IaaS, PaaS, SaaS: What's the difference?

“As a service” refers to the way IT assets are consumed with cloud-based products, highlighting the essential difference between cloud computing and traditional IT. In traditional IT, businesses consume IT assets by purchasing, installing, managing and maintaining them in on-premises data centers. With cloud computing, the cloud service provider owns, manages and maintains assets. The customer consumes them using an internet connection and pays for them on a subscription or pay-as-you-go basis.

IaaS is a form of cloud computing that delivers on-demand access to cloud-hosted compute, storage and networking—the backend IT infrastructure for running applications and workloads in the cloud. It enables businesses to scale resources as needed and reduces the need for significant upfront capital expenditures or complex on-premises infrastructure configurations. 

Organizations often rely on IaaS tools to manage high-performance workloads, especially in the case of “spiky” workloads that are prone to sudden surges of user activity.

PaaS is a cloud computing model that provides a complete on-demand cloud platform (hardware, software and infrastructure) for developing, deploying and running applications. The PaaS provider hosts servers, networks, data storage, operating system (OS) software, databases and development tools across a distributed global infrastructure. 

PaaS can enable businesses to build, test, deploy, run, update and scale applications faster and cheaper than with an internally developed and managed, on-premises platform.

SaaS is cloud-hosted software delivered over the internet to computing devices. SaaS providers operate, manage and maintain the software and the infrastructure on which it runs. Instead of buying application software and installing it on a local device, SaaS users can immediately create an account, subscribe to the application and get to work.

IaaS, PaaS and SaaS target different IT layers and provide varying levels of control. Generally, IaaS offers organizations fine-grained control over infrastructure components—but also requires more technical expertise and ongoing maintenance on the part of enterprise customers.

SaaS, meanwhile, provides enterprises relatively little control but is highly accessible, even for non-technical end users. PaaS falls somewhere in between: providers handle development infrastructure and related components, while organizations control the apps and data that run on top of the vendor-hosted production environment.

IaaS, PaaS and SaaS are not mutually exclusive—many enterprises use all three—as each one provides developers accessible, scalable IT capabilities with a more flexible cost structure.

IaaS offers a cloud-based alternative to on-premises computing infrastructure, delivering access to physical and virtual computing resources (hosted in data centers by IaaS providers) to IT teams.   

With IaaS, providers supply and maintain (through patches, upgrades and troubleshooting, for example) the foundational infrastructure for IT operations, so customers can focus on software and strategy rather than managing physical hardware. Customers access IT resources and services over the internet or private network connections and retain control over everything above the infrastructure layer, including operating systems, runtimes, middleware and applications.

IaaS tools rely on virtualization technology, which enables multiple virtual machines (VMs) to run on a single physical server. Each VM operates independently—with its own operating system, applications, CPU, memory and storage—and the provider manages hypervisors (also called virtual machine monitors or VMMs) that keep the VMs isolated. Hypervisors also allocate computing power, memory and storage to each instance, enabling customers to create, configure and scale virtual instances to match their needs.

Depending on business needs, IaaS can be paired with automated services such as auto scaling, load balancing, disaster recovery and performance monitoring to help optimize application availability and workload management.

However, vendor lock-in can be a concern, making it difficult for businesses to change providers after their IaaS platform is fully configured. As a result, decision makers should carefully consider their long-term IT goals and needs before selecting an IaaS provider.

IaaS providers typically charge customers through a flexible, usage-based (pay-as-you-go) model. But for more predictable workloads and longer-term commitments, companies can opt for reserved instances or subscription-based billing (such as monthly billing). Many providers offer discounts for these commitments. 

IaaS delivers a range of virtualized computing resources that IT teams can access and control over the internet. They include:

IaaS compute engines consist of central processing units (CPUs) for web processing and application execution, graphics processing units (GPUs) for high-performance workloads, system memory (RAM) and networking components. Organizations can request computing resources in the form of virtual machines or dedicated bare metal servers.

Bare metal servers are physical machines that are typically dedicated to a single customer. They give customers full control over the hardware, enabling customers to configure and run customized workloads. This capability can be especially useful for workloads that require high performance, strict compliance or minimal latency. Traditional bare metal servers lack preinstalled hypervisors, but users can add them if necessary.

Virtual servers are software-defined servers that enable multiple VMs to share a single bare metal server. They’re ideal for flexible, short-term workloads like development, testing and data backup. They can help businesses optimize resource usage, cut costs and quickly provision IT resources.

Enterprises often use a combination of virtual and bare metal servers to balance performance, customization and scalability.

Networking in IaaS is powered by software-defined networking (SDN), which uses application programming interfaces (APIs) to give IT teams access to virtualized routers, switches, firewalls, subnets, VPN gateways and load balancers. Customers can use network APIs to securely connect their virtual infrastructure to the internet and manage communication between different network resources.

IaaS platforms offer several cloud storage options. Block storage, for instance, stores data in volumes on storage area networks (SANs) or in cloud-based storage environments. This capability makes block storage well suited for use cases that require fast, reliable data transfer. File storage enables multiple users to share files by storing data in the cloud and providing access through the internet.

IaaS environments support containerization, which packages applications into lightweight, portable containers that include all necessary OS libraries and dependencies. Containers are more efficient than VMs because they can be deployed, managed and scaled with orchestration tools such as Docker and Kubernetes.  

Security in IaaS is based on a shared responsibility model. The provider is responsible for securing the physical infrastructure, including data center facilities and underlying hardware. Typically, the vendor offers tools for data encryption, access controls and network security, which help customers safeguard sensitive information and reduce the risk of cyberattacks. Customers, in turn, are responsible for securing their own applications, workloads and data within the cloud.

IaaS models offer general-purpose compute resources across a range of use cases, including:

Compared to traditional IT infrastructures, IaaS platforms give customers more flexibility to quickly scale computing resources. Specifically, IaaS helps businesses address the rightsizing dilemma: Organizations don’t need to purchase excess on-premises capacity to accommodate spikes—or risk outages and suboptimal performance when demand exceeds available resources.

Investing in an IaaS solution has numerous benefits, including:

• Greater availability. With IaaS, businesses can create redundant servers in geographically dispersed locations to help ensure high system availability, even during local service outages or disruptions.
  
  
• Lower latency, improved performance. Because IaaS providers typically operate data centers in multiple locations, businesses that use IaaS can often run apps and services closer to users to minimize latency and improve performance.
  
  
• Improved responsiveness. IaaS enables IT teams to dynamically provision resources to match demand. It also enables them to accelerate the testing and deployment of new products and services.
  
  
• Faster access to cutting-edge technology. With a cloud-based infrastructure, businesses can generally take advantage of the latest technologies sooner—and at a lower cost—than with on-premises infrastructure.

PaaS provides a cloud-based platform for developing, deploying and running applications. The cloud service provider hosts, manages and maintains hardware and software—including servers (for development, testing and deployment), operating system (OS) software, storage, networking, databases, middleware, runtime environments, application frameworks and development tools—as well as related services for security, software upgrades, backups and more.

Organizations access the PaaS through a graphical user interface (GUI), where development or DevOps teams can collaborate across the entire application lifecycle including coding, integration, testing, delivery, deployment and feedback.

Like IaaS, vendor lock-in can present a challenge with PaaS services, especially when teams attempt to migrate complex applications to another provider. PaaS also requires businesses to give up some control of development infrastructure. If the vendor experiences a security issue or modifies the platform (by discontinuing support for certain services, for example), the changes can degrade app performance.  

With PaaS, organizations can pay a fixed fee for a set amount of resources supporting a specific number of users. Or, like with IaaS, enterprises can choose pay-as-you-go pricing, where costs scale based on platform usage.

PaaS delivers an application platform layer—abstracting servers, operating systems, networks, storage and other components—so that dev teams can focus on coding rather than managing application infrastructure. Key components include:

PaaS supports multiple runtimes, each corresponding to a particular programming language and its associated components, including libraries, dependencies and interpreters. For example, if a customer builds an application with Java, it can deploy the app inside a PaaS-provided Java runtime environment. An application written in Python can be deployed in a separate runtime instance. Both instances share the same PaaS-provided infrastructure. PaaS platforms also support custom runtimes for specialized deployments, although this approach requires more setup and configuration on the part of the customer.  

PaaS solutions offer built-in middleware services that facilitate integrations and orchestration across internal and third-party services, databases and clients, often through APIs. For example, message queues help applications exchange data asynchronously, while database middleware connects applications to backend data stores. Finally, PaaS-provided web servers receive requests and route them to API endpoints so that clients can access applications on the web.

PaaS solutions typically provide extensive database and storage services so that applications can continually access critical data, such as user accounts, product inventories, transactional records and analytics, without the customer needing to provision and maintain its own databases. In some configurations, PaaS platforms can automatically scale database capacity based on application traffic to reduce the risk of bottlenecks and improve availability.

PaaS provides a suite of development tools that can help streamline and accelerate app rollouts and updates.

PaaS can integrate with version control systems, such as Git repositories, helping teams track source code changes, maintain a record of deployments and revert to previous versions if needed. Testing and staging environments enable dev teams to validate changes before committing to full-scale production, while software development kits (SDKs) provide libraries, documentation and other tools to streamline the code-writing process.

Built-in logging and monitoring tools can help teams assess app performance, while debugging tools help detect errors before they cascade into major failures.

GUIs are accessible dashboards where development or DevOps teams can manage their work throughout the application lifecycle. The GUI’s development tools enable developers to log in from anywhere, collaborate on projects, test new applications and release finished products.

PaaS offloads not only underlying infrastructure but also the provisioning, scaling and operation of the application environment to the PaaS provider. PaaS use cases include:

PaaS platforms balance control and convenience, helping DevOps teams boost productivity and accelerate development cycles.

PaaS tools can help businesses:

• Accelerate time to market. PaaS platforms enable enterprises to provision resources and develop software without managing the underlying platform, accelerating deployments.

• Streamline scalability. With on-premises platforms, businesses often must purchase excess IT resources to manage traffic fluctuations, which can be both wasteful and expensive. During low- and normal-traffic periods, the excess resources sit idle. PaaS platforms enable enterprises to automatically scale resources as needed and to use those resources immediately.

• Access a wider range of IT resources. PaaS platforms offer access to a wide range of resources that many organizations can’t afford to purchase and maintain themselves.

• Experiment with less financial and operational risk. PaaS enables developers to test new operating systems, languages and other tools without making substantial investments in them.
  
  
• Enhance security. PaaS platforms provide built-in security tools that can strengthen security for organizations without dedicated security resources or expertise.

SaaS (or cloud application services) offers complete, provider-managed software solutions delivered over the internet.

SaaS takes advantage of cloud computing and economies of scale, providing customers with a more efficient way to access, use and pay for software. SaaS providers host SaaS applications on their servers and manage their availability, security and performance. Users typically subscribe to SaaS applications on a monthly or annual basis and access them using a web browser or mobile app.

While some SaaS providers offer usage-based pricing, others use flat-rate pricing, where users can access all app features for a single, fixed price, like a streaming service subscription. An estimated 72% of SaaS providers, meanwhile, use hybrid pricing, where customers pay a fixed price alongside other usage-based components. Many SaaS providers offer tiered packages based on the number of users that need to access the app.

Today, SaaS is the most widely used public cloud computing service and the dominant software delivery model. The average organization manages 305 SaaS apps, while large enterprises use nearly 700 on average, according to a 2026 Zylo report.

Examples of SaaS apps include everyday tools—such as Salesforce for customer relationship management (CRM), Dropbox for file storage and sharing, and HubSpot for product marketing—as well as core enterprise resource planning (ERP), human resources and workforce optimization platforms.

While SaaS provides numerous benefits, the model also introduces new challenges. Because SaaS apps are easy to access and deploy, they can proliferate across an organization without IT staff’s knowledge. This phenomenon—known as SaaS sprawl—can cause wasteful spending, inefficient workflows, data silos and security risks.

SaaS applications also come with lock-in challenges. Proprietary technologies, complex integrations (vendor-specific APIs, for example) and other factors can create application dependencies that make it complicated and expensive to change SaaS providers.

At its core, SaaS delivers a fully managed, ready-to-use application to the customer. Unlike IaaS and PaaS, neither IT teams nor end users manage underlying infrastructure or platform architecture; they consume the application, while the provider handles maintenance, provisioning and updates. Components include:

In SaaS, the provider handles data storage and management so that customers can access and store data without needing to manage databases in the backend.

A good example is a CRM platform that integrates customer records, sales histories, demand forecasts and marketing materials. While SaaS customers generally decide which users can access this data, the CRM provider is responsible for storing, securing and backing it up at the infrastructure and platform levels.

SaaS providers are responsible for securing data stored within their platform and maintaining regulatory compliance, which can vary by location and industry. Providers can use encryption, audit logs, firewalls, API gateways and other mechanisms to help monitor activity, detect vulnerabilities and fix bugs. These built-in security features significantly reduce the burden on customers’ IT teams. However, consuming organizations remain responsible for identity and access management as well as maintaining the security of connected devices and services.

Many SaaS applications feature an accessible user interface that enables non-technical customers to use the application, often through the web. Unlike IaaS and PaaS, users typically do not write or deploy code. Instead, the SaaS provider abstracts and controls the coding and infrastructure layers, including provisioning, runtime management and scaling. Customers use the UI to access features, manage workflows, interact with data and toggle settings such as permissions and integrations.

SaaS providers can roll out updates, such as security patches or feature launches, without interfering with customers’ workflows or involving customers’ IT teams. Updates are delivered in real time through the cloud, often without customers being aware of them.

Many SaaS apps run on a multitenant architecture, where a single instance of the application serves multiple customers. To help ensure security and privacy, each customer’s data and configurations are kept separate from others through data isolation, tenant identifiers and other mechanisms.

Many providers offer APIs that enable customers to integrate SaaS solutions with other cloud-based web applications or on-premises software systems. For example, an organization might connect an e-commerce site to a cloud-based payment platform or CRM.

SaaS is now the dominant software delivery model across virtually every business function, including:

SaaS platforms prioritize convenience, accessibility and ease of use across an array of capabilities. SaaS platforms can enable:

• Universal accessibility. SaaS applications are available to any user with an internet connection and a compatible device. Most SaaS solutions are available through a web browser, dedicated mobile app or lightweight desktop client, enabling users to access them across devices without managing local installations or infrastructure.
  
  
• Faster adoption. Customers can purchase and use SaaS applications immediately, often within hours or days, for a minimal upfront cost (typically, the cost of the first month’s subscription).
  

• Streamlined upgrades and updates. SaaS applications give users access to new features and versions immediately when they’re available. Providers might roll out new functions or fixes on a weekly basis, often without customers noticing.
  
  
• No provisioning or infrastructure maintenance: With SaaS, customers don’t have to worry about managing or maintaining underlying infrastructure because the SaaS provider delivers all critical services.
  

• On-demand scalability. Organizations can scale SaaS applications as needed, by upgrading or downgrading tiers or purchasing more capacity. In some enterprise cases, however, downgrading can be contractually restricted.
  

• Flexible costs and efficient spending. Enterprises no longer need to dedicate in-house IT resources to infrastructure, installations and upgrades; the SaaS provider owns these tasks. As a result, costs are tied to subscriptions and usage, resulting in more predictable and cost-efficient IT budgets.

Though many enterprises use all three cloud service models, each model is designed for different customer needs and assigns varying levels of IT responsibility to the provider.

IaaS provides organizations with fundamental IT infrastructure and a flexible, scalable solution that can be adjusted as business needs evolve. However, IaaS requires the most hands-on IT expertise of the three models covered here: Enterprises remain responsible for configuring and maintaining virtualized infrastructure and the full software stack.

Compared to the other cloud computing models, IaaS provides fewer preconfigured components. Without sufficient resources, even skilled IT teams can struggle to maintain workloads and associated costs.

Despite these challenges, IaaS’s pay-as-you-go pricing model accommodates organizations with a range of budgets, including enterprises whose IT departments lack the resources for major infrastructure investments. IaaS also enables organizations with unpredictable workloads, such as startups undergoing rapid growth, to optimize infrastructure costs with highly scalable and customizable cloud-based components.

PaaS acts as the middle layer in the cloud computing stack, combining the flexibility and customization of IaaS with the streamlined workflows and rapid deployment benefits of SaaS. PaaS builds upon the IaaS model by not only providing basic infrastructure but also offering managed OSs, middleware and runtime environments. These resources make it easier for developers to deploy applications and build CI/CD pipelines, but they also limit customization and control over the development environment.

PaaS platforms can simplify routine tasks such as code integration and database management, providing a level of flexibility not available with SaaS. For example, programmers designing a CRM platform can offload infrastructure and development resource management to the service provider, while retaining control over the CRM’s features and associated data.

Because PaaS abstracts the platform and provides a consistent development environment, it is advantageous for geographically dispersed teams. Like IaaS, PaaS can be more cost-efficient than building in-house solutions, but the key distinction from IaaS is that it provides a development platform on top of the infrastructure layer.

Unlike IaaS and PaaS, nearly all organizations use SaaS products in some capacity, regardless of industry or size. Businesses choose SaaS when they need a ready-to-use software application that is reliable and requires minimal setup. This will inevitably be the case for at least some business functions, although the extent that an enterprise integrates SaaS tools into its workflows can vary widely.

With SaaS, the service provider handles everything from application development to infrastructure provisioning and maintenance. Users access the application through a web browser, often without needing to install or maintain app components.

For example, users of a calendar app might want the ability to create events and manage scheduling without the hassle of configuring settings or keeping software updated. If a server fails due to a misconfiguration or a security breach, users expect the SaaS provider to promptly address the issue and restore access (ideally without service disruptions).

However, the convenience of SaaS comes with tradeoffs. Users have little to no administrative control, and integration options can be limited. Also, because users don’t own SaaS software, the provider retains control of the platform and data, which limits user oversight.

Returning to the CRM example, a business might select a ready-made SaaS CRM solution, offloading all day-to-day IT management but relinquishing control over functions, data storage and security to the SaaS provider.

If a business requires greater control or customization, PaaS or IaaS paired with proprietary software might be better options for specific business functions. But because SaaS apps are easier to deploy and require minimal setup, they remain popular across many enterprise use cases.

The shared responsibility model is a framework that defines how responsibilities, and especially security roles, should be divided between vendors and customers across different cloud service models. The framework plays an important role in enterprise accountability, helping ensure that there are no gaps between customers’ and vendors’ security expectations.

Generally, the higher up the stack you go (IaaS → PaaS → SaaS), the more security responsibility transfers to the vendor and the less remains with the customer. It’s worth noting that “the vendor” is not always the same entity: a SaaS vendor might host their application on AWS, in which case, the SaaS vendor is responsible for application security, while AWS is responsible for infrastructure security. 

While duties can vary by product and provider, here’s a general breakdown of security responsibilities across the three primary cloud models:

IaaS:

• The provider oversees servers, networking, hypervisors and other physical infrastructure.
  
  
• The customer is responsible for keeping middleware, integrations, runtimes, apps, OSs and data secure. The client also handles access controls and monitoring.

PaaS:

• The provider secures the platform environment, including storage, databases, middleware and other development-related components.
  
  
• The customer secures the apps (and accompanying data) built and deployed on the development platform.

SaaS:

• The provider is responsible for most dimensions of security, including for the application itself and the underlying infrastructure.
  
  
• The customer retains control of identity and access, connected devices and some data stored within the application.

IaaS, PaaS and SaaS are part of an emerging category known as “anything as a service” (XaaS), which has grown to encompass numerous cloud-based functions, including disaster recovery as a service (DRaaS), database as a service (DBaaS) and Function as a Service (FaaS).

As cloud-based, API connected services, XaaS makes it easier to connect and integrate data across different environments. This capability can acclerate digital transformation initiatives and support modern technologies such as 5G networking, edge computing, artificial intelligence (AI) and Internet of Things (IoT).

While cloud adoption is widespread, dissatisfaction—particularly around costs—is also on the rise; more than half (60%) of businesses are spending more than they want on cloud products.

To address this problem, enterprises are increasingly adopting multicloud and hybrid cloud strategies, blending public and private cloud resources to take advantage of the benefits of each. This approach helps companies streamline both traditional development processes and newer practices, such as AIOps and big data processing. Today, 88% of businesses operate across hybrid or multicloud environments, according to cybersecurity firm Fortinet.

Hybrid and multicloud environments also enable IT teams to distribute workloads across on-premises infrastructure and public cloud platforms, and to take advantage of the strengths of multiple providers, which helps prevent vendor lock-in. Together, these strategies can improve the flexibility, resilience and scalability of IT environments, helping businesses remain agile as technologies and customer needs change.   

AI and machine learning (ML) have the potential to accelerate and streamline workflows across IaaS, PaaS and SaaS deployments. For example, teams can use AI to analyze cloud usage patterns, identify cloud waste and automate cost reduction processes (such as workload right-sizing).

While AI technologies can increase upfront cloud expenditure, they can also help businesses optimize cloud budgets, contributing to more efficient spending in the long term.

Each “as a service” platform uses AI in different ways—with responsibilities distributed differently across services:

Developers can use IaaS’s on-demand computing power and infrastructure to design, train and run custom AI models at scale. For example, instead of purchasing and maintaining expensive GPUs (which incur expenses even when sitting idly), teams can dynamically provision GPU access through the cloud based on current needs.

IaaS is ideal for organizations that need to maintain fine-grained control of their LLMs, including enterprises that incorporate AI into customer-facing products or who have special compliance and regulatory considerations.

PaaS can provide a suite of fully integrated, pre-built machine learning services to streamline the development of AI-powered applications.

Instead of designing their own LLMs or calling models through externally hosted APIs, teams can access managed AI capabilities—including vision, speech and natural language processing—directly in the production environment. The PaaS provider handles hardware provisioning, scaling, request routing and other duties. Developers can then incorporate PaaS-provided machine learning (ML) capabilities into user-facing applications and present them as native features.

PaaS providers might also offer MLOps support, including managed pipelines for training, versioning, monitoring and retraining models. These capabilities enable organizations with more specialized AI needs to accelerate custom ML deployments while benefiting from platform-level orchestration and monitoring.

A growing share of SaaS products incorporates generative AI capabilities, enabling customers to benefit from AI integrations without having to build and manage models themselves. Models are typically integrated into the service and are abstracted from the end user.

For example, a cloud-based productivity tool might use AI to autonomously organize projects, while an analytics platform might use AI to identify traffic and data patterns.

However, AI integration brings new security, privacy and governance challenges. For example, users might unintentionally embed sensitive or proprietary data in their prompts. While this data remains stored inside the SaaS environment, the customer has little control over how it is handled. The SaaS provider might use customer data to train new foundation models, raising confidentiality concerns.

Also, although the customer can customize some model behaviors and settings, the vendor controls most parameters. As a result, customers lose the ability to audit and fine-tune their own AI models and outputs.