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Exam Professional Cloud DevOps Engineer topic 1 question 13 discussion

Actual exam question from Google's Professional Cloud DevOps Engineer
Question #: 13
Topic #: 1
[All Professional Cloud DevOps Engineer Questions]

You are performing a semi-annual capacity planning exercise for your flagship service. You expect a service user growth rate of 10% month-over-month over the next six months. Your service is fully containerized and runs on Google Cloud Platform (GCP), using a Google Kubernetes Engine (GKE) Standard regional cluster on three zones with cluster autoscaler enabled. You currently consume about 30% of your total deployed CPU capacity, and you require resilience against the failure of a zone. You want to ensure that your users experience minimal negative impact as a result of this growth or as a result of zone failure, while avoiding unnecessary costs. How should you prepare to handle the predicted growth?

  • A. Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify your expected resource needs.
  • B. Because you are deployed on GKE and are using a cluster autoscaler, your GKE cluster will scale automatically, regardless of growth rate.
  • C. Because you are at only 30% utilization, you have significant headroom and you won't need to add any additional capacity for this rate of growth.
  • D. Proactively add 60% more node capacity to account for six months of 10% growth rate, and then perform a load test to make sure you have enough capacity.
Show Suggested Answer Hide Answer
Suggested Answer: B 🗳️
by devopsbatch at June 2, 2021, 5:06 p.m.

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Charun
Highly Voted 2 years, 10 months ago
answer A
upvoted 24 times
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francisco_guerra
Highly Voted 2 years, 11 months ago
A: Correct. 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 B: Incorrect. It is not based on the CPU its based on the workload C: No, Hope is not an strategy D: No, have more resource than needed
upvoted 23 times
AzureDP900
1 year, 6 months ago
Agreed
upvoted 1 times
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jomonkp
Most Recent 5 months, 2 weeks ago
option A
upvoted 1 times
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Hiren_Meghnathi
6 months ago
Selected Answer: A
Answer A
upvoted 1 times
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umesh0u
1 year, 2 months ago
Selected Answer: A
i think A
upvoted 1 times
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JonathanSJ
1 year, 4 months ago
Selected Answer: A
Answer is A
upvoted 1 times
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akarayol
1 year, 4 months ago
A and B confusing
upvoted 1 times
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mohan999
1 year, 6 months ago
B is incorrect, because the cluster autoscaler doesn't work based on CPU/Memory usage on the node. The cluster will be scaled on the basis of resources requested by the workloads. So A is more relevant since HPA will automatically scales up/down based on the workload usage.
upvoted 1 times
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GCP72
1 year, 9 months ago
Selected Answer: A
The correct answer is "A"
upvoted 1 times
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Ananda
2 years ago
Selected Answer: A
Submit the option provide in A
upvoted 1 times
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gomezzang
2 years ago
Selected Answer: A
A is correct
upvoted 1 times
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skm4690
2 years, 1 month ago
A seems to be correct.
upvoted 1 times
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Goatee_McGee
2 years, 2 months ago
Answer is A
upvoted 1 times
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asdqweasd
2 years, 2 months ago
Selected Answer: A
Even with autoscaling maximul limit effect scaling
upvoted 1 times
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burndayl
2 years, 5 months ago
C for me: 30% of total deployed CPU consumption mean 10% of CUP on each zone; 10% of increment month-over-month mean at the beginning of the second mont you will have 11% of CPU, at the tird 12,1% and so on; you can easly accomodate a fault of a zone; you don't have additional cost
upvoted 2 times
mohan999
1 year, 6 months ago
10% growth is only predicted value, but you should also be prepared for scenarios if the growth at real time is higher. In any case, using HPA and scaling based on it would be an optimal choice in my opinion.
upvoted 2 times
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alaahakim
2 years, 5 months ago
Selected Answer: A
Ans: A
upvoted 1 times
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Bala999
2 years, 5 months ago
Selected Answer: A
Correct answer A.
upvoted 1 times
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C (25%)
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