So yesterday, while studying for my Certified Information Systems Security Professional (CISSP) exam, I encountered the terms Platform as a Service (PaaS) and Serverless computing. I had encountered these concepts during my AWS Cloud Practitioner training and worked with both architectures afterwards. Serverless and PaaS are almost the same architecture but with key differences that I hope this piece will help you demystify.
What are Serverless and PaaS?
Serverless computing revolves around individual functions. Developers using Serverless architecture solely focus on writing their piece of code – usually a function – and the cloud service providers will handle the rest of the backend infrastructure including (especially) scaling. In this model, new instances of the functions spin up when invoked by users and shut down when idle An example of a Serverless architecture solution is AWS Lambda.
A Platform as a Service (PaaS) provides broader environment for building and deploying applications. Thus, they oversee provisioning the resources they need based on several factors like expected number of users or calls to the application they are developing. Scaling in PaaS requires a manual intervention of the developer, due to demand spike, for instance, which is different from the complete hands-off approach of the Serverless. An example of PaaS is the Google App Engine or Amazon Elastic Beanstalk.
Now let’s answer some common questions that come up when people try to understand and/or compare these architectures. We will focus on scaling and pricing, and then give some general differences and similarities.
Does Serverless scale better than PaaS?
The short answer is Yes. Serverless architecture scales more seamlessly than PaaS. This is because in Serverless the CSP fully automates scaling. Whereas with PaaS architecture, a developer must provision resources manually, and revisits regularly They must physically configure if the resources should increase during a spike where the developer with the Serverless architecture would need to do nothing and the resources will scale up or down.
Verdict: Serverless wins for effortless scalability.
Which architecture wins pricing – Serverless or PaaS?
Pricing depends on use case. When a company uses Serverless, they get their functions to scale down automatically when there is no call to it without doing anything. But what happens when there is a constant call of the function? The bills continue to accumulate. Whereas a startup using PaaS for their solution would have planned, in advance, the resources that they would consume in advance and get charged for only that.
Verdict: It’s a stalemate – context is king!
Which is more secure – Serverless or PaaS?
Security is at the heart of modern-day development and deployment. PaaS gives more control to the developer while CSPs manage security for developers using the Serverless model. This means that developers using PaaS must ensure they are using the best practices to secure the applications they are deploying for end-users, giving them more control over compliance.
For Serverless users, security is a shared responsibility. While CSPs secure the infrastructure (servers, patching etc.), developers must include security in their code (e.g. input validation, permissions etc.).
Verdict: PaaS wins—its configurability and visibility make it stronger for security-conscious use cases, while Serverless leans heavily on the CSP.
Verdict: PaaS wins. It has more security control
Key differences between Serverless and PaaS
The distinction in both architectures boils down to control, scaling automation and launch time.
Control
With the PaaS architecture, developers have greater control over the deployment environment. Although there is no server management for developers using any of the architectures, developers using the PaaS architecture get access to more tools for finetuning resources such as memory or CPUs.
With a Serverless architecture, the user has no control over the deployment environment, the cloud service provider’s Serverless engine take on the job of managing the deployment environment leaving the developer with zero visibility of the underlying infrastructure. This trade-off yields precise usage-based pricing but sacrifices customization.
Verdict: PaaS wins—it offers greater control for developers who need it, while Serverless sacrifices control for simplicity.
Automating Scale
As stated earlier, with a Serverless solution, functions scale automatically without any extra effort by the developer or business. With PaaS architecture, if a user needs their application to scale up with increased demand and scale down with reduced demand. Thus a scaling rule is needed, say – “add more instances when usage hits 75%”, making it less agile but more configurable.
Verdict: Serverless wins—its automatic, real-time scaling outshines PaaS’ rule-based approach.
Launch time
Serverless architecture takes less time to launch than an application built using the PaaS architecture. This is because Serverless functions are lightweight. Or at least, lighter than PaaS-built applications. Thus, going live immediately they are called. Serverless applications are also helped by the fact that the Serverless engines create instances automatically when a function is invoked.
PaaS applications, being fully-fledged systems, are heavier and take longer to deploy and start. To match Serverless speed, developers might configure PaaS apps to keep instances “warm” (always running), but this increases costs and negates some scaling benefits.
Verdict: Serverless wins—its lightweight nature and instant activation give it the edge, despite occasional cold-start hiccups.
Are Serverless and PaaS rivals?
Serverless and PaaS aren’t rivals—they’re tools for different jobs. Serverless shines for event-driven, short-lived tasks (e.g., processing uploads or API calls), while PaaS suits complex, persistent applications (e.g., web platforms). Both free developers from server management, but Serverless prioritizes simplicity and speed, while PaaS offers control and stability. Understanding your workload—its frequency, duration, and predictability—guides the choice.
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