Support for HorizontalPodAutoscaler in kubectl

The HorizontalPodAutoscaler (HPA) in Kubernetes handles scheduling pod scaling up automatically based on resource use metrics as CPU or memory. Below is an overview of how it operates:

• Create Autoscaler: Kubectl create can be utilized to construct a new HPA in the exact same way that any other resource. This option enables a fast and efficient autoscaler setup.
• List HPAs: Use kubectl get hpa to get all of your current HPAs. Using the assistance of this command, you are able to view the names, target resources, and scaling environments of all of your current autoscalers.
• Describe HPA: Use kubectl describe hpa to secure additional information about a specific HPA. Full details about the autoscaler, including events, metrics, and scaling history, is given by this command.
• Specialized Autoscale Command: In addition, kubectl autoscale, a specialized command created specifically for HPA development, is offered by Kubernetes. This command lets you specify scaling parameters directly, and streamlines the procedure. For example, kubectl autoscale deployment my-app –min=2 –max=5 –cpu-percent=80 creates an autoscaler with a replica count of between two and five and a target CPU utilization of 80% for the my-app deployment.
• Delete Autoscaler: Finally, you may execute kubectl delete hpa to eliminate an autoscaler following you finish using it. By deleting the assigned HPA from your cluster, this procedure guarantees efficient resource management.

The process of automatically scaling in and scaling out of resources is called Autoscaling. There are three different types of autoscalers in Kubernetes: cluster autoscalers, horizontal pod autoscalers, and vertical pod autoscalers. In this article, we’re going to see Horizontal Pod Autoscaler.

Application running workload can be scaled manually by changing the replicas field in the workload manifest file. Although manual scaling is okay for times when you can anticipate load spikes in advance or when the load changes gradually over long periods of time, requiring manual intervention to handle sudden, unpredictable traffic increases isn’t ideal.

To solve this problem, Kubernetes has a resource called Horizontal Pod Autoscaler that can monitor pods and scale them automatically as soon as it detects an increase in CPU or memory usage (Based on a defined metric). Horizontal Pod Autoscaling is the process of automatically scaling the number of pod replicas managed by a controller based on the usage of the defined metric, which is managed by the Horizontal Pod Autoscaler Kubernetes resource to match the demand.