.png)
How It Works
When demand grows, a horizontally scaled system spins up additional instances of the same size to share the workload. A load balancer distributes incoming traffic across all running instances. When demand drops, instances are terminated to reduce cost. This approach contrasts with vertical scaling, which replaces a smaller instance with a larger one. Most modern cloud architectures favor horizontal scaling because it avoids the downtime often required to resize a single instance, and because many cloud services are designed to run workloads across fleets of smaller machines rather than one large one.
Why It Matters for Cloud Cost
Horizontal scaling directly affects how you plan and purchase compute commitments. When your workload runs on a fleet of smaller, uniform instances, a predictable baseline of those instances can be covered with Reserved Instances or Savings Plans at significant discounts compared to on-demand rates. AWS offers up to 72% off on-demand pricing with Reserved Instances, Azure Reservations offer up to 72%, and GCP Committed Use Discounts offer up to 57%. The challenge is that horizontal scaling also introduces variability: the fleet size changes as load fluctuates, making it harder to know exactly how much capacity to commit to. Over-committing wastes money on unused reservations; under-committing leaves savings on the table.
Usage AI’s Autopilot mode purchases and adjusts commitments daily without human approval, helping teams maintain coverage across a dynamic EC2, Fargate, and Lambda fleet through the Usage Flex Savings Plan, which saves 40 to 60% versus on-demand.