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Karpenter vs. Cluster Autoscaler — Kubernetes Scaling Tools
Kubernetes has become one of the standard container orchestration systems. As applications running on Kubernetes clusters face varying workload demands, the ability to automatically scale resources becomes a critical requirement for modern cloud-native architectures.
Kubernetes offers several approaches to handling these scaling needs, with two solutions emerging for cluster-level scaling: the traditional Kubernetes Cluster Autoscaler and the newer, more sophisticated Karpenter. Although both tools serve the fundamental purpose of automatically adjusting cluster capacity, they differ significantly in their approach and implementation.
This article compares these autoscaling solutions, exploring their architectures, differences, and use cases.
Kubernetes autoscaling basics
In Kubernetes, containers and pods spin up and down constantly, so efficient resource management is crucial for performance and cost optimization. Before discussing each solution's specifics, let’s review the basics of Kubernetes autoscaling.
Scaling Kubernetes workloads
Kubernetes provides two layers of autoscaling to handle different aspects of resource management. The first layer includes autoscaling at the…