What Are Cloud Deployment Models?

Success in today’s data-driven business landscape means staying on top of a multitude of applications, resources, and services. Cloud computing gives enterprises the flexibility to adapt to the fluctuations of business and to operate more efficiently. But the overall effectiveness of the cloud for business depends on the underlying cloud deployment model.

So what is a cloud deployment model? These paradigms dictate where enterprise apps, workloads, and data reside—whether in the public cloud, a privately owned and managed data center, or, commonly, a combination of both.

Multiple factors come into play when creating a cloud deployment strategy—including cost, privacy, governance, geography, and service availability—and each should be weighed carefully when choosing a deployment model for enterprise workloads and applications.

Types of Cloud Deployment Models

There are various types of cloud deployment models to choose from, each offering unique business advantages.

Public Cloud

In a public cloud model, a business rents compute, storage, and networking services from a cloud service provider such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform. These resources reside in the provider’s data centers and are delivered over the internet.

This approach offers several business benefits, including reduced hardware and IT management costs, faster time to market, the ability to scale infrastructure quickly as more resources are needed, and easy access to innovative technologies and services hosted by hyperscalers—large-scale cloud service providers—such as foundational models and data analysis tools.

Public cloud service models have a pay-as-you-go pricing structure, making them particularly well suited for running short-term workloads, including seasonal workloads, application development and testing, and ad hoc data processing.

Private Cloud

In a private cloud model, organizations supply their own resources. That means the business is typically responsible for owning and maintaining the hardware, software, and networking infrastructure. As such, it can involve a substantial initial outlay and ongoing managerial and operational costs.

That being said, running workloads in a private cloud can be more cost-effective than the pay-as-you-go pricing of the public cloud over the long term, according to some research, including the influential paper “The Cost of Cloud, a Trillion Dollar Paradox” from Andreessen Horowitz. Additionally, private cloud deployments can deliver a lower total cost of ownership (TCO) in the long run, as virtualization technologies allow resources to be better used, yielding more compute and storage on less physical hardware.

Other operational aspects also come into play. Some workloads are better suited for private cloud environments, including mission-critical applications that can’t afford downtime and legacy applications that are too difficult or risky to migrate. Plus, private cloud deployments can help keep sensitive data secure and ensure compliance with data sovereignty regulations, as the data is processed internally as opposed to in a faraway data center.

Hybrid Cloud

In practice, many enterprises use a mix of public and private clouds to meet the requirements of multifarious applications and achieve workload optimization. A hybrid cloud model gives businesses exposure to both public and private cloud resources, allowing them to designate which workloads run where, depending on which environment is most advantageous. The best of both worlds, this strategic approach gives businesses exacting control over critical applications and sensitive data in the private cloud, in addition to access to the scalability, up-front cost savings, and innovative tools and services of the public cloud.

Multicloud

A multicloud model infuses resources from various cloud service providers and can include private clouds as well. This strategy relies on software to manage and orchestrate resources across different providers, resulting in a flexible, cost-optimized cloud environment.

A multicloud approach can help businesses save money by dividing workloads between services with the best prices. For instance, businesses can store their data on one public cloud and run workloads on another where compute time is less costly. Relatedly, this helps avoid lock-in or dependency on a single cloud provider’s ecosystem.

In addition to cost optimizations, multicloud models are geographically diverse, giving businesses the agility to operate in distinct regions. Placing workloads on cloud infrastructure geographically close to end users can help improve performance and reduce latency. It can also help businesses navigate the patchwork of data regulations in different states and nations.

An added benefit of the multicloud model is business continuity. Should services go down in one environment, other available clouds can act as backup resources.

Community Cloud

A community cloud is a strategy that allows consortiums to access resources and services in a shared environment. For example, a group of banks or government agencies might form a community cloud that is designed to address security, regulatory, and legal requirements specific to their sector. Such models are often integrated with an organization’s own hybrid cloud infrastructure.

Choosing a Cloud Deployment Model

When devising a cloud strategy, it’s best to start with an audit of all your business’s workloads, along with their resource needs and dependencies, keeping in mind how these needs may shift over time. For instance, some workloads may begin in the public cloud but migrate to a private cloud later.

Rather than taking a one-size-fits-all approach, consider assigning a cloud deployment model to each workload on a case-by-case basis. A hybrid cloud approach may be necessary for optimal workload placement, as each application will have its own unique requirements.

Here are some guidelines for getting started.

Public clouds are often used for the following use cases:
 

• Scale up quickly and accelerate time to market.
• Run workloads over the short term.
• Manage up-front costs.
• Relieve demand on IT resources, including infrastructure and staff.
• Drive innovation by taking advantage of services like AI, big data, and development tools.
   

Private clouds are often used for the following use cases:
 

• Protect sensitive information, including intellectual property.
• Meet data sovereignty or compliance requirements.
• Ensure high availability and maximal uptime.
   

Hybrid clouds are often used for the following use cases:
 

• Adjust resource needs fluidly as business goals change.
• Run some workloads in the public cloud while retaining control of sensitive data and mission-critical applications.
• Optimize costs over the life of a workload.
   

Multiclouds are often used for the following use cases:
 

• Optimize costs by distributing workloads between service providers.
• Avoid vendor lock-in.
• Extend geographic footprint.
• Navigate the patchwork of multinational data regulations.
   

Community clouds are often used for the following use cases:
 

• Consolidate resources.
• Address industry-specific security and regulatory concerns.

Cloud Solutions

Having the right blend of cloud computing solutions, including hardware, software, and security features, is essential to getting the most out of an enterprise cloud deployment strategy. Here are some key ingredients to consider.

Data Center Processors

Server-grade processors, such as CPUs, GPUs, and FPGA configurable devices, are designed and optimized for demanding enterprise cloud computing workloads, including analytics, AI, and database workloads. They often contain technologies and extensions that can boost performance when running hypervisors and hybrid workloads within a hybrid cloud environment.

Cloud Tools

A variety of cloud tools are instrumental to cloud deployments and help businesses implement profitable cloud strategies. Cloud migration tools assist with moving workloads and applications to the cloud. Cloud management platforms, meanwhile, provide visibility and insights into cloud spending, resource allocation, and network traffic across multiple cloud environments. Specific tools for enhancing cost optimization and data governance are also available.

Cloud Security

Cloud security solutions help ensure that sensitive company data stays private and that business applications run without disruption. Confidential computing, for instance, keeps data encrypted while it is being processed on cloud infrastructure. Zero trust security prevents unauthorized access to data stored in the cloud. Hardware-based isolation technologies help keep applications secure while running in the cloud.

Compare Cloud Deployment Models

Moving workloads to the cloud ultimately helps businesses be more flexible, allowing them to refine their operations and strategies as priorities change and external factors evolve. The public cloud gives businesses the ability to scale and speed innovation, whereas the private cloud prioritizes control of data, infrastructure, and mission-critical workloads. Hybrid cloud approaches, including multiclouds and community clouds, yield the best of both worlds, bringing together private and public cloud resources into a single model so that workloads can run in their optimal location.