Karpenter is a fast, flexible Kubernetes autoscaler designed to improve cluster performance and cost efficiency. When the cluster doesn’t have capacity to schedule a pod, Karpenter requests additional compute from the cloud provider, specifying a right-sized instance that matches the preferences you’ve set (for example, instance family). Karpenter can also reduce node count to mitigate cluster idle and minimize costs by consolidating workloads onto fewer instances and requesting termination of the abandoned instances.
Karpenter was originally developed by AWS and is supported in Amazon EKS, and its adoption is rapidly expanding as support emerges for other public clouds. As of 2025, it has become the preferred autoscaling solution over the traditional Cluster Autoscaler (CAS).
In this post, we’ll cover the core concepts of Karpenter’s architecture. We’ll explore how Karpenter optimizes cost efficiency and how it compares to traditional Kubernetes autoscaling. But first, we’ll look at the capabilities that enable Karpenter to optimize the performance and cost of your Kubernetes clusters.
Karpenter’s configuration model
Karpenter’s configuration is built around a clear separation of concerns. Policies that determine Karpenter’s provisioning and optimization behavior are configured in one Kubernetes custom resource—a provider-agnostic NodePool. Specific infrastructure details that determine how Karpenter launches nodes in your cloud environment are configured in a separate custom resource—a provider-specific NodeClass. Dividing this logic across two separate custom resources enables Karpenter to flexibly and efficiently provision compute capacity that ensures application performance within your infrastructure’s operational constraints.
