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How It Works
Azure Kubernetes Service abstracts the complexity of running Kubernetes, which is an open-source system for automating the deployment and scaling of containerized applications. With AKS, Microsoft manages the Kubernetes control plane, meaning the layer responsible for scheduling workloads and maintaining cluster state. You provision worker nodes, which are the virtual machines that run your containers, and AKS handles upgrades, patching, and availability of the underlying orchestration layer. Worker nodes run on Azure Virtual Machines, so the compute cost of an AKS cluster is driven by the VM series and sizes you select for those nodes.
Why It Matters for Cloud Cost
AKS clusters often represent a significant share of Azure compute spend, because worker nodes run continuously to maintain application availability and response time. Teams frequently over-provision node pools to handle traffic spikes, which leaves idle capacity running at full on-demand rates. Without a commitment strategy applied to the underlying VM compute, that baseline capacity is never discounted. Azure Savings Plans cover AKS compute, meaning the VMs running your Kubernetes worker nodes are eligible for commitment-based pricing that can reduce costs by up to 65% versus on-demand rates. The equivalent commitment mechanism on AWS is the Compute Savings Plan, which covers EKS worker nodes; on GCP, Committed Use Discounts cover GKE compute. Without applying one of these mechanisms to your baseline node capacity, you pay full on-demand pricing for workloads that run predictably around the clock.
Usage AI: Usage AI optimizes Azure Savings Plans that cover AKS compute, purchasing and managing commitments on your behalf so your Kubernetes worker node costs are reduced without any infrastructure changes or upfront spend.