Google Exam Professional Data Engineer Topic 5 Question 89 Discussion

Actual exam question for Google's Professional Data Engineer exam

Question #: 89
Topic #: 5

[All Professional Data Engineer Questions]

You have a data processing application that runs on Google Kubernetes Engine (GKE). Containers need to be launched with their latest available configurations from a container registry. Your GKE nodes need to have GPUs. local SSDs, and 8 Gbps bandwidth. You want to efficiently provision the data processing infrastructure and manage the deployment process. What should you do?

AUse Compute Engi.no startup scriots to pull container Images, and use gloud commands to provision the infrastructure.

BUse GKE to autoscale containers, and use gloud commands to provision the infrastructure.

CUse Cloud Build to schedule a job using Terraform build to provision the infrastructure and launch with the most current container images.

DUse Dataflow to provision the data pipeline, and use Cloud Scheduler to run the job.

Show Suggested Answer

Suggested Answer: C

https://cloud.google.com/architecture/managing-infrastructure-as-code

by Penney at Jul 18, 2024, 01:13 AM

Limited Time Offer

25%

Off

Get Premium Professional Data Engineer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Hana

7 months ago

Option C is the clear winner here. Terraform and Cloud Build? That's like peanut butter and jelly, except for infrastructure provisioning and container deployment.

upvoted 0 times

...

Clare

7 months ago

Am I the only one who thinks Option A sounds like a lot of manual work? No thanks, I'll take the automated solutions any day.

upvoted 0 times

...

Carolann

7 months ago

Option D is intriguing, but Dataflow and Cloud Scheduler? That's a lot of moving parts. I'd prefer a more unified approach like Option C.

upvoted 0 times

Brandon

6 months ago

I agree, Option C seems like a more streamlined solution for managing the deployment process.

upvoted 0 times

...

Gearldine

6 months ago

Option D is intriguing, but Dataflow and Cloud Scheduler? That's a lot of moving parts. I'd prefer a more unified approach like Option C.

upvoted 0 times

...

Erick

7 months ago

I'm leaning towards Option B. GKE's autoscaling capabilities combined with the `gcloud` commands for infrastructure setup could be a really efficient solution.

upvoted 0 times

Lourdes

6 months ago

Agreed, GKE's autoscaling feature combined with `gcloud` commands sounds like a solid plan for managing the data processing infrastructure.

upvoted 0 times

...

Queenie

6 months ago

Using `gcloud` commands for infrastructure setup would definitely streamline the deployment process.

upvoted 0 times

...

Luke

7 months ago

I think Option B is a good choice. GKE autoscaling can help manage the containers efficiently.

upvoted 0 times

...

Whitney

7 months ago

Option C looks like the way to go. Terraform and Cloud Build seem like the perfect combo to provision the infrastructure and deploy the latest containers. Plus, it's all managed in one place.

upvoted 0 times

Quentin

6 months ago

I think it's important to have a streamlined process for provisioning and deploying containers, especially in a data processing application. Option C seems like the best choice.

upvoted 0 times

...

Dominga

6 months ago

It's definitely a more efficient way to manage the infrastructure and deployment. Plus, it helps with scalability and reliability.

upvoted 0 times

...

Henriette

6 months ago

I agree, using Cloud Build with Terraform simplifies the deployment process and ensures we are always using the latest container images.

upvoted 0 times

...

Xochitl

7 months ago

Option C looks like the way to go. Terraform and Cloud Build seem like the perfect combo to provision the infrastructure and deploy the latest containers. Plus, it's all managed in one place.

upvoted 0 times

...