Google Professional Data Engineer Exam - Topic 1 Question 78 Discussion

Actual exam question for Google's Professional Data Engineer exam

Question #: 78
Topic #: 1

[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 Nicolette at Mar 04, 2024, 04:41 AM

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Felix

6 months ago

Local SSDs are a must for performance, good call!

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Regenia

6 months ago

Wait, can Dataflow really handle this?

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Evan

6 months ago

A is outdated, we need to use newer methods.

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Ricki

7 months ago

I disagree, C is more efficient with Terraform.

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Annice

7 months ago

B seems like the best option for autoscaling.

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Lashanda

7 months ago

I vaguely remember Dataflow being mentioned in our study materials, but I don't think it fits here since we need to manage container images directly.

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Ozell

7 months ago

I feel like using Compute Engine startup scripts might be too manual for this. I think we should focus on something more automated like GKE.

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Lauran

7 months ago

I think option C sounds familiar. We practiced using Terraform with Cloud Build in a similar question, but I can't recall the exact details.

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Lewis

8 months ago

I remember we discussed using GKE for autoscaling, but I'm not sure if that's the best option for this specific scenario.

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Ellsworth

8 months ago

Okay, I think I've got it. The question is asking us to set up a GKE cluster with the required specifications, and then deploy the data processing application using the latest container images. Cloud Build and Terraform seem like the way to go.

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Jettie

8 months ago

Ah, I see. Using Cloud Build and Terraform to provision the infrastructure and launch the latest container images seems like the most efficient and scalable solution here. That's the approach I'll focus on.

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Lorita

8 months ago

Hmm, I'm a bit confused about the different options here. I'm not sure if using Compute Engine startup scripts or Dataflow is the right approach for this scenario. I'll need to think it through carefully.

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Salome

8 months ago

This question seems pretty straightforward. I think the key is to use a combination of GKE and Terraform to provision the infrastructure and manage the deployment process.

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Sylvie

8 months ago

Hmm, I'm a bit unsure about this one. I'm debating between B and C, since sending the same email delivery could also potentially save time with a template. I'll have to think this through a bit more.

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Yolande

8 months ago

Huh, this is an interesting question. I'll need to carefully consider the purpose and contents of each log file to find the one that doesn't belong.

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Kara

8 months ago

Hmm, this seems like a tricky one. I'll need to think carefully about the definition of MTTR and how it relates to the time taken to diagnose the problem.

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Youlanda

8 months ago

Okay, let me walk through this step-by-step. Positive risks are opportunities, so the best strategy would be to accept and capitalize on them.

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Buddy

8 months ago

I think the minimal privilege required to create a view is SELECT on the underlying tables, but I'm not entirely sure.

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Erasmo

8 months ago

I hope none of the options state that new content types can't be created, because I thought I read that you can create them through Model Manager.

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Adelina

2 years ago

I see the benefit of using Cloud Scheduler to run the job as well.

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Tammara

2 years ago

I beliTammara using Dataflow for the data pipeline is the best option.

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Leila

2 years ago

But wouldn't using GKE to autoscale containers be more efficient?

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Adelina

2 years ago

I prefer using Cloud Build with Terraform to provision the infrastructure.

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Leila

2 years ago

I think we should use Compute Engine startup scripts and gloud commands.

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Amos

2 years ago

Absolutely, and Dataflow and Cloud Scheduler seem more focused on data processing pipelines, which isn't the core requirement here. Cloud Build and Terraform is the way to go.

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Portia

2 years ago

Yeah, that's a good point. The other options like using Compute Engine startup scripts or GKE autoscaling don't seem to address the need for specialized hardware like GPUs and local SSDs.

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Ariel

2 years ago

I agree, the Cloud Build and Terraform option seems like the most comprehensive and efficient solution. It allows us to manage the entire provisioning and deployment process programmatically.

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Theresia

2 years ago

Hmm, this question seems to be testing our knowledge of infrastructure provisioning and deployment strategies for GKE. I'm thinking the best approach would be to use Cloud Build and Terraform to provision the infrastructure and deploy the latest container images.

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