Google Exam Associate Cloud Engineer Topic 1 Question 80 Discussion

Actual exam question for Google's Associate Cloud Engineer exam

Question #: 80
Topic #: 1

[All Associate Cloud Engineer Questions]

A team of data scientists infrequently needs to use a Google Kubernetes Engine (GKE) cluster that you manage. They require GPUs for some long-running, non-restartable jobs. You want to minimize cost. What should you do?

AEnable node auto-provisioning on the GKE cluster.

BCreate a VerticalPodAutscaler for those workloads.

CCreate a node pool with preemptible VMs and GPUs attached to those VMs.

DCreate a node pool of instances with GPUs, and enable autoscaling on this node pool with a minimum size of 1.

Show Suggested Answer

Suggested Answer: B

by Judy at Apr 21, 2024, 10:12 AM

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Dorothea

2 months ago

If I had a penny for every time I've had to optimize for cost on a certification exam, I'd be rich enough to buy my own GKE cluster.

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Lynna

14 days ago

A) Enable node auto-provisioning on the GKE cluster.

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Dorian

20 days ago

D) Create a node pool of instances with GPUs, and enable autoscaling on this node pool with a minimum size of 1.

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Karima

1 months ago

C) Create a node pool with preemptible VMs and GPUs attached to those VMs.

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Justine

2 months ago

Wait, there's an option to use preemptible VMs with GPUs? That's like the holy grail of cost optimization!

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Ngoc

16 days ago

I didn't know that was an option, thanks for pointing it out!

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Carman

18 days ago

That's right! It's a great way to minimize costs while still getting the GPU power you need.

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Georgene

1 months ago

Yes, option C allows you to create a node pool with preemptible VMs and GPUs attached to those VMs.

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Rozella

2 months ago

A and B don't really address the GPU requirement, so I'm leaning towards C. Gotta love those preemptible VMs!

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Nikita

2 months ago

D sounds tempting, but I'd rather not have to worry about scaling up and down. C is the clear winner here.

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Chan

18 days ago

It might be more convenient, but C is still the most cost-effective choice.

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Kris

1 months ago

But wouldn't D be more convenient in terms of autoscaling?

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Arlene

2 months ago

I agree, using preemptible VMs with GPUs attached seems like the most cost-effective solution.

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Lorriane

2 months ago

I think C is the best option for minimizing cost.

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Narcisa

2 months ago

That's a good point. Autoscaling with GPUs could be more cost-effective in the long run.

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Alisha

2 months ago

I disagree, I believe option D is better. Autoscaling with GPUs can ensure the jobs are completed efficiently.

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Allene

2 months ago

Hmm, I think C is the way to go. Preemptible VMs with GPUs? That's a cost-saver for sure!

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Barabara

1 months ago

Yes, it's a great way to minimize cost while still meeting the data scientists' needs.

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Tamar

2 months ago

I agree, using preemptible VMs with GPUs attached is a cost-effective solution.

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Narcisa

2 months ago

I think option C is the best choice. Preemptible VMs with GPUs can help minimize cost.

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