost every real architecture picks one of each.

NIST SP 800-145 defines four deployment models. Twenty years in, the boundaries between them blur in practice, but the four categories still describe how organizations actually choose hosting. Most enterprises run a mix — not because they planned to, but because different workloads have different requirements and the answer is rarely "all in one place."

The four models

Public cloud

Shared infrastructure, rented capacity

Infrastructure owned and operated by the cloud provider, available to anyone with a credit card. Your VM may share a physical host with hundreds of other customers' VMs. You pay for what you use; you don't pay for what you don't.

Owner
Provider
Tenants
Many organizations, multi-tenant by design
Cost
Operational (OpEx), per-hour / per-request
Scale
Effectively unlimited
ExamplesAWS (commercial regions), Azure, Google Cloud, Oracle Cloud Infrastructure, DigitalOcean, Linode
Private cloud

Dedicated infrastructure for one tenant

Cloud-style infrastructure (self-service provisioning, elastic scaling, metered billing) but the underlying hardware is yours alone. Can live in your data center or be hosted by a provider on dedicated equipment.

Owner
Customer, or provider on customer-only hardware
Tenants
One organization
Cost
Capital (CapEx) + operating; pays even at idle
Scale
Limited by what you bought / leased
ExamplesVMware Cloud Foundation, OpenStack, AWS Outposts, Azure Stack Hub, Google Cloud Anthos on bare metal
Hybrid cloud

Public + private, orchestrated together

A composition of two or more distinct cloud infrastructures (public, private, or both) that remain unique entities but are bound together with standardized technology enabling data and application portability. The most common real-world architecture.

Owner
Mixed
Tenants
Yours on private + multi-tenant on public
Cost
Both models combined; complex to model
Scale
Burst from private to public on demand
ExamplesBank that keeps customer data on-prem but runs marketing on AWS · Hospital with EHR private + analytics in Azure · Manufacturer using Outposts + main AWS
Community cloud

Shared by orgs with the same concerns

Infrastructure provisioned for exclusive use by a specific community of consumers from organizations with shared concerns (mission, security requirements, policy, compliance). May be owned by one or more of the orgs, by a third party, or some combination.

Owner
Member orgs, third party, or combination
Tenants
Limited group sharing common requirements
Cost
Shared among community members
Scale
Sized for the community
ExamplesAWS GovCloud / Azure Government (US federal agencies) · Microsoft 365 GCC High (DoD) · Research and Education clouds · Healthcare HIPAA-scoped clouds

Trade-offs at a glance

No deployment model wins on every axis. The matrix below shows which model is strongest on each common decision factor. Reading it down a column tells you the personality of one model; reading it across a row tells you who wins on that specific trade-off.

Deployment model trade-offs · high = strongest
Decision factorPublicPrivateHybridCommunity
Up-front costLowestHighMixedShared
Long-term cost at huge steady scaleMidLowestMidMid
Scalability ceilingEffectively noneWhat you boughtBurst to publicSized for community
Control over hardware & configProvider'sTotalWhere you put itCommunity-defined
Data residency / sovereigntyProvider regionYour data centerSensitive data privateGuaranteed by SLA
Compliance fit (FedRAMP High, IL5, etc.)Standard regions: noCustomizableMixedBuilt for it
Time to deploy a new serviceMinutesWeeksDepends on sideMember onboarding
Maintenance burdenProvider'sYoursSplitShared / outsourced
Vendor lock-inHighNone / lowReducedTo community

Pick the right one for a scenario

Click each scenario to see which deployment model fits best and why. The right answer is rarely "public cloud always" — the constraints attached to the workload almost always pick the model for you.

Scenario picker · click a row
Scenario A
A three-person startup needs to launch a SaaS product in 90 days. No budget for hardware. They want to scale instantly if a launch goes viral.
Scenario B
A defense contractor processes classified information under contract clauses that prohibit storage on shared infrastructure or in any provider-controlled location.
Scenario C
A regional bank wants modern customer-facing apps and analytics in the cloud, but regulators require core deposit data to remain inside the bank's own facilities.
Scenario D
A U.S. federal agency needs FedRAMP High and IL5-authorized infrastructure that's certified, audited, and shared only with other federal customers.
Scenario E
A manufacturer runs latency-sensitive control systems on the factory floor (can't go offline if the WAN drops) plus enterprise apps that benefit from cloud scale.
Scenario F
An e-commerce site sees 80% of annual traffic in November — December. Running peak capacity year-round would waste money for ten months.
Pick a scenario to see the recommended deployment model.

Hybrid in practice

In real architectures, "hybrid" is the default. Almost no enterprise of any size runs 100% public or 100% private. The questions worth answering up front:

The point

Deployment model is a question about who shares the underlying hardware with you, and it is independent of how much of the stack the provider runs. You can have private-cloud IaaS, public-cloud SaaS, hybrid PaaS, and community FaaS — the two dimensions multiply.

Almost every real organization ends up hybrid: public cloud for elasticity and most new workloads, private cloud or on-prem for workloads with hard data-residency or latency constraints, community cloud for regulated work, all glued together with identity, network, and management planes. The skill isn't picking one model; it's knowing which workloads belong on which side of the line.

References

Formatted in APA 7. Alphabetized by first author's last name.

  1. Amazon Web Services. (n.d.). AWS GovCloud (US). https://aws.amazon.com/govcloud-us/
  2. Mell, P., & Grance, T. (2011). The NIST definition of cloud computing (NIST Special Publication No. 800-145). National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.800-145
  3. Microsoft. (n.d.). Azure Government documentation. Microsoft Learn. https://learn.microsoft.com/en-us/azure/azure-government/
  4. U.S. General Services Administration. (n.d.). FedRAMP marketplace. https://marketplace.fedramp.gov/