Optimizing Resource Utilization with Horizontal Pod Autoscaling (HPA) in Kubernetes | AKS 

Horizontal Pod Autoscaling (HPA) is a Kubernetes feature that automatically adjusts the number of replicas of a deployment based on metrics such as CPU utilization or memory usage. HPA enables a cluster to scale the number of pods running in a deployment based on the workload demand, ensuring that the required resources are available to meet the application's performance needs. This helps to improve the efficiency and resource utilization of the cluster, as well as providing a self-healing mechanism to ensure that applications remain highly available even in the event of pod failures.
Introduction to Horizontal Pod Autoscaling (HPA) in Kubernetes
Setting Up Horizontal Pod Autoscaling (HPA) on a Kubernetes Cluster
Using Horizontal Pod Autoscaling (HPA) to Scale Your Applications in Kubernetes
A Practical Guide to Horizontal Pod Autoscaling (HPA) in Kubernetes
Optimizing Resource Utilization with Horizontal Pod Autoscaling (HPA) in Kubernetes
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