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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'?

Show Suggested Answer Hide Answer
Suggested Answer: C

Contribute your Thoughts:

Portia
1 months 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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Salley
27 days ago
Definitely, using GKE for load testing is a smart choice for scalability.
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Basilia
1 months ago
That sounds like a solid plan. It's always good to follow Google's recommendations.
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Annmarie
1 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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Ashlyn
2 months 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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Jerlene
20 days ago
I think option A could be a simpler solution, deploying an image with cURL installed in a managed instance group.
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Lelia
1 months ago
I see your point, but I still believe option C is the most Google-recommended approach for load testing.
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Stefania
2 months ago
I think option D could also work well, starting multiple instances on Cloud Shell could be efficient.
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Vivan
2 months ago
I agree, option C seems like the most comprehensive choice for load testing.
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Mira
2 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
1 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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Jovita
2 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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Phuong
2 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
3 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
1 months 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
1 months ago
I agree, deploying additional Pods on GKE is a scalable solution for load testing.
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Valentin
2 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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Helga
3 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
3 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
3 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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