Associate-Cloud-Engineer Google Cloud Certified - Associate Cloud Engineer exact Exam Questions

Google Cloud Certified - Associate Cloud Engineer

Last Update 13 hours ago Total Questions : 332

The Google Cloud Certified - Associate Cloud Engineer content is now fully updated, with all current exam questions added 13 hours ago. Deciding to include Associate-Cloud-Engineer practice exam questions in your study plan goes far beyond basic test preparation.

You'll find that our Associate-Cloud-Engineer exam questions frequently feature detailed scenarios and practical problem-solving exercises that directly mirror industry challenges. Engaging with these Associate-Cloud-Engineer sample sets allows you to effectively manage your time and pace yourself, giving you the ability to finish any Google Cloud Certified - Associate Cloud Engineer practice test comfortably within the allotted time.

Question # 21

You are running multiple microservices in a Kubernetes Engine cluster. One microservice is rendering images. The microservice responsible for the image rendering requires a large amount of CPU time compared to the memory it requires. The other microservices are workloads that are optimized for n1-standard machine types. You need to optimize your cluster so that all workloads are using resources as efficiently as possible. What should you do?

Assign the pods of the image rendering microservice a higher pod priority than the older microservices

Create a node pool with compute-optimized machine type nodes for the image rendering microservice Use the node pool with general-purposemachine type nodes for the other microservices

Use the node pool with general-purpose machine type nodes for lite mage rendering microservice Create a nodepool with compute-optimized machine type nodes for the other microservices

Configure the required amount of CPU and memory in the resource requests specification of the image rendering microservice deployment Keep the resource requests for the other microservices at the default

Question # 22

Your Dataproc cluster runs in a single Virtual Private Cloud (VPC) network in a single subnet with range 172.16.20.128/25. There are no private IP addresses available in the VPC network. You want to add new VMs to communicate with your cluster using the minimum number of steps. What should you do?

Modify the existing subnet range to 172.16.20.0/24.

Create a new Secondary IP Range in the VPC and configure the VMs to use that range.

Create a new VPC network for the VMs. Enable VPC Peering between the VMs’ VPC network and the Dataproc cluster VPC network.

Create a new VPC network for the VMs with a subnet of 172.32.0.0/16. Enable VPC network Peering between the Dataproc VPC network and the VMs VPC network. Configure a custom Route exchange.

Question # 23

You want to deploy an application on Cloud Run that processes messages from a Cloud Pub/Sub topic. You want to follow Google-recommended practices. What should you do?

1. Create a Cloud Function that uses a Cloud Pub/Sub trigger on that topic.2. Call your application on Cloud Run from the Cloud Function for every message.

1. Grant the Pub/Sub Subscriber role to the service account used by Cloud Run.2. Create a Cloud Pub/Sub subscription for that topic.3. Make your application pull messages from that subscription.

1. Create a service account.2. Give the Cloud Run Invoker role to that service account for your Cloud Run application.3. Create a Cloud Pub/Sub subscription that uses that service account and uses your Cloud Run application as the push endpoint.

1. Deploy your application on Cloud Run on GKE with the connectivity set to Internal.2. Create a Cloud Pub/Sub subscription for that topic.3. In the same Google Kubernetes Engine cluster as your application, deploy a container that takes the messages and sends them to your application.

Question # 24

You are designing an application that uses WebSockets and HTTP sessions that are not distributed across the web servers. You want to ensure the application runs properly on Google Cloud Platform. What should you do?

Meet with the cloud enablement team to discuss load balancer options.

Redesign the application to use a distributed user session service that does not rely on WebSockets and HTTP sessions.

Review the encryption requirements for WebSocket connections with the security team.

Convert the WebSocket code to use HTTP streaming.

Question # 25

You are developing an application that will be deployed on Google Cloud. The application will use a service account to retrieve data from BigGuery. Before you deploy your application, you want to test the permissions of this service account from your local machine to ensure there will be no authentication issues. You want to ensure that you use the most secure method while following Google-recommended practices What should you do?

Configure the gcloud CLI with Application Default Credentials using your user account. Issue a relevant BigGuery request through the gcloud CLI to test the access.

Grant the service account the BlgQuery Administrator 1AM role to ensure the service account has all required access.

Generate a service account key, and configure the gcloud CLI to use this key. Issue a relevant BlgQuery request through the gcloud CLI to test the access.

Configure the gcloud CLI to use service account impersonation. Issue a relevant BigQuery request through the gcloud CLI to test the access.

Question # 26

You have been asked to create robust Virtual Private Network (VPN) connectivity between a new Virtual Private Cloud (VPC) and a remote site. Key requirements include dynamic routing, a shared address space of 10.19.0.1/22, and no overprovisioning of tunnels during a failover event. You want to follow Google-recommended practices to set up a high availability Cloud VPN. What should you do?

Use a custom mode VPC network, configure static routes, and use active/passive routing

Use an automatic mode VPC network, configure static routes, and use active/active routing

Use a custom mode VPC network use Cloud Router border gateway protocol (86P) routes, and use active/passive routing

Use an automatic mode VPC network, use Cloud Router border gateway protocol (BGP) routes and configure policy-based routing

Question # 27

Your company’s infrastructure is on-premises, but all machines are running at maximum capacity. You want to burst to Google Cloud. The workloads on Google Cloud must be able to directly communicate to the workloads on-premises using a private IP range. What should you do?

In Google Cloud, configure the VPC as a host for Shared VPC.

In Google Cloud, configure the VPC for VPC Network Peering.

Create bastion hosts both in your on-premises environment and on Google Cloud. Configure both as proxy servers using their public IP addresses.

Set up Cloud VPN between the infrastructure on-premises and Google Cloud.

Question # 28

Your company has embraced a hybrid cloud strategy where some of the applications are deployed on Google Cloud. A Virtual Private Network (VPN) tunnel connects your Virtual Private Cloud (VPC) in Google Cloud with your company ' s on-premises network. Multiple applications in Google Cloud need to connect to an on-premises database server, and you want to avoid having to change the IP configuration in all of your applications when the IP of the database changes.

What should you do?

Configure Cloud NAT for all subnets of your VPC to be used when egressing from the VM instances.

Create a private zone on Cloud DNS, and configure the applications with the DNS name.

Configure the IP of the database as custom metadata for each instance, and query the metadata server.

Query the Compute Engine internal DNS from the applications to retrieve the IP of the database.

Question # 29

You have sensitive data stored in three Cloud Storage buckets and have enabled data access logging. You want to verify activities for a particular user for these buckets, using the fewest possible steps. You need to verify the addition of metadata labels and which files have been viewed from those buckets. What should you do?

Using the GCP Console, filter the Activity log to view the information.

Using the GCP Console, filter the Stackdriver log to view the information.

View the bucket in the Storage section of the GCP Console.

Create a trace in Stackdriver to view the information.

Question # 30

(You have an application running inside a Compute Engine instance. You want to provide the application with secure access to a BigQuery dataset. You must ensure that credentials are only valid for a short period of time, and your application will only have access to the intended BigQuery dataset. You want to follow Google-recommended practices and minimize your operational costs. What should you do?)

Attach a custom service account to the instance, and grant the service account the BigQuery Data Viewer IAM role on the project.

Attach a new service account to the instance every hour, and grant the service account the BigQuery Data Viewer IAM role on the dataset.

Attach a custom service account to the instance, and grant the service account the BigQuery Data Viewer IAM role on the dataset.

Attach a new service account to the instance every hour, and grant the service account the BigQuery Data Viewer IAM role on the project.

Answer:

Explanation:

Comprehensive and Detailed In Depth Explanation:

The core requirements are secure access to a specific BigQuery dataset from a Compute Engine instance, using short-lived credentials, adhering to Google ' s best practices, and minimizing operational overhead.

A. Project-level IAM role: Granting the BigQuery Data Viewer role at the project level gives the service account broad access to all BigQuery datasets within that project. This violates the principle of least privilege, a fundamental security best practice, as the application should only have access to the designated dataset.

B. Hourly new service account with dataset-level role: While this aims to achieve short-lived credentials, the operational burden of creating, attaching, and managing IAM policies for a new service account every hour is significant and not a Google-recommended practice for routine access. It introduces unnecessary complexity and potential for errors.

C. Custom service account with dataset-level IAM role: This is the recommended and most efficient approach. You create a dedicated Google Cloud service account specifically for this application. You then grant this service account the necessary IAM role (e.g., BigQuery Data Viewer, or a more specific custom role) directly on the target BigQuery dataset. When the Compute Engine instance runs as this service account, the Google Cloud client libraries automatically handle the acquisition and rotation of short-lived OAuth 2.0 access tokens from the instance ' s metadata server. This eliminates the need to manage long-lived credentials (like service account keys) and ensures the application only has access to the intended dataset. This adheres to the principle of least privilege and minimizes operational costs.

D. Hourly new service account with project-level role: This option combines the high operational overhead of frequently creating new service accounts with the security risk of granting overly permissive project-level access. It is not a recommended practice.

Therefore, the most secure, cost-effective, and operationally efficient solution is to create a custom service account, attach it to the Compute Engine instance, and grant it the appropriate BigQuery IAM role specifically on the target dataset. The platform handles the short-lived credentials automatically.

Google Cloud Documentation References:

Creating and enabling service accounts for instances: https://cloud.google.com/compute/docs/access/create-enable-service-accounts-for-instances - Explains how to create and associate service accounts with Compute Engine VMs.

Granting, changing, and revoking access to resources: https://cloud.google.com/iam/docs/granting-changing-revoking-access - Details how to manage IAM policies and grant roles to service accounts on specific resources (like BigQuery datasets).

BigQuery IAM roles: https://cloud.google.com/bigquery/docs/control-access - Provides information on the various IAM roles available for controlling access to BigQuery resources at different levels (project, dataset, table, etc.).

Best practices for using service accounts: https://cloud.google.com/iam/docs/best-practices-for-using-service-accounts - Emphasizes the importance of the principle of least privilege and avoiding the management of long-lived service account keys when possible (relying on the metadata server for short-lived tokens).

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