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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?

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Suggested Answer: B

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

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Dorothea
1 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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Dorian
3 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
20 days ago
C) Create a node pool with preemptible VMs and GPUs attached to those VMs.
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Justine
1 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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Carman
19 hours 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
22 days 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
1 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
1 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
19 hours ago
It might be more convenient, but C is still the most cost-effective choice.
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Kris
23 days ago
But wouldn't D be more convenient in terms of autoscaling?
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Arlene
1 months ago
I agree, using preemptible VMs with GPUs attached seems like the most cost-effective solution.
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Lorriane
1 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
28 days ago
Yes, it's a great way to minimize cost while still meeting the data scientists' needs.
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Tamar
1 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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