Question-35: If you turn off auto-provisioning on your cluster and then turn it back on again, the auto-provisioning setting for any existing node pools will not be restored. You will need to declare specific node pools as auto-provisioned in order to bring back the functionality of auto-provisioning for these node pools. It will function properly for newly created node pools. You want the nodes in your Google Kubernetes Engine cluster to be added or removed automatically depending on how busy the CPUs are. What steps should you take?
A. Establish a target for the amount of CPU usage in a HorizontalPodAutoscaler. Activate the Cluster Autoscaler through the Google Cloud Platform Console.
B. Set a target CPU use on a HorizontalPodAutoscaler and configure it accordingly. Through the use of the gcloud command, enable autoscaling for the managed instance group that belongs to the cluster.
C. Make a deployment and adjust its parameters for maximum available time and maximum surge capacity. Through the use of the gcloud command, enable the Cluster Autoscaler.
D. Create a deployment and configure its maximum usable time and maximum surge capacity. Using the Google Cloud Platform Console, turn autoscaling on for the cluster managed instance group.
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: 1 Explanation: How does Horizontal Pod Autoscaler work with Cluster Autoscaler? Horizontal Pod Autoscaler changes the deployment's or replicaset's number of replicas based on the current CPU load. If the load increases, HPA will create new replicas, for which there may or may not be enough space in the cluster. If there are not enough resources, CA will try to bring up some nodes, so that the HPA-created pods have a place to run. If the load decreases, HPA will stop some of the replicas. As a result, some nodes may become underutilized or completely empty, and then CA will terminate such unneeded nodes. The HPA and CA complement each other for truly efficient scaling. If the load increases, HPA will create new replicas. If there isn’t enough space for these replicas, CA will provision some nodes, so that the HPA-created pods have a place to run. The Horizontal Pod Autoscaler changes the shape of your Kubernetes workload by automatically increasing or decreasing the number of Pods in response to the workload's CPU or memory consumption, or in response to custom metrics reported from within Kubernetes or external metrics from sources outside of your cluster.