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How It Works
With IaaS, a cloud provider owns and operates the physical hardware in its data centers. Customers rent access to that hardware as virtual resources: servers (compute), disk (storage), and connectivity (networking). The customer is responsible for everything above the hardware layer, including the operating system, middleware, runtime, and applications. AWS, Azure, and GCP are the three dominant IaaS providers. On AWS, EC2 is the primary compute service. On Azure, the equivalent is Azure Virtual Machines. On GCP, it is Compute Engine. Customers provision resources through a console or API and pay only for what they use, with no upfront capital expenditure required.
Why It Matters for Cloud Cost
IaaS removes the need to purchase and maintain physical servers, which reduces capital spending and shifts infrastructure cost to an operational budget. That flexibility, however, creates a different financial challenge. Resources are provisioned quickly and costs accumulate continuously, whether or not the resource is actively used. Teams that over-provision compute or leave instances running after a workload ends generate waste that compounds month over month. Because IaaS pricing is consumption-based, the gap between what a company provisions and what it actually needs is where most cloud overspend originates. Managing that gap, through rightsizing, scheduling, and commitment-based discounts, is the core discipline of cloud cost optimization.
Usage AI’s Autopilot autonomously purchases and adjusts commitment-based discounts across AWS, Azure, and GCP daily, without requiring human approval, at zero upfront cost and with no financial risk to the customer.