What is infrastructure as a service (IaaS)?

IaaS enables users to scale resources on an as-needed basis, especially in "spiky" workloads, reducing the need for high up-front capital expenditures and the complexity that comes with buying, setting up and maintaining on-premises infrastructure. Startups, enterprise organizations and businesses with high-performance workloads choose IaaS for its cost-effective, flexible and scalable IT infrastructure.

IaaS emerged as a computing model beginning with the launch of Amazon Compute Cloud (EC2) in 2006, which enabled businesses to access virtualized computing resources. Since then, IaaS has become the standard abstraction model for many types of workloads.

With an IaaS model, a cloud service provider (CSP)—Amazon Web Services (AWS), Google Cloud, Microsoft Azure, IBM Cloud or Oracle Cloud—maintains and manages physical infrastructure components (servers, patching, networking hardware). At the same time, an organization remains in control of installing, configuring and managing their software applications.

The IaaS market is predicted to grow rapidly in the next few years, reaching USD 562.53 billion by 2031 at a compound annual growth rate (CAGR) of 33.50% from 2024 to 2031. ¹

In the following video, Bradley Knapp breaks down the basics of IaaS:

Infrastructure as a service (IaaS) comprises a collection of physical and virtualized resources that provide consumers with the basic building blocks that are needed to run applications and workloads in the cloud. IaaS providers host resources such as the physical servers needed to power the various layers of abstraction on top of them in large global data centers.

Virtualization technology makes IaaS possible by creating multiple virtual machines (VMs)—each with its own operating system (OS) and applications—on a single physical machine. This enables dozens of applications and workloads to run and scale successfully. The cloud service provider manages the hypervisors, also known as virtual machine monitors (VMMs), that logically separate VMs from each other, assigning each its own slice of the underlying computing power, memory and storage. Users can then provision virtual "instances" with wanted amounts of compute, memory and storage. 

Deploying virtual machines and other virtualized infrastructure relies heavily on creating and implementing automated processes and software in place of time-consuming manual activities. Automating infrastructure management simplifies tasks such as configuration management, deployment and provisioning. Depending on business needs, IaaS can be paired with automated services and upgrades such as auto scaling, load balancing, backup and disaster recovery and performance monitoring to help optimize application availability and deliver a positive user experience.

IaaS compute includes central processing units (CPU) inside servers for processing web requests and running applications. It also includes graphical processing units (GPU) that handle high-performance workloads and internal memory (RAM). Users can request compute resources via virtual machines, also known as virtual servers or bare metal servers.

Virtual servers are software-based servers that allow multiple virtual machines (VMs) to run simultaneously on a single "bare metal" physical server.

Virtual servers rely on hypervisors that act as a layer between the physical hardware and multiple unique virtual environments. Each of these virtual environments can run its own operating system (such as Microsoft Windows, Linux® or Ubuntu).

Organizations frequently choose virtual servers to run workloads for short periods (that is, development testing, backup and recovery). The benefits of server virtualization include greater resource utilization, lower costs, faster provisioning and more.

While both virtual servers and bare metal servers run on "bare metal hardware," they function differently.

Bare metal servers as a cloud service are physical machines dedicated to one single tenant who gets complete control over the physical machine. Bare metal as a service (BMaaS) features allows the user to choose their operating system, avoid the noisy neighbor challenges of shared cloud computing infrastructure, and finely tune hardware and software for specific—often data-intensive—workloads. While a traditional bare metal server does not come with a preinstalled hypervisor, this software layer can be added to virtualize the server for optimal performance.

Most enterprises use a mix of dedicated or bare metal and virtual servers across their cloud ecosystem. Organizations generally choose bare metal servers over virtual server instances if they need access to the hardware to run a hypervisor. Bare metal servers are a good fit for large steady-state workloads (such as ecommerce and CRM) or applications with complex security or regulatory requirements (such as finance and healthcare).

IaaS relies on software-defined networking (SDN), in which APIs make network hardware (for example, routers, switches, firewalls and load balancers) available. IaaS models virtualize the networking functions of this hardware, and clients can access IaaS services from anywhere over the public internet or by using a virtual private network (VPN).

IaaS offers three types of cloud storage:

• Block storage: Block storage is a technology for storing data files on storage area networks (SANs) or cloud-based storage environments. Developers favor block storage for computing situations that require fast, efficient and reliable data transportation.

• File storage: File storage, also called file storage hosting, allows multiple users to share the same file data. In IaaS instances, organizations store data files off-site in cloud providers' data centers and access them via the internet (instead of storing them locally on a NAS device). 

• Object storage: Object storage is a data storage architecture ideal for storing, archiving, backing up and managing high volumes of static unstructured data—reliably, efficiently and affordably. It is the most common type of cloud storage. 

IaaS includes support for containerization, which packages software code with just the operating system (OS) libraries and dependencies that are required to run the code to create a single lightweight executable—a container—that runs consistently on any infrastructure. More portable and resource-efficient than virtual machines, containers have become the de facto compute units of modern cloud-native applications. 

In many instances, containers replaced VMs as the standard unit of process or service deployment. Container orchestration tools such as Kubernetes automate the deployment, scaling and management of containerized applications. IaaS models provide the underlying resources to scale Kubernetes and containerized applications up or down as business needs dictate.

Third-party cloud service providers adhere to cloud security and compliance frameworks through a shared responsibility model. In essence, the cloud service provider manages the physical security of data centers (cameras, security staff) and underlying infrastructure (compute, storage, physical network).

At the same time, the cloud customer is responsible for securing their workloads, applications and data. The cloud service vendor allows the customer to encrypt virtual machines and other methods to protect client data and reduce the risk of cyberattacks.

The IaaS cloud model represents general-purpose compute resources and can thus support use cases of all types.

• Development and testing

• Backup and disaster recovery

• Website hosting

• Big data analytics

• High-performance computing (HPC)

• Hybrid multicloud adoption

• Artificial intelligence (AI) and machine learning (ML)
  
  

IaaS provides an ideal testing and development environment that users can set up faster than on-premises. This feature offers DevOps and other teams the flexibility to scale dev/test environments up or down quickly, allowing organizations to bring new apps to market faster.

IaaS provides cloud-based backup and disaster recovery solutions, allowing organizations to replicate and back up their systems and data in the cloud. For instance, organizations can duplicate applications across multiple servers. If one server fails, another takes over, helping ensure business continuity.

IaaS provides a cost-efficient way to host customer-facing websites and web applications that are secure, scalable and can be tailored to optimize user experiences.

Driven by cutting-edge technologies such as artificial intelligence (AI) and the Internet of Things (IoT), big data analytics involves the use of advanced analytic techniques against extensive, diverse big data. IaaS supports the enormous processing power needed to analyze vast amounts of data and deliver the best insights.

Compared to a traditional on-premises infrastructure setup, IaaS provides an efficient and cost-effective way to support high-performance computing (HPC). HPC uses supercomputers and computer clusters to solve advanced computation problems that support advances in human knowledge and create significant competitive advantages (for example, DNA sequencing, stock trading automation).

A hybrid cloud approach combines and unifies public cloud, private cloud and on-premises infrastructure to create a single, flexible, cost-optimal IT infrastructure. Today, hybrid cloud is combined with a multicloud approach, which allows companies to select best-in-class cloud services from multiple cloud vendors and avoid vendor lock-in.

IaaS plays an essential role in hybrid multicloud strategy, providing the flexibility to deploy resources across hybrid cloud environments based on business needs. For instance, IaaS supports "lift and shift" migration, where an application is moved from an on-premises setting to compute, storage and networking infrastructure in a cloud provider's data center.

IaaS platforms allow organizations to use AI and machine learning (ML) capabilities. For instance, with IaaS, data scientists and developers can build, train and deploy ML models by using fully managed infrastructure, tools and workflows. IaaS also provides the compute power and underlying infrastructure support foundation models for building and scaling generative AI applications.

The phrase "as a service" typically refers to a cloud computing service where a cloud vendor manages services for an organization. Along with platform as a service (PaaS) and software as a service (SaaS), IaaS is among the top three most popular cloud service models. These cloud computing service categories are not mutually exclusive. Most enterprises use more than one, and most large enterprises use all three managed cloud services as part of their cloud stack offered by cloud service providers.

IaaS, PaaS and SaaS rely on multitenant resources—a single physical computer or VM is shared among multiple users or client organizations. Cloud service providers typically offer multitenant hosting solutions as a lower-cost alternative to single-tenant or dedicated hosting solutions.

In a traditional IT setting, the user is responsible for managing the whole stack end-to-end, from the physical hardware for servers and networking resources up through virtualization, operating systems, middleware and so on. IaaS, PaaS and SaaS each offer a progressive abstraction layer after that. 

As discussed above, IaaS abstracts away the physical compute, network, data storage and the technology that is needed to virtualize those resources. Platform as a service (PaaS) goes a step further and abstracts away the management of the operating system, middleware and runtime. PaaS provides customers with a complete cloud platform—hardware, software and infrastructure—for developing, running and managing applications without the cost, complexity and inflexibility that often comes with building and maintaining that platform in an on-premises data center. 

Red Hat® OpenShift® is a popular PaaS built around Docker containers and Kubernetes.

Software as a service (SaaS) is application software that is hosted in the cloud, and it serves as the primary delivery model for most commercial software today. Popular SaaS business solutions include enterprise resource planning (ERP), project management software and more.

While IaaS abstracts away many low-level components so developers can focus on business logic differentiating the business, it still requires users to manage operating systems, middleware and runtimes. As an application development and execution model, serverless offers an advantage by enabling developers to build and run application code without provisioning or managing servers or backend infrastructure, thus decreasing downtime.

The most common use case of serverless today is supporting microservices (also called microservices architecture), which focuses on creating small services that do a single job and communicate with one another using APIs. Microservices are a vital part of DevOps processes and development tools, which serverless supports as developers don't need to spend time defining the infrastructure required to integrate, test, deliver and deploy code builds into production.

Extra security and privacy within a public cloud are desirable for many users, particularly companies with sensitive data or strict compliance requirements (for example, fintech and healthcare). A virtual private cloud (VPC) can create more isolation of cloud infrastructure resources without sacrificing speed, scale or functions.

A VPC is hosted on a multitenant public cloud architecture. Yet, each customer's data and workloads are logically separate from all other tenants to create a “private-cloud-like” setting. This feature gives users control over multiple facets (for example, virtual firewalls, security groups, load balancers). 

As with all public cloud services, IaaS requires a service level agreement (SLA)—a contract between a cloud service provider and client that outlines what services the vendor will provide, the level of performance to be expected, how performance is measured and what happens if performance levels are not met.

IaaS is priced on a consumption basis, meaning users are only charged for what they use. Other pricing methods include the following: 

• Subscriptions and reserved instances: Many providers offer discounts off the sticker price for clients willing to commit to longer contract terms—typically around one to three years.

• Monthly billing: Monthly billing models are more common with BMaaS than IaaS, where physical infrastructure typically implies steady-state workloads without spiky characteristics.

• By the hour/second: The most common granularity for traditional cloud infrastructure, users are charged only for what they use.

• Transient/spot: Some providers offer up unused capacity at a discount via transient/spot instances, but those instances can be reclaimed if the capacity is needed.

Some of the top advantages of IaaS include the following:

• Pay-as-you-go: Unlike traditional IT, IaaS does not require any upfront capital expenditures, and users are only billed for what they use.

• Speed: With IaaS, users can provision small or vast amounts of resources in minutes, testing new ideas quickly or scaling proven ones even quicker.

• Availability: Through things like multizone regions, the availability and resiliency of cloud applications can exceed traditional approaches.

• Scale: With seemingly limitless capacity and the ability to scale resources automatically or with some supervision, it's simple to go from one instance of an application or workload to many.

• Latency and performance: Given the broad geographic footprint of most IaaS providers, it's easy to bring apps and services closer to users, reducing latency and improving performance.