1/18/2023 0 Comments What is kubernetes hpa![]() ![]() HPA will calculate the required number of replicas on the basis of collected resource usage.ģ. Horizontal Pod Autscaler keeps monitoring the metrics server for resource usage.Ģ. Here’s how each of the steps in that loop work:ġ. In simpler words, HPA works in a ‘check, update, check again’ style loop. ![]() How does a Horizontal PodAutoscaler work? With the controller, one can periodically adjust the number of replicas in a deployment or replication controller to match the observed average CPU utilization to the target specified by the user. HPA is implemented as a Kubernetes Application Programming Interface (API) resource and a controller. Scaling can be done only for scalable objects like controller, deployment, or replica sets. Kubernetes has the possibility to automatically scale pods based on observed CPU utilization which is horizontal pod autoscaling. The Kubernetes Horizontal Pod Autoscaling automatically scales the number of pods in a replication controller, deployment, or replica set based on that resource’s CPU utilization. Kubernetes Horizontal Pod Autoscaling (HPA) : It schedules, runs, and manages isolated containers running on virtual, physical, and cloud machines. Kubernetes is an open-source container management tool that automates container deployment, container scaling, and load balancing. So, without further ado, let’s get started! What is Kubernetes? ![]() But before that, let’s first understand what is Kubernetes. We’ll define HPA, explain how it works, and provide a detailed tutorial to configure HPA. In this article, we will take a deep dive into the topic of Horizontal Pod Autoscaling in Kubernetes. This type of autoscaling does not apply to objects that can’t be scaled. HPA can help applications scale out to meet increased demand or scale in when resources are no longer needed. One of the ways in which Kubernetes enables autoscaling is through Horizontal Pod Autoscaling. It is a feature wherein the cluster can increase the number of pods as the demand for service response increases and decrease the number of pods as the requirement decreases. Once configured correctly, it saves administrators’ time, prevents performance bottlenecks, and helps avoid financial waste. Autoscaling is one of the prominent features of the Kubernetes cluster.
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