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

Google Cloud Certified - Associate Cloud Engineer

Last Update 11 hours ago Total Questions : 332

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Question # 51

Your company requires that Google Cloud products are created with a specific configuration to comply with your company ' s security policies You need to implement a mechanism that will allow software engineers at your company to deploy and update Google Cloud products in a preconfigured and approved manner. What should you do?

Create Java packages that utilize the Google Cloud Client Libraries for Java to configure Google Cloud products. Store and share the packages in a source code repository.

Create bash scripts that utilize the Google Cloud CLI to configure Google Cloud products. Store and share the bash scripts in a source code repository.

Create Terraform modules that utilize the Google Cloud Terraform Provider to configure Google Cloud products. Store and share the modules in a source code repository.

Use the Google Cloud APIs by using curl to configure Google Cloud products. Store and share the curl commands in a source code repository.

Question # 52

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 # 53

You have an application that looks for its licensing server on the IP 10.0.3.21. You need to deploy the licensing server on Compute Engine. You do not want to change the configuration of the application and want the application to be able to reach the licensing server. What should you do?

Reserve the IP 10.0.3.21 as a static internal IP address using gcloud and assign it to the licensing server.

Reserve the IP 10.0.3.21 as a static public IP address using gcloud and assign it to the licensing server.

Use the IP 10.0.3.21 as a custom ephemeral IP address and assign it to the licensing server.

Start the licensing server with an automatic ephemeral IP address, and then promote it to a static internal IP address.

Question # 54

You built an application on Google Cloud Platform that uses Cloud Spanner. Your support team needs to monitor the environment but should not have access to table data. You need a streamlined solution to grant the correct permissions to your support team, and you want to follow Google-recommended practices. What should you do?

Add the support team group to the roles/monitoring.viewer role

Add the support team group to the roles/spanner.databaseUser role.

Add the support team group to the roles/spanner.databaseReader role.

Add the support team group to the roles/stackdriver.accounts.viewer role.

Question # 55

You need to create a new billing account and then link it with an existing Google Cloud Platform project. What should you do?

Verify that you are Project Billing Manager for the GCP project. Update the existing project to link it to the existing billing account.

Verify that you are Project Billing Manager for the GCP project. Create a new billing account and link the new billing account to the existing project.

Verify that you are Billing Administrator for the billing account. Create a new project and link the new project to the existing billing account.

Verify that you are Billing Administrator for the billing account. Update the existing project to link it to the existing billing account.

Question # 56

You need to enable traffic between multiple groups of Compute Engine instances that are currently running two different GCP projects. Each group of Compute Engine instances is running in its own VPC. What should you do?

Verify that both projects are in a GCP Organization. Create a new VPC and add all instances.

Verify that both projects are in a GCP Organization. Share the VPC from one project and request that the Compute Engine instances in the other project use this shared VPC.

Verify that you are the Project Administrator of both projects. Create two new VPCs and add all instances.

Verify that you are the Project Administrator of both projects. Create a new VPC and add all instances.

Question # 57

You want to select and configure a solution for storing and archiving data on Google Cloud Platform. You need to support compliance objectives for data from one geographic location. This data is archived after 30 days and needs to be accessed annually. What should you do?

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

Select Multi-Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Nearline Storage.

Select Regional Storage. Add a bucket lifecycle rule that archives data after 30 days to Coldline Storage.

Question # 58

(Your company was recently impacted by a service disruption that caused multiple Dataflow jobs to get stuck, resulting in significant downtime in downstream applications and revenue loss. You were able to resolve the issue by identifying and fixing an error you found in the code. You need to design a solution with minimal management effort to identify when jobs are stuck in the future to ensure that this issue does not occur again. What should you do?)

Set up Error Reporting to identify stack traces that indicate slowdowns in Dataflow jobs. Set up alerts based on these log entries.

Use the Personalized Service Health dashboard to identify issues with Dataflow jobs across regions.

Update the Dataflow job configurations to send messages to a Pub/Sub topic when there are delays. Configure a backup Dataflow job to process jobs that are delayed. Use Cloud Tasks to trigger an alert when messages are pushed to the Pub/Sub topic.

Set up Cloud Monitoring alerts on the data freshness metric for the Dataflow jobs to receive a notification when a certain threshold is reached.

Answer:

Explanation:

Comprehensive and Detailed In Depth Explanation:

The goal is to proactively identify stuck Dataflow jobs with minimal management effort. Let ' s analyze each option:

A. Error Reporting for slowdowns: Error Reporting primarily focuses on capturing and aggregating exceptions and errors (stack traces). While a stuck job might eventually throw an error, it might also just become unresponsive without generating explicit errors. Relying solely on Error Reporting might not provide timely detection of stuck jobs. Identifying stack traces that indicate slowdowns can also be complex and require significant manual configuration and analysis.

B. Personalized Service Health dashboard: The Personalized Service Health dashboard provides information about Google Cloud service incidents that might be affecting your resources. While it can alert you to broader Dataflow service outages, it won ' t specifically identify individual stuck jobs due to application-level errors or logic within your Dataflow pipeline.

C. Pub/Sub messages for delays, backup job, and Cloud Tasks alerts: This approach involves significant custom implementation and management. You would need to instrument your Dataflow jobs to detect delays, send messages to Pub/Sub, manage a backup job, and configure Cloud Tasks for alerting. This adds considerable operational overhead and complexity.

D. Cloud Monitoring alerts on data freshness metric: Dataflow provides built-in metrics, including " data freshness " (or similar metrics like " system lag " or " processing time " ), which indicate how far behind the pipeline is in processing data. If a job gets stuck, the data freshness will deteriorate beyond an acceptable threshold. Cloud Monitoring allows you to easily set up alerts based on these built-in metrics. This requires minimal custom coding and leverages the platform ' s existing monitoring capabilities, aligning with the " minimal management effort " requirement.

Therefore, setting up Cloud Monitoring alerts on relevant Dataflow metrics like data freshness is the most efficient and recommended way to detect stuck Dataflow jobs with minimal management overhead.

Google Cloud Documentation References:

Monitoring Dataflow Pipelines: https://cloud.google.com/dataflow/docs/guides/monitoring-your-pipeline - This document details the various metrics available for monitoring Dataflow jobs in Cloud Monitoring, including metrics related to processing time, system lag, and data freshness.

Creating Alerts in Cloud Monitoring: https://cloud.google.com/monitoring/alerts/create - Explains how to set up alerts based on metrics collected by Cloud Monitoring.

Dataflow Metrics: https://cloud.google.com/dataflow/docs/reference/monitoring-metrics - Provides a comprehensive list of Dataflow metrics that can be used for monitoring and alerting.

Question # 59

You need to produce a list of the enabled Google Cloud Platform APIs for a GCP project using the gcloud command line in the Cloud Shell. The project name is my-project. What should you do?

Run gcloud projects list to get the project ID, and then run gcloud services list --project < project ID > .

Run gcloud init to set the current project to my-project, and then run gcloud services list --available.

Run gcloud info to view the account value, and then run gcloud services list --account < Account > .

Run gcloud projects describe < project ID > to verify the project value, and then run gcloud services list --available.

Question # 60

You have a development project with appropriate IAM roles defined. You are creating a production project and want to have the same IAM roles on the new project, using the fewest possible steps. What should you do?

Use gcloud iam roles copy and specify the production project as the destination project.

Use gcloud iam roles copy and specify your organization as the destination organization.

In the Google Cloud Platform Console, use the ‘create role from role’ functionality.

In the Google Cloud Platform Console, use the ‘create role’ functionality and select all applicable permissions.