IaaS, PaaS, SaaS: What Are They and How to Choose?

What are IaaS, PaaS, and SaaS?

IaaS, PaaS, and SaaS are the three fundamental service models of cloud computing, defined by NIST (National Institute of Standards and Technology). They represent a pyramid of increasing abstraction levels: IaaS provides basic infrastructure building blocks, PaaS offers a development and execution platform, and SaaS delivers complete ready-to-use applications.

To understand these models, consider a culinary analogy. IaaS is like renting an equipped kitchen: you have the utensils and stove, but you cook yourself. PaaS is a meal kit delivery service: ingredients are prepared, you just assemble and cook. SaaS is ordering a dish at a restaurant: everything is done for you, you just eat.

At Kern-IT, we primarily work with IaaS and PaaS for deploying our clients' Django applications. Our applications are deployed on Linux servers (IaaS) or via managed services like Azure App Service (PaaS), depending on the level of control and customisation required by the project. We also develop custom SaaS solutions for clients who want to offer their own software as a service.

Why Understanding IaaS, PaaS, and SaaS Matters

Choosing the right cloud service model directly impacts costs, operational complexity, time-to-market, and technical flexibility. A poor understanding of these models often leads to suboptimal choices.

• IaaS (Infrastructure as a Service): you rent the basic infrastructure — virtual servers, storage, networking — and manage everything else: operating system, middleware, runtime, application, and data. This model offers the most control but also the most responsibility. Examples: AWS EC2, Azure Virtual Machines, Google Compute Engine.
• PaaS (Platform as a Service): the provider manages infrastructure, operating system, middleware, and runtime. You only manage your application and data. This model considerably accelerates development and reduces operational burden. Examples: Heroku, Azure App Service, Google App Engine, AWS Elastic Beanstalk.
• SaaS (Software as a Service): the provider manages everything from infrastructure to application. Users access the software through a web browser and pay a subscription. Examples: Gmail, Slack, Salesforce, Microsoft 365.
• Cost optimisation: IaaS requires an operations team to manage infrastructure, PaaS reduces this burden, and SaaS eliminates it entirely. Choosing the right model aligns costs with the team's available skills.

How It Works

The three models are distinguished by the level of shared responsibility between the cloud provider and the customer. Let us imagine deploying a Django application on each of these models.

With IaaS, you provision a virtual machine (EC2, Azure VM), install Linux, configure Python, install dependencies, deploy the application with Nginx and Gunicorn, manage system updates, backups, and security. You have total control but also full operational responsibility.

With PaaS, you push your code to the service (Azure App Service, Google Cloud Run, Heroku). The platform automatically handles provisioning infrastructure, installing dependencies, configuring the web server, and managing updates. You only manage your code and database. Deployment goes from hours to minutes.

SaaS represents the end product: a complete application accessible via the web. When Kern-IT develops a business platform for a client and offers it in SaaS mode, end users do not need to worry about infrastructure, deployment, or maintenance. They simply use the application through their browser.

Concrete Example

At Kern-IT, we illustrate these three models in our daily practice. For a client requiring total control over their infrastructure (financial sector with strict regulatory requirements), we deploy the Django application on a dedicated Linux server (IaaS) with Docker, Nginx, and Gunicorn. Deployment is automated via Fabric, and we manage system updates and backups.

For a startup wanting to launch their MVP quickly, we favour PaaS. The Django application is deployed on Azure App Service or Google Cloud Run, with a managed PostgreSQL database. The client team can focus on the product without worrying about infrastructure. Moving from IaaS to PaaS typically reduces operational costs by 40-60%.

When we develop a complete business platform — real estate management, patient portal, fleet management tool — we offer it in SaaS mode to our clients, who access the application via a simple browser with a monthly subscription.

Implementation

1. Assess needs: analyse the required level of control, team skills, budget, and regulatory constraints. The smaller the team, the more relevant PaaS or SaaS becomes.
2. Choose the right model: IaaS if you need total control and have an operations team. PaaS if you want to accelerate development and reduce operational burden. SaaS if an existing solution already meets your need.
3. Select the provider: compare AWS, Azure, and Google Cloud offerings for IaaS and PaaS. For SaaS, evaluate market solutions before building custom.
4. Plan the migration: if migrating between models (e.g., from a dedicated server to PaaS), plan application containerisation, data migration, and DNS changeover.
5. Plan for evolution: your initial choice is not permanent. Many projects start on PaaS for speed, then migrate to IaaS when the need for customisation grows.

Associated Technologies and Tools

• IaaS: AWS EC2, Azure VM, Google Compute Engine, OVH, Hetzner.
• PaaS: Heroku, Azure App Service, Google Cloud Run, AWS Elastic Beanstalk, Railway.
• SaaS: Microsoft 365, Salesforce, Slack, business platforms developed by Kern-IT.
• Docker: containerisation facilitating portability between IaaS and PaaS.
• Terraform: Infrastructure as Code for automating IaaS and PaaS provisioning.

Conclusion

IaaS, PaaS, and SaaS are not exclusive choices but complementary models that adapt to different needs. The right choice depends on the required level of control, team skills, budget, and project constraints. At Kern-IT, we combine these models according to context: IaaS deployment with Docker and Fabric for projects requiring total control, PaaS for startups and MVPs, and custom SaaS development for business platforms. The key is choosing the model that maximises delivered value while minimising operational complexity.