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Google Associate-Cloud-Engineer Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Deploying and implementing a cloud solution	20%	- Deploying applications and services - Implementing networking components
Topic 2: Setting up a cloud solution environment	20%	- Managing billing and identity access - Setting up cloud projects and accounts
Topic 3: Configuring access and security	15%	- Managing IAM roles and permissions - Securing data and services
Topic 4: Planning and configuring a cloud solution	25%	- Configuring storage and database solutions - Configuring compute resources
Topic 5: Ensuring successful operation of a cloud solution	20%	- Managing cloud resources - Monitoring and logging

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Google Associate Cloud Engineer Exam Sample Questions (Q145-Q150):

NEW QUESTION # 145
You have a Dockerfile that you need to deploy on Kubernetes Engine. What should you do?

A. Use gcloud app deploy <dockerfilename>.
B. Use kubectl app deploy <dockerfilename>.
C. Create a docker image from the Dockerfile and upload it to Container Registry. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.
D. Create a docker image from the Dockerfile and upload it to Cloud Storage. Create a Deployment YAML file to point to that image. Use kubectl to create the deployment with that file.

Answer: C

NEW QUESTION # 146
You want to verify the IAM users and roles assigned within a GCP project named my-project. What should you do?

A. Run gcloud iam roles list. Review the output section.
B. Navigate to the project and then to the IAM section in the GCP Console. Review the members and roles.
C. Run gcloud iam service-accounts list. Review the output section.
D. Navigate to the project and then to the Roles section in the GCP Console. Review the roles and status.

Answer: D

NEW QUESTION # 147
You deployed an App Engine application using gcloud app deploy, but it did not deploy to the intended project. You want to find out why this happened and where the application deployed. What should you do?

A. Check the web-application.xml file for your application and check project settings.
B. Check the app.yaml file for your application and check project settings.
C. Go to Deployment Manager and review settings for deployment of applications.
D. Go to Cloud Shell and run gcloud config list to review the Google Cloud configuration used for deployment.

Answer: D

Explanation:
account = xxx@gmail.com
disable_usage_reporting = False
project = my-first-demo-xxxx
https://cloud.google.com/endpoints/docs/openapi/troubleshoot-gce-deployment

NEW QUESTION # 148
(You are migrating your company's on-premises compute resources to Google Cloud. You need to deploy batch processing jobs that run every night. The jobs require significant CPU and memory for several hours but can tolerate interruptions. You must ensure that the deployment is cost-effective. What should you do?)

A. Use the M1 machine series on Compute Engine.
B. Use custom machine types on Compute Engine.
C. Use Spot VMs on Compute Engine.
D. Containerize the batch processing jobs and deploy them on Compute Engine.

Answer: C

Explanation:
Spot VMs (formerly known as preemptible VMs) are Compute Engine virtual machine instances that are available at a much lower price than standard Compute Engine instances. However, Compute Engine might preempt (stop) these instances if it needs to reclaim those resources for other tasks. This makes Spot VMs ideal for batch processing jobs that are fault-tolerant and can handle interruptions, as they can be restarted when resources become available again. This directly addresses the requirement for a cost-effective solution for interruptible workloads.
Option A: While containerization offers portability and consistency, it doesn't inherently provide cost savings for compute resources. You would still need to choose a cost-effective underlying compute option.
Option B: Custom machine types allow you to tailor the CPU and memory configuration of your VMs, which can optimize costs to some extent by avoiding over-provisioning. However, they don't offer the significant cost reduction that Spot VMs provide.
Option C: The M1 machine series is a specific family of Compute Engine instances optimized for memory- intensive workloads. While potentially suitable for the job's requirements, it doesn't inherently address the cost-effectiveness requirement as directly as Spot VMs, which are priced lower regardless of the machine series.
Reference to Google Cloud Certified - Associate Cloud Engineer Documents:
The concept and use cases for Spot VMs are explicitly covered in the Compute Engine section of the Google Cloud documentation, which is a key area for the Associate Cloud Engineer certification. The cost savings and suitability for fault-tolerant workloads are highlighted as primary benefits.

NEW QUESTION # 149
Your VMs are running in a subnet that has a subnet mask of 255.255.255.240. The current subnet has no more free IP addresses and you require an additional 10 IP addresses for new VMs. The existing and new VMs should all be able to reach each other without additional routes. What should you do?

A. Delete the subnet, and recreate it using a wider range of IP addresses.
B. Create a new subnet with the same starting IP but a wider range to overwrite the current subnet.
C. Create a new project. Use Shared VPC to share the current network with the new project.
D. Use gcloud to expand the IP range of the current subnet.

Answer: D

Explanation:
https://cloud.google.com/sdk/gcloud/reference/compute/networks/subnets/expand-ip-range gcloud compute networks subnets expand-ip-range - expand the IP range of a Compute Engine subnetwork gcloud compute networks subnets expand-ip-range NAME --prefix-length=PREFIX_LENGTH
[--region=REGION] [GCLOUD_WIDE_FLAG ...]

NEW QUESTION # 150
......

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