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Google Updated Associate-Cloud-Engineer Exam Questions and Answers by selina

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Google Associate-Cloud-Engineer Exam Overview :

Exam Name: Google Cloud Certified - Associate Cloud Engineer
Exam Code: Associate-Cloud-Engineer Dumps
Vendor: Google Certification: Google Cloud Certified
Questions: 343 Q&A's Shared By: selina
Question 76

You are operating a Google Kubernetes Engine (GKE) cluster for your company where different teams can run non-production workloads. Your Machine Learning (ML) team needs access to Nvidia Tesla P100 GPUs to train their models. You want to minimize effort and cost. What should you do?

Options:

A.

Ask your ML team to add the “accelerator: gpu” annotation to their pod specification.

B.

Recreate all the nodes of the GKE cluster to enable GPUs on all of them.

C.

Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs. Dedicate this cluster to your ML team.

D.

Add a new, GPU-enabled, node pool to the GKE cluster. Ask your ML team to add the cloud.google.com/gke -accelerator: nvidia-tesla-p100 nodeSelector to their pod specification.

Discussion
Question 77

Your organization has a dedicated person who creates and manages all service accounts for Google Cloud projects. You need to assign this person the minimum role for projects. What should you do?

Options:

A.

Add the user to roles/iam.roleAdmin role.

B.

Add the user to roles/iam.securityAdmin role.

C.

Add the user to roles/iam.serviceAccountUser role.

D.

Add the user to roles/iam.serviceAccountAdmin role.

Discussion
Question 78

You need to manage a Cloud Spanner Instance for best query performance. Your instance in production runs in a single Google Cloud region. You need to improve performance in the shortest amount of time. You want to follow Google best practices for service configuration. What should you do?

Options:

A.

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 45% If you exceed this threshold, add nodes lo your instance.

B.

Create an alert in Cloud Monitoring to alert when the percentage to high priority CPU utilization reaches 45% Use database query statistics to identify queries that result in high CPU usage, and then rewrite those queries to optimize their resource usage

C.

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 65% If you exceed this threshold, add nodes to your instance

D.

Create an alert in Cloud Monitoring to alert when the percentage of high priority CPU utilization reaches 65%. Use database query statistics to identity queries that result in high CPU usage, and then rewrite those queries to optimize their resource usage.

Discussion
Question 79

You have several hundred microservice applications running in a Google Kubernetes Engine (GKE) cluster. Each microservice is a deployment with resource limits configured for each container in the deployment. You've observed that the resource limits for memory and CPU are not appropriately set for many of the microservices. You want to ensure that each microservice has right sized limits for memory and CPU. What should you do?

Options:

A.

Modify the cluster's node pool machine type and choose a machine type with more memory and CPU.

B.

Configure a Horizontal Pod Autoscaler for each microservice.

C.

Configure GKE cluster autoscaling.

D.

Configure a Vertical Pod Autoscaler for each microservice.

Discussion
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