PaaS (Platform as a Service)

How It Works

With PaaS, the cloud provider manages the operating system, runtime, middleware, and networking layers. Developers upload their application code and configuration, and the platform handles the rest. AWS Elastic Beanstalk, Azure App Service, and Google App Engine are common PaaS examples. The developer focuses on writing application logic. The provider handles patching, scaling, and availability of the underlying platform.

Why It Matters for Cloud Cost

PaaS removes operational overhead, but it introduces a different cost challenge. Pricing is typically tied to compute hours, memory, and request volume, and costs can climb quickly if usage patterns are unpredictable or environments are left running without active workloads. Because PaaS abstracts the infrastructure layer, teams often have less visibility into the compute resources actually consumed, which makes it harder to right-size spending or apply commitment-based discounts at the resource level. Services like AWS Lambda and Azure App Service have their own pricing models, and optimizing them requires understanding how each platform meters usage.

Usage AI includes showback support and ClearCost reporting across AWS, GCP, and Azure, giving finance and engineering teams visibility into cloud spend across services.

See how Usage AI saves 30 to 50% on AWS, GCP, and Azure.