This post describes configurable tolerance for horizontal Pod autoscaling, a new alpha feature first available in Kubernetes 1.33.
What is it? Horizontal Pod Autoscaling is a well-known Kubernetes feature that allows your workload to automatically resize by adding or removing replicas based on resource utilization.
Let's say you have a web application running in a Kubernetes cluster with 50 replicas. You configure the HorizontalPodAutoscaler (HPA) to scale based on CPU utilization, with a target of 75% utilization.

Kubernetes is an open-source container orchestration platform for automating the deployment, scaling, and management of containerized applications. With Kubernetes, developers can deploy applications across clusters of machines, ensuring high availability, scalability, and resilience. Developers can learn about Kubernetes' architecture, core concepts, and deployment strategies, and gain hands-on experience with managing containerized workloads using Kubernetes.

Kubernetes

Kubernetes v1.33 introduces a new alpha feature, Configurable Tolerance for Horizontal Pod Autoscaling (HPA), allowing users to fine-tune tolerance settings for replica scaling based on resource utilization. By adjusting the scaleUp and scaleDown tolerances, users can better manage large deployments, reduce unwanted scaling actions, and optimize resource usage in response to CPU fluctuations. This feature can be enabled through the HPAConfigurableTolerance feature gate.

Kubernetes v1.33: HorizontalPodAutoscaler Configurable Tolerance