The Major Types of Cloud Computing Models Explained

Cloud computing has transformed how organizations access computing resources and services. Businesses can gain agility, scalability, and cost efficiency by leveraging the cloud. Understanding the different types of cloud computing models is key to harnessing the full potential of the cloud.
This article will explain the significant deployment models of cloud computing: public, private, and hybrid cloud. We’ll also break down the key service models: IaaS, PaaS, SaaS, and more. Let's dive in.

The deployment model refers to the type of cloud environment and infrastructure. There are three main models to choose from:

A public cloud provides computing services and infrastructure over the internet hosted at a cloud provider's data centers. The resources are shared between different organizations (tenants).

Leading public cloud platforms include Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM Cloud, and Oracle Cloud.

Public clouds are best suited for workloads that require agility, scalability, and pay-as-you-go pricing. Organizations can quickly provision resources on-demand without upfront infrastructure costs.

However, there are some security and compliance concerns with public clouds since data resides outside the organization's walls. Public clouds are not ideal for highly regulated workloads.

A private cloud provides dedicated cloud resources for a single organization, hosted on-premise or externally with a third-party provider. The infrastructure allows organizations greater control and security while benefiting from cloud scalability and self-service.

Private clouds are preferable for regulated industries like finance and healthcare that require greater control over sensitive data. However, they are more expensive to set up and maintain than public clouds.

A hybrid cloud combines private and public cloud infrastructure. Organizations can extend or migrate workloads from a private cloud to public cloud resources to harness agility, scalability, and cost savings.

The hybrid model provides the most flexibility. Businesses can determine the best deployment environment for each application based on security, compliance, and economics. However, hybrid clouds are more complex to set up and manage.

Infrastructure as a Service (IaaS) delivers fundamental compute, storage, and networking resources over the Internet on a pay-as-you-go basis. Users can provision infrastructure on-demand instead of building and maintaining it physically on-premise.

IaaS allows organizations to scale infrastructure seamlessly without upfront capital investment. It also automates resource management so users don't have to handle time-consuming infrastructure tasks.

Leading IaaS providers include Amazon Web Services (AWS), Microsoft Azure, Google Compute Engine (GCE), IBM Cloud, and Oracle Cloud Infrastructure (OCI).

• Cloud Servers in IaaS

A core component of IaaS is cloud servers. Also called virtual servers, these are simulated computer instances created through virtualization. Users can launch cloud servers on-demand and pay based on short-term usage.

Cloud servers offer the same capabilities as physical servers but with added benefits like rapid scaling, high availability through redundancy, and resilience through distributed architecture. IaaS can deliver flexible and instantly scalable compute power by utilizing cloud servers.

Platform as a Service (PaaS) provides a fully managed platform to develop, deploy, and manage cloud-based applications without building the underlying infrastructure. This allows developers to focus solely on application code.
Key capabilities provided by PaaS include application hosting, database management, workflow management, cloud storage, APIs, security tools, CI/CD pipelines, machine learning, and more.
Leading PaaS vendors include Amazon Web Services (Elastic Beanstalk), Microsoft Azure, Salesforce Platform, Google App Engine, and Red Hat OpenShift.

For developers, PaaS eliminates the need to provision infrastructure and middleware. Developers can use the pre-built, auto-scaling environments in PaaS to quickly develop and test applications using modern frameworks, containers, microservices, and DevOps patterns.

PaaS empowers faster code development and deployment. The managed platform handles infrastructure, operations, and middleware so developers can dedicate their energy exclusively to application innovation.

Software as a Service (SaaS) provides ready-to-use cloud-based applications that users can access on-demand over the internet, usually on a subscription basis. Users don't have to manage any underlying infrastructure.

Examples include email, conferencing tools, CRM, HR management, ERP, and productivity software like Office 365, Google Workspace, and Zoho Office.

The benefits of SaaS include lower upfront costs, flexible usage-based pricing, automatic updates, accessibility from anywhere on any device, and seamless collaboration capabilities.

However, SaaS also comes with reduced customization and reliance on vendors for uptime and performance—the risk of losing data if the vendor goes out of business.

SaaS is ubiquitous for productivity software like documents, spreadsheets, presentations, email, calendars, and collaboration tools. Leading options include Microsoft 365, Google Workspace, Zoho Office, and OnlyOffice.

These provide enterprise-grade capabilities without complex on-premise installation. Users can access applications from any device with an internet connection. Vendors handle hardware, software, and security patching.

Networking as a Service (NaaS) delivers enterprise-grade network infrastructure and capabilities on-demand over the cloud. This includes services like virtual LANs, private network connections, load balancing, DDOS protection, and bandwidth on demand.

NaaS allows businesses to scale and optimize network capacity as needs change without upfront infrastructure costs. Leading NaaS vendors include Cisco Meraki, VMware NSX, and Amazon VPC.

Serverless computing allows users to execute application code without provisioning backend servers. The cloud provider dynamically allocates compute resources to run code on demand. Users are charged based on actual compute usage rather than having to maintain server capacity.

This is ideal for event-driven workloads, have variable traffic, or require automated scaling. Users focus on code while the provider handles infrastructure management. AWS Lambda and Microsoft Azure Functions are leading serverless platforms.

Many modern organizations are adopting multi-cloud or hybrid cloud approaches, combining multiple public and private clouds:

• Multi-cloud: Using two or more public cloud providers to avoid vendor lock-in and optimize for capabilities, reliability, and costs across platforms.
• Hybrid cloud: Bridging private and public cloud infrastructure to get the best of both worlds - security of private along with scalability of public.

Moving to these models provides flexibility to choose across vendors. However, it does require integration efforts to enable interoperability across environments.

The emergence of diverse cloud computing models has provided organizations with tremendous choice and flexibility. Companies can optimize workload placement and spending based on specific performance, security, and cost requirements.

We will continue seeing even greater abstraction of infrastructure complexities through serverless and edge computing trends. Cloud interoperability will improve further with APIs and new standards.

As cloud technologies evolve, businesses must stay nimble and leverage the right deployment and service models to unlock innovation and efficiency. Public, private, and hybrid approaches are ideal for most modern enterprises.