Serverless computing and Platform-as-a-Service (PaaS) both abstract infrastructure management, but they differ in how they handle scaling, cost, and operational control. Serverless platforms, like AWS Lambda or Azure Functions, remove the need to manage servers entirely. Developers deploy code (often as individual functions) that runs on-demand, triggered by events such as HTTP requests or database changes. The platform automatically scales instances to match incoming requests and charges only for the time the code executes. PaaS, such as Heroku or Google App Engine, simplifies deploying applications by handling underlying servers and runtime environments, but developers still configure scaling rules, manage dependencies, and maintain the application’s runtime state. PaaS typically requires defining resource allocation (e.g., number of instances) upfront, even if traffic fluctuates.
A key distinction lies in scalability and cost structure. Serverless platforms scale to zero when there’s no traffic, meaning no costs are incurred during idle periods. For example, an AWS Lambda function runs only when triggered, with billing per millisecond of execution. PaaS, however, often requires at least one active instance to keep the application available, leading to baseline costs even during low usage. Additionally, serverless functions have execution time limits (e.g., 15 minutes for Lambda), making them unsuitable for long-running tasks. PaaS environments, like Heroku’s dynos, can handle sustained workloads since they’re designed for applications that run continuously. This makes PaaS better suited for traditional web apps with steady traffic, while serverless excels for event-driven tasks like processing file uploads or handling API requests sporadically.
Use cases also differ. Serverless is ideal for stateless, short-lived operations that benefit from automatic scaling and pay-per-use pricing. For example, a serverless function could resize images when a user uploads a file to cloud storage. PaaS is better for applications requiring persistent state, longer processing times, or more control over the runtime environment. A PaaS like Heroku might host a Node.js API that maintains database connections and uses in-memory caching. While both models reduce infrastructure overhead, serverless shifts more responsibility to the provider (e.g., scaling, patching) and enforces stricter constraints, whereas PaaS offers a middle ground between serverless and traditional hosting, allowing developers to retain some configuration flexibility without managing physical servers.