Associate-Cloud-Engineer 無料問題集「Google Associate Cloud Engineer」

（A）Create a custom role, and add all the required compute.disks.list and compute, images.list permissions as includedPermissions. Grant the custom role to the user at the project level.

（B）Grant the Compute Storage Admin role at the project level.

（C）Create a custom role based on the Compute Storage Admin role. Exclude unnecessary permissions from the custom role. Grant the custom role to the user at the project level.

（D）Create a custom role based on the Compute Image User role Add the compute.disks, list to the includedPermissions field Grant the custom role to the user at the project level

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

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

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

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

（A）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.

（B）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.

（C）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.

（D）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.

（A）Export the billing data to BigQuery. Create a Cloud Function that uses BigQuery to sum the egress network costs of the exported billing data for the Apache web server for the current month and sends an email if it is over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.

（B）Set up a budget alert on the project with an amount of 100 dollars, a threshold of 100%, and notification type of "email."

（C）Use the Stackdriver Logging Agent to export the Apache web server logs to Stackdriver Logging.Create a Cloud Function that uses BigQuery to parse the HTTP response log data in Stackdriver for the current month and sends an email if the size of all HTTP responses, multiplied by current GCP egress prices, totals over 100 dollars. Schedule the Cloud Function using Cloud Scheduler to run hourly.

（D）Set up a budget alert on the billing account with an amount of 100 dollars, a threshold of 100%, and notification type of "email."

（A）1 Create a Service Account and apply roles/viewer on the three projects
2. Collect metrics and publish them lo the Cloud Monitoring API
3. Add CPU and network Charts for each of the three projects.

（B）1. Create a fourth Google Cloud project
2 Create a Cloud Workspace from the fourth project and add the other three projects

（C）1. Create a Cloud Monitoring Dashboard.
2. Select the CPU and Network metrics from the three projects.
3. Add CPU and network Charts lot each of the three protects.

（D）1. Create a Cloud Monitoring Dashboard
2. Collect metrics and publish them into the Pub/Sub topics 3. Add CPU and network Charts (or each of (he three projects

（A）Obtain OAuth 2.0 credentials, configure the user consent screen, and set up OAuth 2.0 for Web Server Applications.

（B）In Cloud Identity, set up SSO with Google as an identity provider to access custom SAML apps.

（C）Obtain OAuth 2.0 credentials, configure the user consent screen, and set up OAuth 2.0 for Mobile & Desktop Apps.

（D）In Cloud Identity, set up SSO with a third-party identity provider with Google as a service provider.

（A）Upload the data into Cloud Spanner using the import function in the console.

（B）Upload the data to BigQuery using the bq command line tool.

（C）Upload the data into Cloud SQL using the import function in the console.

（D）Upload the data to Cloud Storage using the gsutil command line tool.

（A）When creating the VMs, set the service account's API scope for Compute Engine to read/write.

（B）Download the private key from the service account, and add it to each VMs custom metadata.

（C）Download the private key from the service account, and add the private key to each VM's SSH keys.

（D）Grant the service account the IAM Role of Compute Storage Admin in the project called proj-vm.

（A）Ask your ML team to add the "accelerator: gpu" annotation to their pod specification.

（B）Add a new, GPU-enabled, node pool to the GKE cluster. Ask your ML team to add the cloud.google.com/gke -accelerator: nvidia-tesla-p100 nodeSelector to their pod specification.

（C）Recreate all the nodes of the GKE cluster to enable GPUs on all of them.

（D）Create your own Kubernetes cluster on top of Compute Engine with nodes that have GPUs. Dedicate this cluster to your ML team.

（A）Deploy the application on Cloud Run and configure autoscaling.

（B）Deploy the application on a managed instance group and configure autoscaling.

（C）Deploy the application on Cloud Functions and configure the maximum number instances.

（D）Deploy the application on a Kubernetes Engine cluster and configure node pool autoscaling.

（A）Create an IAM policy and grant all compute. instanceAdmln." permissions to the policy Attach the policy to the DevOps group.

（B）Create a custom role at the folder level and grant all compute. instanceAdmln. * permissions to the role Grant the custom role to the DevOps group.

（C）Grant the basic role roles/viewer and the predefined role roles/compute.admin to the DevOps group.

（D）Grant the basic role roles/editor to the DevOps group.

（A）Save the incoming votes to Firestore. Use Cloud Scheduler to trigger a Cloud Functions instance to periodically process the votes.

（B）Save the incoming votes to Pub/Sub. Use the Pub/Sub topic to trigger a Cloud Functions instance to process the votes.

（C）Use a dedicated instance to process the incoming votes. Send the votes directly to this instance.

（D）Save the incoming votes to a JSON file on Cloud Storage. Process the votes in a batch at the end of the day.

（A）Create an organization to contain all the dev projects. Create an Identity and Access Management (IAM) policy to limit the resources in US regions.

（B）Create an Identity and Access Management <IAM) policy to restrict the resources locations in the US.
Apply the policy to all dev projects.

（C）Create a folder to contain all the dev projects Create an organization policy to limit resources in US locations.

（D）Create an Identity and Access Management (IAM)policy to restrict the resources locations in all dev projects. Apply the policy to all dev roles.