IaaS vs. PaaS vs. SaaS: When Is Each Option Most Applicable?

Cloud adoption is accelerating as businesses look for ways to enhance agility, reduce costs, and streamline operations. According to a Google survey, 41.4% of cloud leaders are increasing their use of cloud-based services and products, 33.4% are migrating from legacy enterprise software to modern cloud-based tools, and 32.8% are moving on-premises workloads to the cloud. This rapid shift has driven the global cloud migration services market to $11.2 billion in value in 2024, with projections to grow at 26% annually from 2025 to 2034.

While the cloud offers unprecedented opportunities for scalability, flexibility, and innovation, choosing the right cloud service model requires a clear understanding of your business goals and careful planning. When picked right, it helps you avoid unnecessary complexities and optimize cloud expenses.

In this article, we’ll explore cloud service models and their unique features, use cases, benefits, and limitations to help you optimize your cloud strategy.

But let’s start from the basics.

Cloud service models represent different ways cloud providers deliver computing services over the Internet. These models define the level of control, management, and responsibility shared between the provider and the user. Specifically, they describe how much of the software and hardware stack you manage and how much the cloud provider manages.

Usually, cloud providers recognize three major cloud service models:

• Infrastructure as a Service (IaaS)
• Platform as a Service (PaaS)
• Software as a Service (SaaS)

However, as cloud computing continues to evolve, new cloud service models emerge. They are often built upon existing ones to expand their capabilities or address previously unmet business needs. What all these models have in common is the “as a service” part. This term highlights how companies consume IT assets in these offerings and distinguishes cloud computing from on-premises.

Typically, organizations purchase and own physical IT resources (e.g., hardware, system software, development tools, and applications) and then install, manage, and maintain them in their on-premises data centers.

In contrast, cloud computing shifts this burden to the cloud service provider. The provider owns and maintains the underlying IT infrastructure or software. Customers access these resources over the Internet and pay for them on a subscription or pay-as-you-go basis. This approach reduces the need for upfront capital investment and provides more flexibility.

By understanding the role and responsibilities inherent to each model, you can choose the one that aligns the most with your operational goals. In the following sections, we’ll dive deeper into the specific characteristics, advantages, and use cases of the primary cloud service models. We’ll also take a closer look at their extensions, such as Container as a Service (CaaS) and Function as a Service (FaaS), which offer additional flexibility for containerized workloads and event-driven applications.

Infrastructure as a Service (IaaS) is the foundational layer of cloud computing. It provides virtualized computing resources such as servers, virtual machines (VMs), compute, network and storage over the Internet on a pay-as-you-go basis.

In 2023, IaaS accounted for over a quarter of the overall cloud computing market . The rise of IaaS is closely tied to the growing need for businesses to find cost-effective alternatives to deploying and maintaining on-premises infrastructures.

In-house data centers require significant upfront investments in hardware, space, and maintenance, which makes their implementation a challenging option, particularly for small and midsize companies. IaaS removes these financial and operational burdens, allowing businesses to start quickly without establishing physical data centers.

However, IaaS provides more than just the raw infrastructure. It also gives you a wide range of tools and services to adapt to changing demands, including logging and monitoring, load balancing and clustering, and services such as backups, replication, and disaster recovery to ensure data availability. In addition, IaaS can offer built-in security measures, such as firewalls and encryption, to protect data. All of these make IaaS an accessible alternative to on-premises data centers.

In the IaaS market, the most prominent companies in terms of revenue are Amazon Web Services (AWS) and Microsoft Azure. While Amazon remains the leading provider of cloud infrastructure by a significant margin, its dominance is gradually being challenged by Microsoft Azure. In fact, in 2024, 62% of Statista respondents reported using Microsoft Azure, and 54% used Amazon Web Services (AWS) as their IaaS provider.

IaaS is highly adaptable, making it suitable for various use cases across diverse industries. Here are some of the most common scenarios in which IaaS proves to be a great choice.

• On-demand environments for application development and testing. IaaS provides developers with a flexible and scalable environment to create, test, and deploy applications without managing physical hardware. This means you can quickly spin up virtual machines to test software under different configurations and scale resources up or down as needed.
• Scalable hosting for high-traffic events. IaaS is perfect for hosting websites and applications, especially those with fluctuating or unpredictable traffic patterns. It allows businesses to handle traffic surges during events like sales or promotions without overprovisioning resources.
• Disaster recovery and backup. IaaS enables businesses to establish reliable disaster recovery and backup solutions without maintaining separate physical infrastructure. Critical business data is stored and replicated in the cloud to ensure business continuity during outages.
• Virtual desktops. IaaS supports the deployment of virtual desktops, allowing employees to access their work environments securely from anywhere. This allows remote workforces to log in to virtual machines with pre-configured desktops.

Yet, IaaS might not be the most fitting option if you don’t want to manage infrastructure. Since IaaS provides significant control over the operating system, middleware, and runtime, it demands a certain level of technical knowledge and responsibility from the user.

For example, if your business doesn’t have an in-house or dedicated IT team, you may find it challenging to manage virtual machines, handle operating system updates, or troubleshoot infrastructure-related issues. In such cases, Platform as a Service (PaaS) may be more suitable, as it offers higher abstraction and management.

Containers as a Service (CaaS) is a cloud-based service that sits between IaaS and PaaS in the cloud computing landscape. It is often viewed as a subset of IaaS, which typically uses resources like virtual machines (VMs) or bare-metal hosts. However, CaaS focuses on the container as the core resource. Containers are lightweight and portable environments designed to package applications with all their dependencies, making them ideal for cloud-native environments.

As organizations shift toward microservices to improve agility and flexibility, they require a reliable and scalable platform to deploy and manage these distributed, containerized workloads. This increasing demand for microservices architecture has fueled the growth of CaaS platforms.

In 2023, 51% of companies worldwide reported running multiple applications within containers. Additionally, 50% indicated they use single containers for individual applications alongside supporting services.

Here are several key features of CaaS.

• Scalability. CaaS offers the flexibility to scale containerized applications quickly and automatically, based on real-time demand, without manual intervention.
• Automation. With built-in automation for tasks like deployment, networking, and load balancing, CaaS platforms minimize manual effort and reduce the chances of errors.
• Security. CaaS platforms provide a secure environment for running containers, with features like isolated execution, role-based access control, and encryption to protect sensitive data and ensure compliance.

CaaS platforms typically integrate with popular container orchestration tools such as Kubernetes, Docker Swarm, or Apache Mesos. These tools automate the deployment, scaling, and management of containerized applications and ensure smooth and efficient operations.

CaaS is particularly well-suited for deploying microservices applications because each container operates independently, with its own operating system, codebase, and pre-configured network protocols. This self-contained structure allows near-instantaneous deployments, streamlining the process and reducing downtime.

In addition, you can use CaaS in the following cases:

• Legacy application modernization. CaaS helps businesses modernize their legacy applications by containerizing them, making integrating with modern technologies and migrating to the cloud easier.
• AI-driven applications and machine learning tasks. CaaS is an excellent choice for running applications that involve machine learning models and AI-driven processing workloads. It supports resource-intensive tasks like training and inference. Portability ensures consistency between training and deployment environments, and dynamic scaling supports resource-heavy workloads.
• Hybrid cloud and multi-cloud deployments. CaaS platforms, such as Kubernetes, allow applications to be easily moved between cloud environments, whether on-premises, public cloud, or multiple cloud providers.

However, you should note that containers introduce additional layers of management and complexity. For small-scale or static workloads, VMs or even bare-metal servers can be more cost-effective and easier to manage.

Platform as a Service (PaaS) is a comprehensive cloud computing model that provides developers with all the tools and resources needed to build, test, deploy, and manage applications without worrying about the complexities of managing the underlying infrastructure. Today, PaaS accounts for about 20% of the overall cloud services market.

PaaS offerings include security features like authentication, encryption, and application monitoring. They also come with pre-configured tools for application development, such as code editors, compilers, version control systems, and multi-tenant capability, which reduce the amount of coding developers must do. With PaaS, developers only need to manage the applications and services they develop, and the cloud service provider typically manages everything else.

IaaS and PaaS are powering current use cases for 72% of companies worldwide. Here are some of the most prominent examples of PaaS usage.

• Rapid app development. One primary use case for PaaS is its ability to accelerate the development lifecycle, as PaaS eliminates the need to set up and manage underlying infrastructure. It also includes middleware like databases (MySQL, PostgreSQL) and pre-configured application servers for immediate use. All these features make it highly suitable for teams working in agile environments where iterative development and testing cycles are frequent.
• Cross-platform development. Modern applications often must run across multiple platforms, including web browsers, mobile devices (iOS/Android), and desktops. PaaS provides a unified development environment, enabling developers to efficiently create, test, and deploy cross-platform apps. PaaS supports frameworks like React Native and Flutter for building apps with shared codebases across platforms and offers numerous SDKs.

While PaaS abstracts the underlying infrastructure to simplify application development, you should evaluate your business’s specific needs to determine whether PaaS will be suitable for your particular settings.

For instance, infrastructure abstraction can limit control over system configurations, hardware, and operating systems. This lack of flexibility can be a drawback for applications that require custom setups or direct interaction with hardware. Also, the subscription fees for advanced PaaS services can be prohibitive for small-scale or short-term projects.

Serverless computing is a distinct cloud service model that doesn’t fit neatly into the formal categories of IaaS or PaaS but overlaps with them in specific ways. However, it’s most commonly associated with Function as a Service (FaaS) and is considered an evolution of PaaS.

Unlike PaaS, which provides a platform with integrated development tools, frameworks, and environments for building and deploying applications, serverless architecture focuses on running individual functions or pieces of logic without needing to deploy an entire application.

In this model, the cloud provider dynamically allocates and manages server resources, executing code only when triggered by specific events. This “on-demand” execution model enables developers to focus solely on writing code while the cloud provider handles server provisioning, scaling, and maintenance.

The 2022 CNCF Annual Survey reports a massive uptake in FaaS adoption, rising from 30% in 2020 to 53% of companies using serverless architecture. Significant cost savings are the main reason companies choose FaaS. With serverless computing, you pay only for the compute resources your code uses during execution, which, in turn, eliminates costs for idle infrastructure. This means zero idle costs as serverless functions are event-driven and automatically scale up or down without manual intervention.

Deloitte states that serverless applications can reduce development costs by 68% by allocating compute resources on a pay-for-use basis. Yet, serverless isn’t a one-size-fits-all approach. It is typically used for lightweight, short-lived, event-driven tasks, making it an excellent complement to microservices. Here are several use cases:

• Lower (non-production) environments. The benefits of serverless services become even more evident when a company has multiple environments (e.g., PROD, UAT, TEST, DEV). Lower environments refer to non-production environments (UAT, TEST, DEV) that are primarily used for testing, development, and staging before deploying to production. These environments typically have lower workloads, and with FaaS, they can often run at little to no cost. Even though serverless may entail higher production costs, the overall expenses can still be substantially lower compared to other hosting solutions.
• Event-driven automation. Serverless computing is perfect for triggering automated workflows based on specific events, such as file uploads, database changes, or user actions. It seamlessly integrates with storage services (e.g., Amazon S3) to execute code whenever an event occurs. Serverless also supports event-driven tools like AWS EventBridge or Azure Event Grid to route and manage triggers.
• Scheduled tasks and batch jobs. Serverless functions are excellent for scheduled operations, such as database cleanups, report generation, or periodic data synchronization. They can quickly execute short-duration tasks, minimizing costs compared to running dedicated servers for periodic jobs.

Yet, despite all the benefits, serverless functions have execution time limits, making them unsuitable for processes requiring long durations.

Software as a Service (SaaS) is a cloud computing model that delivers software applications over the Internet on a subscription or pay-as-you-go basis. With SaaS, users access applications through a web browser or a dedicated client interface, eliminating the need to install, maintain, or upgrade software locally. Instead, the service provider handles all aspects of infrastructure, software updates, and security.

SaaS usually operates on a multi-tenant or a single-tenant architecture. The key difference between them lies in resource sharing, customization, and cost efficiency.

In a multi-tenant architecture, multiple users (tenants) share the same infrastructure and application instance while maintaining data isolation. The software is hosted on the provider’s servers, with users connecting via APIs or web interfaces. This model is highly cost-effective, as maintenance, updates, and scaling are handled centrally by the provider, reducing overhead for individual users. However, customization and performance control may be limited due to shared resources.

In contrast, a single-tenant architecture provides each customer with a dedicated instance of the software (a so-called white-label solution). Since resources are not shared, businesses with strict compliance requirements or specific performance needs may prefer this model. However, it also comes with higher costs for the provider, as maintaining separate instances for each customer requires additional infrastructure and operational effort.

SaaS startups received over $30 billion in VC investment in 2022. Their growth is powered by the growing need for ready-to-use applications in various niches and spheres. However, this cloud service model can offer limited use cases for companies building their software. Here are some of them.

• Preconfigured solutions for standard business processes. SaaS is an excellent choice for companies with straightforward workflows or processes that don’t require extensive customization. For example, businesses can use SaaS tools for standard needs like email management (e.g., Gmail or Outlook), or project collaboration (e.g., Trello or Asana). These platforms come preconfigured with easy-to-use interfaces and features that address everyday operational needs.
• Quickly fill operational gaps. SaaS platforms can be helpful for businesses that need to address specific challenges or gaps in their operations without committing to long-term infrastructure investments. For example, a company that requires temporary customer support during seasonal peaks can deploy SaaS-based contact center solutions like Zendesk or Freshdesk.
• Collaboration and remote work. The shift to hybrid and remote work has made SaaS collaboration tools crucial. Platforms such as Microsoft Teams, Google Workspace, and Zoom enable teams to stay connected, share files, and collaborate in real-time.

SaaS applications are typically designed for broad use cases, which means their features and workflows may not align perfectly with a company’s unique requirements. While many platforms offer some level of configuration, they rarely allow deep customization. For businesses in highly specialized industries or with unique operational workflows, building a tailored SaaS solution can be a more effective approach.

At Leobit, we build custom SaaS applications from the ground up, ensuring they meet your specific business needs or those of your audience. Our expertise covers multiple industries, with successful SaaS development cases spanning healthcare, logistics, fintech, sportstech, media and entertainment, proptech and real estate, construction, and other industries.

Here’s a comparison table of the basic cloud service models, highlighting their peculiarities.

Selecting the right cloud service model is a crucial decision that can significantly impact your cloud migration. Each model provides a unique level of control, flexibility, and management. Evaluating your specific needs against each option’s offerings can help you use the cloud more effectively.

However, you don’t need to stick to just one service model. Combining different cloud service models can help you optimize performance and achieve cost efficiency.

Below are the key points to consider when choosing one or a combination of cloud service models.

Start by evaluating the nature of the workload you want to move to or build in the cloud. Each workload has distinct requirements regarding computing power, storage, scalability, and security, which directly influence the suitability of a cloud service model.

Here are a few suggestions.

• IaaS is ideal for compute-intensive workloads requiring significant processing power, such as big data analytics and AI/ML models, or storage-heavy workloads, such as video streaming, backup systems, or content management.
• CaaS works best for containerized applications and microservices architectures.
• PaaS is well-suited for development environments where rapid application building, testing, and deployment are priorities.
• FaaS is excellent for lightweight, event-driven workloads such as APIs, IoT applications, and real-time data processing.
• SaaS works great for straightforward business processes like customer communication, sales management, and team collaboration. These solutions are designed to efficiently address specific business challenges, providing ready-to-use tools without the need for complex setup or maintenance.

Clearly understanding your workload ensures you choose a model/models that align with your operational needs.

Control encompasses access to the underlying infrastructure, customization capabilities, and the ability to manage security settings, scaling, and configurations. Each cloud service model offers varying degrees of control, so it’s important to match your requirements to the features they offer.

• IaaS offers maximum control over servers, storage, networking, and operating systems. This makes it suitable for businesses with complex configurations or legacy systems.
• CaaS allows detailed control over container orchestration and scaling but abstracts away hardware management.
• PaaS provides control over applications and development tools but abstracts away infrastructure management, making it easier to focus on coding and application design.
• FaaS requires minimal control; developers only focus on function logic, while the provider handles all infrastructure and runtime.
• SaaS requires the least control when using a ready-made solution, as you only manage data and configurations, while the provider handles updates, infrastructure, and security. However, if you build your own SaaS product, you take on more responsibility, including development, customization, and ongoing maintenance.

By determining the level of control your business requires, you can better align your choice of cloud service model with your operational and strategic goals. This clarity also helps in combining models effectively.

Cost is a major consideration when selecting a cloud service model and provider. While cloud computing is often praised for its cost-efficiency and scalability, misjudging or underestimating your budgetary needs can lead to overspending or an underperforming solution. By thoroughly evaluating your budget, you can strike the right balance between affordability, functionality, and scalability.

Cloud service costs vary widely based on the model:

• IaaS typically involves variable costs based on usage, including compute power, storage, and networking.
• CaaS pricing is tied to container usage, orchestration, and scaling, which can fluctuate based on workload demands.
• PaaS is often cost-effective for development teams due to pre-configured environments, but costs can escalate with high usage or add-ons.
• FaaS follows a pay-per-execution model, making it highly cost-efficient for workloads with sporadic or variable demand.
• SaaS is generally affordable on a subscription basis, with predictable costs but limited flexibility.

When evaluating your budget, look beyond initial costs and consider the total cost of ownership (TCO) over time. TCO includes upfront costs (i.e., fees for setup, configuration, and initial migration) and ongoing costs (i.e., subscription fees, resource usage, maintenance, and scaling). There could also be unexpected expenses, such as overprovisioning, egress charges (data transfer out of the cloud), and additional tools or services for monitoring and security.

Once you understand the costs, you should also implement strategies to maximize cost efficiency of the chosen models.

Scalability in cloud computing can be categorized into two primary types:

• Vertical scalability (scaling up) involves adding more power to existing resources, such as upgrading a server’s CPU, memory, or storage capacity. Vertical scaling is useful for applications with predictable growth or workloads requiring higher performance but fewer resources, like databases.
• Horizontal scalability (scaling out) entails adding more resources, such as additional servers or instances, to distribute the workload. Horizontal scaling is ideal for applications with fluctuating traffic.

Each cloud service model supports scalability differently.

• IaaS is highly scalable, but scaling requires manual intervention and management.
• CaaS is excellent for dynamic scalability as containers can be easily added, removed, or managed in response to demand.
• PaaS offers built-in scalability, which simplifies growth without requiring significant user input.
• FaaS is designed for automatic scaling, responding instantly to demand spikes or decreases.
• SaaS has limited scalability since resources are predefined by the provider.

Match your scalability requirements with the service model’s capabilities to avoid performance bottlenecks or overpaying for unused resources.

The shared responsibility model is a guiding principle in cloud computing. While providers ensure the security of the cloud infrastructure, businesses are responsible for securing their data, applications, and access management. The division of responsibilities varies by service model:

• IaaS requires businesses to implement their own security protocols, including firewalls and encryption. Ideal for industries with strict compliance needs (e.g., healthcare or finance).
• CaaS security depends on the configuration of containers and orchestration tools. A misconfigured container can lead to vulnerabilities.
• PaaS offers a shared responsibility model in which the provider handles infrastructure security, but application-level security is up to the user.
• FaaS built-in security features are provided, but the function code must be secure to avoid potential risks.
• SaaS providers typically offer built-in security, including encryption, access controls, and regular security updates. However, data privacy and compliance remain key concerns because businesses should ensure that sensitive information is stored, processed, and transmitted

Also, you should note that guaranteeing security and compliance may involve additional costs, including licensing fees for specialized encryption or compliance tools.

You can take these steps alone or hire an experienced cloud development company that would help you align your business needs with the appropriate cloud service model. Keep in mind that, in many cases, combining multiple service models allows achieving a balance between flexibility, functionality, and cost efficiency.

Choosing the right cloud service model is a critical decision that impacts your business’s efficiency, scalability, and overall success in the digital age. Each cloud model offers distinct advantages and caters to specific needs, from infrastructure control and application development to seamless software delivery and event-driven computing.

The key to making the right choice lies in understanding your workload requirements, evaluating your team’s expertise, and aligning your selection with your business goals and budget. For example:

• If you’re looking for the ultimate control over your infrastructure to host complex systems or manage large-scale data, IaaS offers the perfect blend of flexibility and scalability you need.
• For organizations adopting microservices or containerized architectures, CaaS offers a robust environment for managing and scaling container workloads.
• For accelerating development cycles or using pre-configured tools, PaaS is an excellent choice, enabling developers to focus on innovation rather than infrastructure management.
• If your workload involves event-driven, on-demand operations, FaaS provides a cost-effective and highly scalable solution.
• Finally, businesses with straightforward processes or those looking for ready-to-use solutions can benefit most from SaaS.

It’s also essential to consider hybrid and multi-cloud strategies for businesses with diverse workloads or those aiming to mitigate vendor lock-in. Combining different service models, such as using IaaS for infrastructure-heavy tasks and FaaS for lightweight, event-driven functions, can create a tailored cloud environment that meets your unique needs.

The cloud landscape is constantly evolving, with new service models and capabilities emerging to address previously unmet challenges. Leobit can carefully evaluate your workload type, control requirements, and scalability demands to help you choose the cloud service model, or combination of models, that delivers the most value to your business. Contact us, and we’ll gladly consult you further on the topic.