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

Google Cloud Certified - Associate Cloud Engineer

Last Update 19 hours ago Total Questions : 325

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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 # 4

You are building an application that stores relational data from users. Users across the globe will use this application. Your CTO is concerned about the scaling requirements because the size of the user base is unknown. You need to implement a database solution that can scale with your user growth with minimum configuration changes. Which storage solution should you use?

Cloud SQL

Cloud Spanner

Cloud Firestore

Cloud Datastore

Question # 5

You have an application that is currently processing transactions by using a group of managed VM instances. You need to migrate the application so that it is serverless and scalable. You want to implement an asynchronous transaction processing system, while minimizing management overhead. What should you do?

Install Kafka on VM instances to acknowledge incoming transactions. Use Cloud Run to process transactions.

Install Kafka on VM Instances to acknowledge incoming transactions. Use VM Instances to process transactions.

Use Pub/Sub to acknowledge incoming transactions. Use VM instances to process transactions.

Use Pub/Sub to acknowledge incoming transactions. Use Cloud Run to process transactions.

Answer:

Explanation:

The goal is to create a serverless, scalable, and asynchronous transaction processing system with minimal management overhead.

Serverless Requirement:Options involving installing Kafka on VMs (A, B) or using VM instances for processing (B, C) introduce management overhead associated with VMs (patching, scaling configuration, OS management) and Kafka cluster management, violating the serverless and minimal management criteria.

Asynchronous Requirement:Both Kafka and Pub/Sub can handle asynchronous messaging. However, Pub/Sub is Google Cloud's fully managed, serverless messaging service, inherently minimizing management overhead compared to self-managed Kafka on VMs.

Scalability and Processing:Cloud Run is a fully managed, serverless platform that automatically scales based on traffic, suitable for processing transactions without managing underlying infrastructure. VM instances require manual scaling configuration or managed instance groups, adding overhead.

Combining Pub/Sub for asynchronous message ingestion (fully managed, serverless) and Cloud Run for processing (fully managed, serverless, scalable) directly meets all requirements: serverless, scalable, asynchronous, and minimal management overhead. Option D is the only one that uses fully serverless components for both ingestion and processing.

[References:, Google Cloud Pub/Sub Overview: "Pub/Sub is an asynchronous and scalable messaging service..." -https://cloud.google.com/pubsub/docs/overview, Google Cloud Run Overview: "Cloud Run is a managed compute platform that lets you run containers directly on top of Google's scalable infrastructure." -https://cloud.google.com/run/docs/overview/what-is-cloud-run , Serverless Patterns (Pub/Sub + Cloud Run): This combination is a standard pattern for event-driven, serverless applications. -https://cloud.google.com/run/docs/triggering/pubsub-push, , , ]

Question # 6

You manage an App Engine Service that aggregates and visualizes data from BigQuery. The application is deployed with the default App Engine Service account. The data that needs to be visualized resides in a different project managed by another team. You do not have access to this project, but you want your application to be able to read data from the BigQuery dataset. What should you do?

Ask the other team to grant your default App Engine Service account the role of BigQuery Job User.

Ask the other team to grant your default App Engine Service account the role of BigQuery Data Viewer.

In Cloud IAM of your project, ensure that the default App Engine service account has the role of BigQuery Data Viewer.

In Cloud IAM of your project, grant a newly created service account from the other team the role of BigQuery Job User in your project.

Question # 7

Your company set up a complex organizational structure on Google Could Platform. The structure includes hundreds of folders and projects. Only a few team members should be able to view the hierarchical structure. You need to assign minimum permissions to these team members and you want to follow Google-recommended practices. What should you do?

Add the users to roles/browser role.

Add the users to roles/iam.roleViewer role.

Add the users to a group, and add this group to roles/browser role.

Add the users to a group, and add this group to roles/iam.roleViewer role.

Question # 8

During a recent audit of your existing Google Cloud resources, you discovered several users with email addresses outside of your Google Workspace domain.

You want to ensure that your resources are only shared with users whose email addresses match your domain. You need to remove any mismatched users, and you want to avoid having to audit your resources to identify mismatched users. What should you do?

Create a Cloud Scheduler task to regularly scan your projects and delete mismatched users.

Create a Cloud Scheduler task to regularly scan your resources and delete mismatched users.

Set an organizational policy constraint to limit identities by domain to automatically remove mismatched users.

Set an organizational policy constraint to limit identities by domain, and then retroactively remove the existing mismatched users.

Question # 9

You are configuring service accounts for an application that spans multiple projects. Virtual machines (VMs) running in the web-applications project need access to BigQuery datasets in crm-databases-proj. You want to follow Google-recommended practices to give access to the service account in the web-applications project. What should you do?

Give “project owner” for web-applications appropriate roles to crm-databases- proj

Give “project owner” role to crm-databases-proj and the web-applications project.

Give “project owner” role to crm-databases-proj and bigquery.dataViewer role to web-applications.

Give bigquery.dataViewer role to crm-databases-proj and appropriate roles to web-applications.

Question # 10

Your organization is a financial company that needs to store audit log files for 3 years. Your organization has hundreds of Google Cloud projects. You need to implement a cost-effective approach for log file retention. What should you do?

Create an export to the sink that saves logs from Cloud Audit to BigQuery.

Create an export to the sink that saves logs from Cloud Audit to a Coldline Storage bucket.

Write a custom script that uses logging API to copy the logs from Stackdriver logs to BigQuery.

Export these logs to Cloud Pub/Sub and write a Cloud Dataflow pipeline to store logs to Cloud SQL.