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Exam Professional Cloud Architect topic 1 question 186 discussion

Actual exam question from Google's Professional Cloud Architect
Question #: 186
Topic #: 1
[All Professional Cloud Architect Questions]

Your company uses Google Kubernetes Engine (GKE) as a platform for all workloads. Your company has a single large GKE cluster that contains batch, stateful, and stateless workloads. The GKE cluster is configured with a single node pool with 200 nodes. Your company needs to reduce the cost of this cluster but does not want to compromise availability. What should you do?

  • A. Create a second GKE cluster for the batch workloads only. Allocate the 200 original nodes across both clusters.
  • B. Configure CPU and memory limits on the namespaces in the cluster. Configure all Pods to have a CPU and memory limits.
  • C. Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling.
  • D. Change the node pool to use preemptible VMs.
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Suggested Answer: C 🗳️
by spET_1024 at Sept. 3, 2022, 11:50 a.m.

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jabrrJ68w02ond1
Highly Voted 2 years, 5 months ago
Selected Answer: C
A: Is not necessary because you can have multiple node pools with different configurations. B: Optimizes resource usage of CPU/memory in your existing node pool but does not necessarily improve cost - still an option that should be considered. C: This looks really good. Autoscaling workloads and the node pools makes your whole infrastructure more elastic and gives you the option to rely on the same node pool. D: This might not be a good option for every type of workload. Batch and stateless workloads can often handle this quite well, but stateful workloads are not well-suited for operation on preemptible VMs. Since only one answer is accepted, I'll choose C.
upvoted 15 times
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ramzez4815
Highly Voted 2 years, 5 months ago
Selected Answer: C
C is the correct answer as it doesn't involve major changes to the current Kubernetes configuration
upvoted 8 times
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MarcoPellegrino
Most Recent 3 months, 4 weeks ago
It uses Google features
upvoted 1 times
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Gino17m
9 months, 2 weeks ago
Selected Answer: C
Vote for C. In B limits could compromise availability.
upvoted 1 times
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AugustoKras011111
1 year, 11 months ago
Selected Answer: C
Answer C. Use HorizontalPodAutoscaler.
upvoted 1 times
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zerg0
2 years ago
Selected Answer: C
HorizontalPodAutoscaler is the way
upvoted 1 times
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tdotcat
2 years ago
Selected Answer: C
c is good
upvoted 1 times
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omermahgoub
2 years, 1 month ago
The correct answer is C: Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling. One way to reduce the cost of a Google Kubernetes Engine (GKE) cluster without compromising availability is to use horizontal pod autoscalers (HPA) and node auto scaling. HPA allows you to automatically scale the number of Pods in a deployment based on the resource usage of the Pods. By configuring HPA for stateless workloads and for compatible stateful workloads, you can ensure that the number of Pods is automatically adjusted based on the actual resource usage, which can help to reduce costs. Node auto scaling allows you to automatically add or remove nodes from the node pool based on the resource usage of the cluster. By configuring node auto scaling, you can ensure that the cluster has the minimum number of nodes needed to meet the resource requirements of the workloads, which can also help to reduce costs.
upvoted 5 times
omermahgoub
2 years, 1 month ago
A: Creating a second GKE cluster for the batch workloads only and allocating the 200 original nodes across both clusters would not necessarily help to reduce costs, as the total number of nodes in the clusters would remain the same. B: Configuring CPU and memory limits on the namespaces in the cluster and configuring all Pods to have CPU and memory limits may help to reduce costs, but it is not sufficient on its own. You should also use HPA and node auto scaling to ensure that the cluster is properly sized based on the actual resource usage. D: Changing the node pool to use preemptible VMs may help to reduce costs, but it is not sufficient on its own. Preemptible VMs can be terminated at any time, which may not be suitable for all workloads. You should also use HPA and node auto scaling to ensure that the cluster is properly sized based on the actual resource usage.
upvoted 3 times
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ale_brd_111
2 years, 1 month ago
Selected Answer: C
C is the correct answer as it doesn't involve major changes to the current Kubernetes configuration
upvoted 1 times
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megumin
2 years, 2 months ago
Selected Answer: C
C is ok
upvoted 1 times
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AzureDP900
2 years, 4 months ago
C is correct
upvoted 1 times
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rorz
2 years, 5 months ago
Selected Answer: C
C is correc
upvoted 1 times
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aswani
2 years, 5 months ago
Selected Answer: C
Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling
upvoted 2 times
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spET_1024
2 years, 5 months ago
Option C is correct. Since, the company does not want to compromise availability of the application so, HPA is suitable option for autoscaling pods. Keeping the cost optimization in mind, nodes of the GKE cluster also needs to be autoscaled. Therefore, the correct option is, C. Configure a HorizontalPodAutoscaler for all stateless workloads and for all compatible stateful workloads. Configure the cluster to use node auto scaling.
upvoted 3 times
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B (20%)
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