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Free Google Associate Cloud Engineer Exam Braindumps (page: 30)

Page 29 of 74
PDF with 290 Questions

You need to assign a Cloud Identity and Access Management (Cloud IAM) role to an external auditor. The auditor needs to have permissions to review your Google Cloud Platform (GCP) Audit Logs and also to review your Data Access logs.
What should you do?

  1. Assign the auditor the IAM role roles/logging.privateLogViewer. Perform the export of logs to Cloud Storage.
  2. Assign the auditor the IAM role roles/logging.privateLogViewer. Direct the auditor to also review the logs for changes to Cloud IAM policy.
  3. Assign the auditor's IAM user to a custom role that has logging.privateLogEntries.list permission. Perform the export of logs to Cloud Storage.
  4. Assign the auditor's IAM user to a custom role that has logging.privateLogEntries.list permission. Direct the auditor to also review the logs for changes to Cloud IAM policy.

Answer(s): B

Explanation:

Google Cloud provides Cloud Audit Logs, which is an integral part of Cloud Logging. It consists of two log streams for each project: Admin Activity and Data Access, which are generated by Google Cloud services to help you answer the question of who did what, where, and when? within your Google Cloud projects.

Ref: https://cloud.google.com/iam/docs/job-functions/auditing#scenario_external_auditors



You are managing several Google Cloud Platform (GCP) projects and need access to all logs for the past 60 days. You want to be able to explore and quickly analyze the log contents. You want to follow Google- recommended practices to obtain the combined logs for all projects.
What should you do?

  1. Navigate to Stackdriver Logging and select resource.labels.project_id="*"
  2. Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days.
  3. Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days.
  4. Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days.

Answer(s): B

Explanation:

Navigate to Stackdriver Logging and select resource.labels.project_id=*. is not right. Log entries are held in Stackdriver Logging for a limited time known as the retention period which is 30 days (default configuration). After that, the entries are deleted. To keep log entries longer, you need to export them outside of Stackdriver Logging by configuring log sinks. Ref: https://cloud.google.com/blog/products/gcp/best-practices-for-working-with-google-cloud- audit-logging

Configure a Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery. Configure the table expiration to 60 days. is not right.
While this works, it makes no sense to use Cloud Scheduler job to read from Stackdriver and store the logs in BigQuery when Google provides a feature (export sinks) that does exactly the same thing and works out of the box.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2

Create a Stackdriver Logging Export with a Sink destination to Cloud Storage. Create a lifecycle rule to delete objects after 60 days. is not right.
You can export logs by creating one or more sinks that include a logs query and an export destination. Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2 Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization. Ref: https://cloud.google.com/logging/docs/export/aggregated_sinks

Either way, we now have the data in Cloud Storage, but querying logs information from Cloud Storage is harder than Querying information from BigQuery dataset. For this reason, we should prefer Big Query over Cloud Storage.
Create a Stackdriver Logging Export with a Sink destination to a BigQuery dataset. Configure the table expiration to 60 days. is the right answer.

You can export logs by creating one or more sinks that include a logs query and an export destination. Supported destinations for exported log entries are Cloud Storage, BigQuery, and Pub/Sub.
Ref: https://cloud.google.com/logging/docs/export/configure_export_v2

Sinks are limited to exporting log entries from the exact resource in which the sink was created: a Google Cloud project, organization, folder, or billing account. If it makes it easier to exporting from all projects of an organication, you can create an aggregated sink that can export log entries from all the projects, folders, and billing accounts of a Google Cloud organization. Ref: https://cloud.google.com/logging/docs/export/aggregated_sinks

Either way, we now have the data in a BigQuery Dataset. Querying information from a Big Query dataset is easier and quicker than analyzing contents in Cloud Storage bucket. As our requirement is to Quickly analyze the log contents, we should prefer Big Query over Cloud Storage. Also, You can control storage costs and optimize storage usage by setting the default table expiration for newly created tables in a dataset. If you set the property when the dataset is created, any table created in the dataset is deleted after the expiration period. If you set the property after the dataset is created, only new tables are deleted after the expiration period. For example, if you set the default table expiration to 7 days, older data is automatically deleted after 1 week.
Ref: https://cloud.google.com/bigquery/docs/best-practices-storage


Reference:

https://cloud.google.com/blog/products/gcp/best-practices-for-working-with-google- cloud-audit- logging



You need to reduce GCP service costs for a division of your company using the fewest possible steps. You need to turn off all configured services in an existing GCP project.
What should you do?

  1. 1. Verify that you are assigned the Project Owners IAM role for this project.
    2. Locate the project in the GCP console, click Shut down and then enter the project ID.
  2. 1. Verify that you are assigned the Project Owners IAM role for this project.
    2. Switch to the project in the GCP console, locate the resources and delete them.
  3. 1. Verify that you are assigned the Organizational Administrator IAM role for this project.
    2. Locate the project in the GCP console, enter the project ID and then click Shut down.
  4. 1. Verify that you are assigned the Organizational Administrators IAM role for this project.
    2. Switch to the project in the GCP console, locate the resources and delete them.

Answer(s): A

Explanation:

https://cloud.google.com/run/docs/tutorials/gcloud https://cloud.google.com/resource-manager/docs/creating-managing-projects https://cloud.google.com/iam/docs/understanding-roles#primitive_roles

You can shut down projects using the Cloud Console.
When you shut down a project, this immediately happens: All billing and traffic serving stops, You lose access to the project, The owners of the project will be notified and can stop the deletion within 30 days, The project will be scheduled to be deleted after 30 days. However, some resources may be deleted much earlier.



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?

  1. Give "project owner" for web-applications appropriate roles to crm-databases- proj
  2. Give "project owner" role to crm-databases-proj and the web-applications project.
  3. Give "project owner" role to crm-databases-proj and bigquery.dataViewer role to web- applications.
  4. Give bigquery.dataViewer role to crm-databases-proj and appropriate roles to web-applications.

Answer(s): C


Reference:

https://cloud.google.com/blog/products/gcp/best-practices-for-working-with-google- cloud-audit- logging bigquery.dataViewer role provides permissions to read the datasets metadata and list tables in the dataset as well as Read data and metadata from the datasets tables. This is exactly what we need to fulfil this requirement and follows the least privilege principle. Ref: https://cloud.google.com/iam/docs/understanding-roles#bigquery-roles






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