Google Exam Professional-Cloud-Developer Topic 8 Question 90 Discussion

Actual exam question for Google's Professional Cloud Developer exam

Question #: 90
Topic #: 8

[All Professional Cloud Developer Questions]

You need to load-test a set of REST API endpoints that are deployed to Cloud Run. The API responds to HTTP POST requests Your load tests must meet the following requirements:

* Load is initiated from multiple parallel threads

* User traffic to the API originates from multiple source IP addresses.

* Load can be scaled up using additional test instances

You want to follow Google-recommended best practices How should you configure the load testing'?

ACreate an image that has cURL installed and configure cURLto run a test plan Deploy the image in a
managed instance group, and run one instance of the image for each VM.

BCreate an image that has cURL installed and configure cURL to run a test plan Deploy the image in an
unmanaged instance group, and run one instance of the image for each VM.

CDeploy a distributed load testing framework on a private Google Kubernetes Engine Cluster Deploy
additional Pods as needed to initiate more traffic and support the number of concurrent users.

DDownload the container image of a distributed load testing framework on Cloud Shell Sequentially start
several instances of the container on Cloud Shell to increase the load on the API.

Show Suggested Answer

Suggested Answer: C

by Annita at Aug 28, 2024, 03:34 AM

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Portia

12 days ago

I'd have to say C is the way to go. Leveraging a distributed load testing framework on GKE is the most Google-approved and scalable solution.

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Basilia

2 days ago

That sounds like a solid plan. It's always good to follow Google's recommendations.

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Annmarie

8 days ago

C) Deploy a distributed load testing framework on a private Google Kubernetes Engine Cluster Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.

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Ashlyn

24 days ago

Personally, I think C is the best choice. It ticks all the boxes - parallel threads, multiple source IPs, and scalability. Can't go wrong with that.

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Stefania

13 days ago

I think option D could also work well, starting multiple instances on Cloud Shell could be efficient.

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Vivan

15 days ago

I agree, option C seems like the most comprehensive choice for load testing.

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Mira

1 months ago

Haha, using Cloud Shell to run load tests? That's like trying to power a rocket with a AA battery. C is the clear winner here.

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Leota

13 days ago

C) Deploy a distributed load testing framework on a private Google Kubernetes Engine Cluster Deploy additional Pods as needed to initiate more traffic and support the number of concurrent users.

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Jovita

18 days ago

A) Create an image that has cURL installed and configure cURL to run a test plan Deploy the image in a managed instance group, and run one instance of the image for each VM.

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Phuong

1 months ago

I agree, C seems like the most appropriate option. Deploying on a private GKE cluster gives you the flexibility to handle the load requirements.

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Gracia

1 months ago

C is definitely the way to go. Using a distributed load testing framework on GKE aligns with the Google-recommended best practices and allows for easy scaling of the load.

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Moon

10 days ago

That makes sense. It's important to follow best practices when load testing REST API endpoints on Cloud Run.

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Adell

12 days ago

I agree, deploying additional Pods on GKE is a scalable solution for load testing.

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Valentin

22 days ago

C is definitely the way to go. Using a distributed load testing framework on GKE aligns with the Google-recommended best practices and allows for easy scaling of the load.

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Helga

2 months ago

I'm not sure about option D. Downloading a container image on Cloud Shell and starting several instances sequentially may not be as scalable as deploying on a Kubernetes Engine Cluster.

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Marylou

2 months ago

I agree with Clay. Option C seems like the most efficient way to configure the load testing while following Google-recommended best practices.

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Clay

2 months ago

I think option C is the best choice. Deploying a distributed load testing framework on a private Google Kubernetes Engine Cluster allows for scalability and flexibility.

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