Exam Professional Cloud Architect topic 1 question 79 discussion

Answer: A Support: 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.

i'm for A, but the question in ambiguous, because requires the autoscale of nodes (not pod) when the cpu overload, but in answer use k8s pod autoscaler based on cpu load ( cpu load for pod, not nodes ). strange

Nice and detailed explanation. I agree with A.

A seems correct. y to create managed instance groups unnecessarily?

The answer is A. More nodes mean it's horizontal scaling (increase VMs means vertical scaling of infrastructure). Cluster AutoScalar is used for increasing number of nodes.

A is the Correct answer, Horizontal Pod Autoscaler and Cluster Autoscaler can be used together to provision new pods and new nodes as per the CPU utilization. https://www.youtube.com/watch?v=VNAWA6NkoBs

ok for A

MIG not for GKE as option B and C, D are not relevant to question

Configure a HorizontalPodAutoscaler with a target CPU usage. Enable the Cluster Autoscaler from the GCP Console.

A... 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.

A is wrong. Pod scaling only spins up additional pods. Not nodes. Cluster Autoscaler does adding of nodes automatically. I am surprised that so many people think that A is the correct answer. Correct answer per me is C

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.

I got one question on my exam which showed autoscaling configuration and was asked to select correct configuration.

I agree A is correct. I found quicklab. Understanding and Combining GKE Autoscaling Strategies.

B and D: You must never change the GKE managed instance group. C and D: maxUnavailable and maxSurge are used for rolling update A. It is the correct.

Go for A

Create Horizontal Autoscaler (min,max for pods): kubectl autoscale deployment my-app --max 6 --min 4 --cpu-percent 50 Autoscaling cluster: gcloud container clusters create example-cluster \ --zone us-central1-a \ --node-locations us-central1-a,us-central1-b,us-central1-f \ --num-nodes 2 --enable-autoscaling --min-nodes 1 --max-nodes 4 Check scaling an application and Horizontal Pod Autoscaler: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/ Manual Cluster Resizing: https://cloud.google.com/kubernetes-engine/docs/how-to/resizing-a-cluster https://cloud.google.com/kubernetes-engine/docs/how-to/scaling-apps