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Google Exam Professional Cloud Developer Topic 12 Question 96 Discussion

Actual exam question for Google's Professional Cloud Developer exam
Question #: 96
Topic #: 12
[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'?

Show Suggested Answer Hide Answer
Suggested Answer: C

Contribute your Thoughts:

Dante
2 months ago
I don't know, guys. That Kubernetes option sounds a bit overkill. Can't we just use some good old cURL scripts? *chuckles*
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Hayley
23 days ago
D) Download 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.
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Jenise
26 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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Almeta
29 days ago
B) Create 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.
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Gianna
1 months 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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Lili
2 months ago
Yep, C is the clear winner. Deploying a distributed framework on GKE is the way to go to meet all the requirements.
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Ronny
2 months ago
Ha, Cloud Shell? Really? That's definitely not going to cut it for a load test of this magnitude. Gotta go with the Kubernetes route.
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Bea
1 months ago
Ha, Cloud Shell? Really? That's definitely not going to cut it for a load test of this magnitude. Gotta go with the Kubernetes route.
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Vincenza
2 months 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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Jerry
2 months ago
B) Create 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.
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Gertude
2 months ago
I agree, C is the best choice. The ability to scale up the load testing pods as needed is really important for this use case.
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Arlette
1 months ago
I agree, C is the best choice. The ability to scale up the load testing pods as needed is really important for this use case.
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Wilda
2 months 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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Brittni
2 months ago
I'm not sure about option D. Starting several instances of a container on Cloud Shell may not be as scalable as using GKE for load testing.
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Omega
2 months ago
I agree with Jospeh. Using a distributed load testing framework on GKE seems like the most efficient way to meet the requirements.
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Mauricio
2 months ago
Option C looks like the way to go here. A managed Kubernetes cluster will give us the scalability and control we need to handle the load.
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Robt
2 months ago
Definitely, deploying additional Pods as needed to support the number of concurrent users will help us meet the requirements for load testing the REST API endpoints on Cloud Run.
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Sheridan
2 months ago
I agree, using a distributed load testing framework on a private Google Kubernetes Engine Cluster seems like the best option for this scenario.
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Corrinne
2 months ago
Option C looks like the way to go here. A managed Kubernetes cluster will give us the scalability and control we need to handle the load.
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Jospeh
3 months ago
I think option C is the best choice. It allows for scaling up the load testing using additional Pods on Google Kubernetes Engine.
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