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 Associate-Cloud-Engineer Dumps with Practice Exam Questions Answers

Questions: 325 Questions and Answers With Step-by-Step Explanation

Last Update: Jul 2, 2025

Associate-Cloud-Engineer Question Includes: Single Choice Questions: 320, Multiple Choice Questions: 5,

Associate-Cloud-Engineer Questions and Answers

Question # 1

For analysis purposes, you need to send all the logs from all of your Compute Engine instances to a BigQuery dataset called platform-logs. You have already installed the Stackdriver Logging agent on all the instances. You want to minimize cost. What should you do?

A.

1. Give the BigQuery Data Editor role on the platform-logs dataset to the service accounts used by your instances.2. Update your instances’ metadata to add the following value: logs-destination: bq://platform-logs.

B.

1. In Stackdriver Logging, create a logs export with a Cloud Pub/Sub topic called logs as a sink.2. Create a Cloud Function that is triggered by messages in the logs topic.3. Configure that Cloud Function to drop logs that are not from Compute Engine and to insert Compute Engine logs in the platform-logs dataset.

C.

1. In Stackdriver Logging, create a filter to view only Compute Engine logs.2. Click Create Export.3. Choose BigQuery as Sink Service, and the platform-logs dataset as Sink Destination.

D.

1. Create a Cloud Function that has the BigQuery User role on the platform-logs dataset.2. Configure this Cloud Function to create a BigQuery Job that executes this query:INSERT INTO dataset.platform-logs (timestamp, log)SELECT timestamp, log FROM compute.logsWHERE timestamp > DATE_SUB(CURRENT_DATE(), INTERVAL 1 DAY)3. Use Cloud Scheduler to trigger this Cloud Function once a day.

Question # 2

You are deploying an application to Google Kubernetes Engine (GKE) that needs to call an external third-party API. You need to provide the external API vendor with a list of IP addresses for their firewall to allow traffic from your application. You want to follow Google-recommended practices and avoid any risk of interrupting traffic to the API due to IP address changes. What should you do?

A.

Configure your GKE cluster with one node, and set the node to have a static external IP address. Ensure that the GKE cluster autoscaler is off. Send the external IP address of the node to the vendor to be added to the allowlist.

B.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with static IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

C.

Configure your GKE cluster with public nodes. Write a Cloud Function that pulls the public IP addresses of each node in the cluster. Trigger the function to run every day with Cloud Scheduler. Send the list to the vendor by email every day.

D.

Configure your GKE cluster with private nodes. Configure a Cloud NAT instance with dynamic IP addresses. Provide these IP addresses to the vendor to be added to the allowlist.

Question # 3

You are creating a Google Kubernetes Engine (GKE) cluster with a cluster autoscaler feature enabled. You need to make sure that each node of the cluster will run a monitoring pod that sends container metrics to a third-party monitoring solution. What should you do?

A.

Deploy the monitoring pod in a StatefulSet object.

B.

Deploy the monitoring pod in a DaemonSet object.

C.

Reference the monitoring pod in a Deployment object.

D.

Reference the monitoring pod in a cluster initializer at the GKE cluster creation time.

Question # 4

You need to track and verity modifications to a set of Google Compute Engine instances in your Google Cloud project. In particular, you want to verify OS system patching events on your virtual machines (VMs). What should you do?

A.

Review the Compute Engine activity logs Select and review the Admin Event logs

B.

Review the Compute Engine activity logs Select and review the System Event logs

C.

Install the Cloud Logging Agent In Cloud Logging review the Compute Engine syslog logs

D.

Install the Cloud Logging Agent In Cloud Logging, review the Compute Engine operation logs

Question # 5

Your company has a 3-tier solution running on Compute Engine. The configuration of the current infrastructure is shown below.

Each tier has a service account that is associated with all instances within it. You need to enable communication on TCP port 8080 between tiers as follows:

• Instances in tier #1 must communicate with tier #2.

• Instances in tier #2 must communicate with tier #3.

What should you do?

A.

1. Create an ingress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.2.0/24)• Protocols: allow all2. Create an ingress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.1.0/24)• Protocols: allow all

B.

1. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #2 service account• Source filter: all instances with tier #1 service account• Protocols: allow TCP:80802. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #3 service account• Source filter: all instances with tier #2 service account• Protocols: allow TCP: 8080

C.

1. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #2 service account• Source filter: all instances with tier #1 service account• Protocols: allow all2. Create an ingress firewall rule with the following settings:• Targets: all instances with tier #3 service account• Source filter: all instances with tier #2 service account• Protocols: allow all

D.

1. Create an egress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.2.0/24)• Protocols: allow TCP: 80802. Create an egress firewall rule with the following settings:• Targets: all instances• Source filter: IP ranges (with the range set to 10.0.1.0/24)• Protocols: allow TCP: 8080

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Google Associate-Cloud-Engineer Practice Exam FAQs

1. What is the Google Associate-Cloud-Engineer Exam?


The Google Associate-Cloud-Engineer certification validates your ability to deploy and secure applications, services, and infrastructure on Google Cloud.

2. Who should take the Google Associate-Cloud-Engineer Exam?


The Google Associate-Cloud-Engineer exam is ideal for cloud professionals with 1+ years of experience managing and deploying cloud solutions on GCP. It's also a valuable credential for IT professionals transitioning to the cloud or seeking to specialize in Google Cloud technologies.

3. What topics does the Associate-Cloud-Engineer Exam cover?


The Associate-Cloud-Engineer exam focuses on five key areas:

  • Setting up a cloud solution environment (projects, billing, IAM)
  • Planning and configuring compute resources (VMs, containers)
  • Deploying and implementing cloud solutions (storage, networking)
  • Ensuring successful operation (monitoring, logging, troubleshooting)
  • Configuring access and security (IAM, IAM policies)

4. How many questions are there in the Google Associate-Cloud-Engineer Exam?


The Google Associate-Cloud-Engineer exam typically consists of 50 multiple-choice questions.

5. What is the duration of the Google Associate-Cloud-Engineer Exam?


The duration of the Google Associate-Cloud-Engineer exam is 2 hours.

6. What is the passing score for the Google Associate-Cloud-Engineer Exam?


The passing score for the Google Associate-Cloud-Engineer exam is 70%.

7. What is the difference between Google Associate-Cloud-Engineer and Professional-Data-Engineer Certification Exams?


The Google Associate-Cloud-Engineer and Professional-Data-Engineer exams are both certifications focused on Google Cloud Platform (GCP), but they cater to different levels of expertise and job roles.

  • Google Associate-Cloud-Engineer: The Google Associate-Cloud-Engineer Exam focus broad overview of GCP services, including Compute Engine, Cloud Storage, Cloud SQL, networking, security, and monitoring.
  • Google Professional-Data-Engineer: The Google Professional-Data-Engineer Exam focus in-depth knowledge of data engineering concepts, including data pipelines, data warehousing, data lakes, and machine learning.

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