Serverless computing and Platform as a Service (PaaS) are both cloud computing models that provide developers with ways to build and deploy applications without managing the underlying infrastructure. However, they differ in terms of management, scalability, and cost structure. In serverless computing, developers write code that is executed in response to events, and they are charged based on the compute time consumed by that code. In contrast, PaaS provides a platform that includes everything needed to develop, run, and manage applications, allowing developers to focus more on coding and less on managing the environment.
One key difference lies in how resources are allocated and billed. In serverless computing, such as AWS Lambda or Azure Functions, users don't have to provision or manage servers. Instead, they define functions that respond to specific triggers. For example, when a file is uploaded to a cloud storage service, a function could process that file automatically. Users only pay for the amount of time their code runs, making it potentially more cost-effective for applications with variable workloads. On the other hand, PaaS offerings like Heroku or Google App Engine let developers deploy applications on predefined platforms. Users typically pay for reserved resources like CPU and memory, regardless of whether those resources are fully utilized at all times.
Another difference is in scalability. Serverless platforms automatically scale to match demand, handling spikes in usage without extra configuration. For instance, if a function experiences an unexpected surge of requests, the serverless architecture will spin up more instances to meet that demand instantly. In contrast, with PaaS, while applications can scale, developers often need to manage or configure the scaling parameters. This difference in scalability can influence how developers design their applications based on expected usage patterns and load requirements.