Types of Cloud Computing: Deployment Models, Service Models & Examples

From streaming movies on Netflix to storing photos in Google Drive, cloud computing has quietly become part of everyday life.

But behind these familiar services is a much bigger system that helps businesses store data, run applications, manage servers, and access computing power without owning all the hardware themselves.

As cloud technology has evolved, it has also developed into different models designed for different needs. This is where understanding the types of cloud computing becomes important. 

Some cloud environments are built for multiple users, while others are dedicated to a single organisation. Similarly, some cloud services give businesses complete control over infrastructure, while others provide ready-to-use software.

In this guide, we’ll break down the major types of cloud computing, their deployment and service models, real-world examples, advantages and limitations, and emerging approaches shaping cloud technology in 2026, all in simple language so even beginners can understand how they work and where they fit.

What Does Cloud Computing Stand For?

Unlike terms such as CPU (Central Processing Unit) or RAM (Random Access Memory), Cloud Computing is not an acronym. The word "cloud" is simply a symbolic representation of the internet, while "computing" refers to the use of computing resources such as servers, storage, databases, networking, and software.

Cloud computing allows users and organisations to access computing resources over the internet instead of purchasing and maintaining physical hardware.

In simple words, rather than owning expensive servers, you rent computing power whenever you need it.

Understanding Cloud Computing with a Real-Life Example

Think about Google Drive.

Years ago, people stored documents only on their personal computers or USB drives. If the device failed, their files could be lost forever.

Today, when you upload a document to Google Drive, it is stored on Google's cloud servers instead of your local computer. You can access it anytime from your phone, laptop, or tablet, as long as you have an internet connection.

Similarly:

• Netflix stores movies in the cloud.
• Gmail stores emails in the cloud.
• Spotify stores millions of songs in the cloud.
• Microsoft 365 stores documents online.

Cloud computing makes these services accessible from anywhere in the world.

Two Ways to Classify Cloud Computing

Cloud computing is commonly classified in two different ways:

1. Deployment models: Where and for whom the cloud infrastructure is deployed

2. Service models: What level of technology the cloud provider gives you 

Types of Cloud Computing: Deployment Models

Deployment models answer one simple question:

Where does the cloud infrastructure operate, and who can use it?

NIST traditionally identifies four deployment models:

1. Public cloud
2. Private cloud
3. Hybrid cloud
4. Community cloud

1. Public Cloud

A public cloud is cloud infrastructure offered by a cloud service provider to many customers.

Resources are delivered through the provider's infrastructure rather than being built exclusively for one organisation.

Popular public cloud providers include:

• Amazon Web Services (AWS)
• Microsoft Azure
• Google Cloud

How does public cloud work?

A cloud provider operates large data centres containing servers, storage and networking equipment.

Customers rent or consume these resources through a web interface, APIs or other management tools.

For example, a startup might use cloud virtual machines to host its website without buying physical servers.

Example

A company launches an online shopping website.

Instead of purchasing servers for peak festival traffic, it uses cloud infrastructure and increases resources as demand rises.

Best for

Public cloud is generally useful for:

• Startups
• Small and medium businesses
• Websites and applications
• Development and testing
• Data analytics
• Organisations that need rapid scaling

Advantages

Lower upfront investment: Organisations do not need to purchase large amounts of physical infrastructure.

Scalability: Resources can be increased or decreased according to demand.

Faster deployment: New environments can often be created quickly.

Access to advanced technology: Organisations can access services such as AI, analytics, databases and managed platforms without building everything themselves.

Disadvantages

Less physical control: The infrastructure is operated by the provider.

Ongoing usage costs: Poorly managed resources can create unexpectedly high bills.

Compliance considerations: Some workloads have strict requirements about where data can be stored or processed.

2. Private Cloud

A private cloud is cloud infrastructure dedicated to a single organisation.

Unlike the public cloud, the environment is not designed to be shared among unrelated customers.

The infrastructure may be located inside the organization's own facilities or managed by a third party.

How does private cloud work?

An organisation creates or operates cloud-style infrastructure specifically for its own workloads.

It may use virtualisation, automation, self-service portals and other technologies associated with cloud environments.

Example

A large financial institution may use a private cloud for applications containing highly sensitive information and subject to strict internal controls.

Best for

Private cloud can be suitable for organisations that need:

• Greater infrastructure control
• Customized environments
• Strict compliance requirements
• Specialised security policies
• Predictable workloads

Advantages

Greater control: The organisation has more control over the environment.

Customisation: Infrastructure can be designed around specific requirements.

Potentially stronger isolation: Resources are dedicated to one organisation.

Disadvantages

Higher cost: Building and maintaining infrastructure can require significant investment.

More management: The organisation or its provider still has to operate the environment.

Scaling can be more complicated: Adding capacity may require additional infrastructure.

3. Hybrid Cloud

A hybrid cloud combines different environments, typically private infrastructure with public cloud resources.

The key idea is not simply having two environments, but connecting them so workloads or data can move or interact appropriately between them.

NIST defines hybrid cloud as a composition of two or more distinct cloud infrastructures connected through technology that enables data and application portability.

How does hybrid cloud work?

Imagine a company has sensitive customer records in a private environment but wants to use public cloud resources for an application that needs additional computing capacity.

The company can connect the two environments.

PRIVATE ENVIRONMENT

     Sensitive data / Core systems

                 │

                 │

          Secure connection

                 │

                 ▼

          PUBLIC CLOUD

       Extra compute / AI /

       analytics/scaling

Example

An e-commerce company could keep certain core systems in its private environment while using public cloud resources to handle sudden increases in website traffic.

Best for

Hybrid cloud is useful for organisations that want:

• A mix of control and scalability
• Gradual cloud migration
• Flexible workload placement
• Support for legacy systems
• Additional capacity when required

Advantages

Flexibility: Different workloads can run in different environments.

Better use of existing infrastructure: Organisations do not necessarily have to abandon existing systems.

Scalability: Public cloud resources can supplement private infrastructure.

Disadvantages

More complexity: Managing connected environments can be difficult.

Security challenges: Data moving between environments needs careful protection.

Higher management requirements: Teams may need skills across multiple infrastructure types.

4. Community Cloud

A community cloud is designed for several organisations that share similar requirements, such as security, compliance, policies or mission needs.

NIST describes it as infrastructure shared by organisations belonging to a specific community with common concerns.

Example

Imagine several government organisations that need similar security and compliance controls. Instead of each organisation building a completely separate environment, a cloud environment could be designed around their shared requirements.

Best for

Community cloud can be relevant to:

• Government Organisations
• Healthcare groups
• Research institutions
• Organisations with shared regulatory requirements

Advantages

• Shared infrastructure costs
• Common security and compliance requirements
• Specialized environment
• Collaboration between participating organisations

Disadvantages

• More limited than a general public cloud
• Governance can become complicated
• Smaller scale may increase costs

Types of Cloud Computing: Service Models

Deployment models tell us where the cloud exists.

Service models tell us how much of the technology stack the provider manages for you.

The three traditional cloud service models are:

• IaaS — Infrastructure as a Service
• PaaS — Platform as a Service
• SaaS — Software as a Service

NIST formally identifies these three service models.

A simple way to remember them is:

IaaS = Rent the infrastructure
PaaS = Build on a managed platform
SaaS = Use the finished software

1. Infrastructure as a Service (IaaS)

IaaS provides basic computing infrastructure through the cloud.

Instead of buying physical servers, you can rent virtual machines, storage and networking resources.

AWS describes IaaS as providing compute, storage and network resources on demand, while the customer remains responsible for applications and much of the software stack.

Simple example

Suppose you want to build a website.

With IaaS, the cloud provider gives you the virtual server and related infrastructure.

You decide:

• Which operating system to use
• Which software to install
• How the application is configured
• How the application is secured

Examples

Common examples include:

• Amazon EC2
• Amazon S3
• Amazon VPC
• Azure Virtual Machines
• Google Compute Engine

Best for

• Developers needing infrastructure control
• Custom applications
• Legacy application migration
• Website hosting
• Testing environments
• High-performance workloads

Pros

• High flexibility
• Greater control
• Easy access to infrastructure
• Can scale resources when needed

Cons

• Requires technical knowledge
• Customer manages more components
• Security mistakes can become the customer's responsibility

2. Platform as a Service (PaaS)

PaaS gives developers a ready-made environment for building and running applications.

Instead of managing servers and operating systems, developers can focus primarily on writing and deploying application code.

Google Cloud describes PaaS as a model where the provider manages the underlying hardware and software environment while developers focus on application development.

Simple example

Suppose you want to build a web application.

With IaaS, you may need to configure the server and operating system.

With PaaS, you can focus more directly on:

Write code → Deploy → Run

The provider manages much of the environment underneath.

Examples

Examples include:

• Google App Engine
• Azure App Service
• Heroku
• AWS Elastic Beanstalk

Best for

• Application developers
• Startups
• Rapid application development
• Teams that do not want to manage servers

Pros

• Faster development
• Less infrastructure management
• Easier deployment
• Developers can focus on the application

Cons

• Less control than IaaS
• Possible vendor lock-in
• Platform limitations may affect certain applications

3. Software as a Service (SaaS)

SaaS is the most user-friendly cloud service model.

Instead of building an application or managing infrastructure, you simply use the software.

The provider manages the underlying infrastructure, application and updates. Google Cloud describes SaaS as delivering the complete application to customers, commonly through a browser.

Examples

Common examples include:

• Google Workspace
• Microsoft 365
• Salesforce
• Zoom
• Slack
• Dropbox

Simple example

When you use an online email service, you do not install and maintain the mail server yourself.

You simply:

Sign in → Use the application → Let the provider handle the infrastructure

Best for

• Everyday users
• Businesses
• Teams needing ready-made software
• Organisations that do not want to build applications themselves

Pros

• Very easy to use
• Minimal maintenance
• Fast deployment
• Automatic updates are commonly handled by the provider

Cons

• Least control
• Dependence on the provider
• Subscription costs
• Customization may be limited

IaaS vs PaaS vs SaaS: What Is the Difference?

Emerging Types of Cloud Computing in 2026

The classic IaaS, PaaS, SaaS and deployment models are still important. However, the cloud ecosystem is expanding rapidly.

In 2026, several cloud approaches are becoming especially important for AI, regulatory control, distributed applications and modern software development.

1. Serverless Computing

Despite its name, being serverless does not mean there are no servers.

It means developers do not have to manage the underlying servers directly.

Cloud infrastructure is automatically provisioned and scaled by the provider, and usage can be billed according to resource consumption.

Two common serverless categories are:

• FaaS — Function as a Service
• BaaS — Backend as a Service

Examples

A website could trigger a small function whenever a customer submits a form.

Instead of keeping a server running 24/7, the cloud platform can execute the function when the event occurs.

Best for

• Event-driven applications
• APIs
• Automation
• Lightweight backend tasks
• Applications with unpredictable traffic

2. Container as a Service (CaaS)

Container as a Service provides an environment for deploying and managing applications packaged in containers.

Containers allow developers to package an application with the components it needs so that it can run consistently across environments.

CaaS sits between traditional infrastructure and fully managed application platforms and is often associated with container orchestration technologies such as Kubernetes.

Best for

• Cloud-native applications
• Microservices
• DevOps teams
• Portable applications
• Large distributed applications

3. Edge Cloud / Edge Computing

Traditional cloud architectures often send data to centralised cloud infrastructure.

Edge computing moves some processing closer to where data is generated or where users need it.

That can help applications that require fast responses or have large amounts of data at the source.

Examples include:

• Smart factories
• Connected vehicles
• IoT systems
• Real-time monitoring
• Retail systems
• Healthcare devices

Edge is increasingly being combined with cloud infrastructure rather than replacing it.

4. Multi-Cloud

Multi-cloud means using services from more than one public cloud provider.

For example, an organisation might use:

• AWS for one workload
• Azure for another
• Google Cloud for AI or analytics

Multi-cloud can provide flexibility and reduce dependence on one provider, although it can also increase management complexity. IBM describes multi-cloud as combining public cloud services from different vendors.

Multi-cloud vs Hybrid Cloud

These terms are often confused.

Hybrid cloud: combines different environments, such as private infrastructure + public cloud.

Multi-cloud: uses multiple cloud providers.

An organisation can have both.

For example:

Private data centre + AWS + Azure = Hybrid multicloud

5. Sovereign Cloud

One of the more important cloud trends in 2026 is the sovereign cloud.

Sovereign cloud focuses on giving organisations greater control over:

• Where data is stored
• Where data is processed
• Who can access it
• Which legal and regulatory rules apply
• Who operates critical infrastructure

This is particularly important for governments and highly regulated industries.

Recent 2026 cloud developments show major providers expanding sovereign-cloud and air-gapped options designed for strict data-residency, regulatory and operational-control requirements.

6. Cloud for AI and Agentic Workloads

AI is changing what organisations expect from cloud infrastructure.

Modern AI applications require large amounts of:

• Computing power
• GPU resources
• High-speed networking
• Specialized storage
• Data pipelines
• Model infrastructure

In 2026, cloud providers are also developing infrastructure specifically for AI agents, which can perform tasks and interact with systems rather than simply generating a response.

Google Cloud, for example, has highlighted new infrastructure and cross-cloud capabilities designed around agentic AI workloads.

This does not necessarily represent a brand-new classical cloud “deployment model” like public or private cloud. Instead, it is better understood as an emerging workload-focused direction of cloud computing.

The Future of Cloud Computing

Cloud computing is moving beyond the traditional idea of “renting servers.”

The biggest shift is toward more specialised, distributed and intelligent cloud infrastructure.

Three developments are particularly important going into 2026:

Cloud + AI

AI workloads are driving demand for specialised infrastructure, GPUs, high-performance networking and new ways of managing compute resources.

Cloud + Edge

Organisations increasingly need computing closer to users and devices, particularly for real-time applications.

Cloud + Sovereignty

Governments and regulated organisations increasingly care not only about where data is stored, but also about who can operate infrastructure and access sensitive information. Recent 2026 developments from major providers show continued investment in sovereign and disconnected cloud environments.

The result is a cloud landscape that is becoming more distributed rather than simply moving everything into a single public cloud.

Conclusion

Cloud computing has transformed the way individuals and Organisations build, deploy, and manage digital solutions. However, understanding cloud computing goes beyond simply knowing what it is, it also involves understanding where your cloud infrastructure is hosted and what level of cloud services you use.

Throughout this guide, we explored the two core classifications of cloud computing: deployment models and service models. Deployment models, including Public, Private, Hybrid, Multi-Cloud, and Community Cloud, determine where cloud resources are hosted and who can access them. On the other hand, service models such as IaaS, PaaS, SaaS, and FaaS (Serverless Computing) define how much of the infrastructure is managed by the cloud provider and how much responsibility remains with the customer.

We also discussed the Shared Responsibility Model, compared different cloud types, explored emerging trends like Edge Computing, AI-Optimized Cloud, and Sovereign Cloud, and learned how businesses can choose the right cloud model based on their goals, budget, and security requirements.