Google Exam Professional Cloud DevOps Engineer Topic 1 Question 64 Discussion

Actual exam question for Google's Professional Cloud DevOps Engineer exam

Question #: 64
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 for the next six months Your service is fully containerized and runs on a Google Kubemetes Engine (GKE) standard cluster across three zones with cluster autoscaling 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 o' as a result of zone failure while you avoid unnecessary costs How should you prepare to handle the predicted growth?

AVerify the maximum node pool size enable a Horizontal Pod Autoscaler and then perform a load lest to verify your expected resource needs

BBecause you deployed the service on GKE and are using a cluster autoscaler your GKE cluster will scale automatically regardless of growth rate

CBecause you are only using 30% of deployed CPU capacity there is significant headroom and you do not need to add any additional capacity for this rate of growth

DProactively add 80% more node capacity to account for six months of 10% growth rate and then perform a load test to ensure that you have enough capacity

Show Suggested Answer

Suggested Answer: A, D

The correct answers are A and D)

Examine the wall-clock time and the CPU time of the application. If the difference is substantial, increase the CPU resource allocation. This is a good way to determine if the application is CPU-bound, meaning that it spends more time waiting for the CPU than performing actual computation. Increasing the CPU resource allocation can improve the performance of CPU-bound applications1.

Examine the latency time, the wall-clock time, and the CPU time of the application. If the latency time is slowly burning down the error budget, and the difference between wall-clock time and CPU time is minimal, mark the application for optimization. This is a good way to determine if the application is I/O-bound, meaning that it spends more time waiting for input/output operations than performing actual computation. Increasing the CPU resource allocation will not help I/O-bound applications, and they may need optimization to reduce the number or duration of I/O operations2.

Answer B is incorrect because increasing the memory resource allocation will not help if the application is CPU-bound or I/O-bound. Memory allocation affects how much data the application can store and access in memory, but it does not affect how fast the application can process that data.

Answer C is incorrect because increasing the local disk storage allocation will not help if the application is CPU-bound or I/O-bound. Disk storage affects how much data the application can store and access on disk, but it does not affect how fast the application can process that data.

Answer E is incorrect because examining the heap usage of the application will not help to determine if the application needs performance tuning. Heap usage affects how much memory the application allocates for dynamic objects, but it does not affect how fast the application can process those objects. Moreover, low heap usage does not necessarily mean that the application is inefficient or unoptimized.

by Penney at Apr 10, 2024, 06:40 AM

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