Azure offers multiple cloud service models; Infrastructure-as-a-Service (IaaS), Platform-as-a-Service (PaaS), and Software-as-a-Service (SaaS), each defined by who manages what.
The real difference comes down to how much control, speed, cost, and operational responsibility you’re willing to trade off.
In this article, we’ll briefly explain IaaS, PaaS, SaaS (and serverless) on Azure and help you choose the right model for your workload.
Reading time 9 minutes Published: 17 April 2026
KEY POINTS:
IaaS, PaaS, and SaaS are the core building blocks of cloud computing, often grouped under the umbrella of “Everything-as-a-Service” (XaaS).
These models define how technology is delivered, and who is responsible for managing it.
At a high level, “as-a-service” means you access IT resources over the internet instead of owning and running them yourself. As you move from IaaS to PaaS to SaaS, the provider takes on more responsibility, while you trade some control for greater speed, simplicity, and reduced operational effort.
See how the (shared) responsibilities differ for each cloud service model below:
The higher you move in the stack, the more Microsoft operates on your behalf. Your responsibilities shift toward configuration, identity management, access control, and data handling. However, you always retain responsibility for parts of security and configuration.
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Microsoft Azure Fundamentals for ISVsInfrastructure as a Service (IaaS) is renting the building blocks: compute, storage, networking. On Azure, think virtual machines, disks, virtual networks, and load balancers. Microsoft runs the physical data centre and the underlying hardware. You still manage the operating system, patching, and most of the configuration.
“Everything else is built on it. It’s basically what we used to do in on-prem data centers: virtual machines, disks, networking, operating systems.”
Wesley Haakman, Principal Azure Architect & Microsoft MVP
Use IaaS when you genuinely need deep control, or when you need to move quickly without rewriting everything.
Typical Azure IaaS patterns:
IaaS gives you the most control and the most responsibility: patching, configuration, availability, backups, and disaster recovery.
Common scenarios when IaaS is used are:
Platform as a Service (PaaS) provides a managed platform for running your app, eliminating the need to manage the underlying servers. You usually keep control over your application, data, and configuration, while Microsoft handles more of the “under the hood” platform work.
PaaS shines when you want to spend less time on platform upkeep and more time on features.
Common choices:
Some compare a single VM to a PaaS service and conclude PaaS is “more expensive”. That comparison usually ignores what you had to build around the VM (availability, load balancing, patching, scaling, monitoring, backup processes). The numbers might appear higher on a cloud invoice, but the actual cost is lower because your team spends less time managing the platform.
Azure SQL is a great example. One database may cost more than running SQL on a VM, but you get features like elastic pools, automated backups, and platform resiliency; things you can’t easily replicate on-prem.
Some common scenarios where PaaS might make sense include:
Software as a Service (SaaS) is the finished product. You sign in and use it. Updates, availability, and the core service operation are handled by the provider. Your focus is identity, access, data, and how you use the software. Microsoft 365 is the obvious example.
SaaS is often defined by the experience (browser login, subscription model, features delivered continuously), not by what is running behind the scenes.
Examples of SaaS solutions:
SaaS is also where people can get complacent. You might have “no control whatsoever” over the service internals, yet you still control user access and how data is handled. Ignore that, and SaaS also becomes quite risky.
Common scenarios for SaaS include:
Serverless often sits between PaaS and “pure code”. It deserves its own call-out because it changes the cost model and the architecture style. Serverless is where you push your code and the platform handles provisioning and scaling.
Microsoft describes serverless computing as: “Serverless is event-driven, with the cloud platform provisioning and scaling infrastructure for you.”
There's no “fixed path” for choosing between cloud computing models. You pick what is fit for purpose, according to the workload.
Microsoft’s Cloud Adoption Framework (CFA) makes the same point in a more structured way, recommending you choose a migration strategy per workload: Rehost, Refactor, Rearchitect, Rebuild, and Replace.
Additionally, consider the amount of control, speed, cost, and risk for your situation, as each cloud service model comes with different responsibilities:
Before selecting a cloud service model, consider your workload and understand business context, including industry, compliance requirements, data sensitivity, operational maturity, and support expectations. These factors all influence the optimal choice.
Most mature Azure estates end up mixed, which often turns out to be the most sensible way to move quickly without painting yourself into a corner. A lift-and-shift workload might reside on IaaS, while the rest is moved to PaaS. You choose per workload, not per ideology.
Do you need more help in Azure, or would you like to know how Intercept, as a cloud specialist, can assist you in setting up the right environment? Contact us!