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Professional Cloud DevOps Engineer Exam - Question 13

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?

Verify the maximum node pool size, enable a horizontal pod autoscaler, and then perform a load test to verify your expected resource needs.

Because you are deployed on GKE and are using a cluster autoscaler, your GKE cluster will scale automatically, regardless of growth rate.

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.

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 Answer

Correct Answer: AB

To handle the predicted user growth and ensure resilience against zone failure, it is crucial to verify the maximum node pool size, enable a horizontal pod autoscaler (HPA), and perform a load test to validate the expected resource needs. HPA adjusts the number of Pods based on CPU or memory consumption, helping to maintain optimal performance under varying loads. This approach ensures that you can scale in line with the growth rate and have adequate resources available while avoiding unnecessary costs, as it allows for dynamic scaling instead of over-provisioning.

Discussion

17 comments

CharunOption: A

Jun 28, 2021

answer A

francisco_guerraOption: A

Jun 20, 2021

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

AzureDP900

Oct 24, 2022

Agreed

burndaylOption: C

Dec 6, 2021

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

mohan999

Nov 10, 2022

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.

alaahakimOption: A

Dec 5, 2021

Ans: A

asdqweasdOption: A

Feb 23, 2022

Even with autoscaling maximul limit effect scaling

Goatee_McGeeOption: A

Mar 14, 2022

Answer is A

skm4690Option: A

Apr 10, 2022

A seems to be correct.

gomezzangOption: A

Apr 21, 2022

A is correct

AnandaOption: A

May 9, 2022

Submit the option provide in A

GCP72Option: A

Aug 14, 2022

The correct answer is "A"

mohan999Option: A

Nov 10, 2022

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.

akarayolOption: A

Dec 29, 2022

A and B confusing

JonathanSJOption: A

Jan 11, 2023

Answer is A

umesh0uOption: A

Mar 3, 2023

i think A

Hiren_MeghnathiOption: A

Nov 16, 2023

Answer A

jomonkpOption: A

Dec 2, 2023

option A

Kedar1234Option: B

Jul 13, 2024

Examtopics suggest Ans B