Professional-Cloud-Architect試験無料問題集「Google Certified Professional - Cloud Architect (GCP) 認定」

A. Build a roadmap to move the machine learning model training from Cloud GPUs to Cloud TPUs, which offer better results.

B. Monitor Compute Engine announcements for availability of newer CPU architectures, and deploy the model to them as soon as they are available for additional performance.

C. Save a history of recommendations and results of the recommendations in BigQuery, to be used as training data.

D. Export Cloud Machine Learning Engine performance metrics from Stackdriver to BigQuery, to be used to analyze the efficiency of the model.

A. 1. Mount the Cloud Storage bucket using gcsfuse on all backend Compute Engine instances
2. Serve muse files directly from the backend Compute Engine instance

B. 1. Create a managed instance group with Compute Engine instances
2. Create a global toad balancer and configure ii with two backbends
* Managed instance group
* Cloud Storage bucket
3. Enable Cloud CDN on the bucket backend

C. 1. Create a Cloud Filestore NFS volume and attach it to the backend Compute Engine instances
2. Download popular songs in Cloud Filestore
3. Serve music Wes directly from the backend Compute Engine instance

D. 1. Copy popular songs into CloudSQL as a blob
2. Update application code to retrieve data from CloudSQL when Cloud Storage is overloaded

A. Perform the following:
1) Create a managed instance group with f1-micro type machines.
2) Use a startup script to clone the repository, check out the production branch, install the dependencies, and start the Python app.
3) Restart the instances to automatically deploy new production releases.

B. Perform the following:
1) Create a managed instance group with n1-standard-1 type machines.
2) Build a Compute Engine image from the production branch that contains all of the dependencies and automatically starts the Python app.
3) Rebuild the Compute Engine image, and update the instance template to deploy new production releases.

C. Perform the following:
1) Create a Kubernetes Engine (GKE) cluster with n1-standard-4 type machines.
2) Build a Docker image from the master branch will all of the dependencies, and tag it with "latest".
3) Create a Kubernetes Deployment in the default namespace with the imagePullPolicy set to
"Always".
Restart the pods to automatically deploy new production releases.

D. Perform the following:
1) Create a Kubernetes Engine cluster with n1-standard-1 type machines.
2) Build a Docker image from the production branch with all of the dependencies, and tag it with the version number.
3) Create a Kubernetes Deployment with the imagePullPolicy set to "IfNotPresent" in the staging namespace, and then promote it to the production namespace after testing.

A. Schedule a cron script using gsutil is -lr gs://backups/** to find and remove items older than 90 days.

B. Write a lifecycle management rule in JSON and push it to the bucket with gsutil.

C. Schedule a cron script using gsutil ls -1 gs://backups/** to find and remove items older than 90 days and schedule it with cron.

D. Write a lifecycle management rule in XML and push it to the bucket with gsutil.

A. Create a BigQuery time-partitioned table for the European data, and set the partition expiration period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

B. Create a BigQuery time-partitioned table for the European data, and set the partition period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action with an Age condition of 36 months.

C. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to enable lifecycle management using a DELETE action with an Age condition of 36 months.

D. Create a BigQuery table for the European data, and set the table retention period to 36 months. For Cloud Storage, use gsutil to create a SetStorageClass to NONE action when with an Age condition of
36 months.

A. Create an instance template from the existing disk. Create a custom image from the instance template.Create an autoscaled managed instance group from the custom image.

B. Create a snapshot of the existing disk. Create a custom image from the snapshot. Create an autoscaled managed instance group from the custom image.

C. Create a custom image from the existing disk. Create an instance template from the custom image.
Create an autoscaled managed instance group from the instance template.

D. Create a snapshot of the existing disk. Create an instance template from the snapshot. Create an autoscaled managed instance group from the instance template.

A. Restore a backup of the application database from a time before the application became slow.

B. Inspect the logs and metrics from the instances in Cloud Logging and Cloud Monitoring.

C. Deploy the applications on a managed instance group with autoscaling enabled. Add a load balancer in front of the managed instance group, and have the users connect to the IP of the load balancer.

D. Change the Compute Engine Instances behind the application to a machine type with more CPU and memory.

A. Use a Google Container Engine cluster to serve the website and store data to persistent disk.

B. Use a single compute Engine virtual machine (VM) to host a web server, backed by Google Cloud SQL.

C. Use a managed instance group to serve the website and Google Cloud Bigtable to store user data.

D. Use Google App Engine to serve the website and Google Cloud Datastore to store user data.

A. Create an egress rule with priority 100 to deny all traffic for all instances. Create another egress rule with priority 1000 to allow the Active Directory traffic for all instances.

B. Create an egress rule with priority 1000 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 100 to block all traffic for all instances.

C. Create an egress rule with priority 100 to allow the Active Directory traffic. Rely on the implied deny egress rule with priority 1000 to block all traffic for all instances.

D. Create an egress rule with priority 1000 to deny all traffic for all instances. Create another egress rule with priority 100 to allow the Active Directory traffic for all instances.

A. Google Cloud Dataflow

B. Google Compute Engine with Google BigQuery

C. Google Container Engine with Bigtable

D. Google Cloud Dataproc

A. Set the memcache service level to shared. Create a cron task that runs every minute to save all expected queries to a key called "cached-queries".

B. Set the memcache service level to dedicated. Create a cron task that runs every minute to populate the cache with keys containing query results.

C. Set the memcache service level to shared. Create a key called "cached-queries", and return database values from the key before using a query to Cloud SQL.

D. Set the memcache service level to dedicated. Create a key from the hash of the query, and return database values from memcache before issuing a query to Cloud SQL.

A. Configure Container Registry to use vulnerability scanning to confirm that there are no vulnerabilities before deploying the workload.

B. Enable Binary Authorization on GKE, and sign containers as part of a CI/CD pipeline.

C. Configure Jenkins to utilize Kritis to cryptographically sign a container as part of a CI/CD pipeline.

D. Configure Container Registry to only allow trusted service accounts to create and deploy containers from the registry.

A. Upload the required installation files to Cloud Storage and use firewall rules to block all traffic except the IP address range for Cloud Storage. Download the files to the VM using gsutil.

B. Upload the required installation files to Cloud Source Repositories. Configure the VM on a subnet with a Private Google Access subnet. Assign only an internal IP address to the VM. Download the installation files to the VM using gcloud.

C. Upload the required installation files to Cloud Storage. Configure the VM on a subnet with a Private Google Access subnet. Assign only an internal IP address to the VM. Download the installation files to the VM using gsutil.

D. Upload the required installation files to Cloud Source Repositories and use firewall rules to block all traffic except the IP address range for Cloud Source Repositories. Download the files to the VM using gsutil.

A. Install gcloud on all of your workstations Run the command gcloud components auto-update on each workstation

B. Use a package manager to install gcloud on your workstations instead of installing it manually

C. Create a Compute Engine instance and install gcloud on the instance Connect to this instance via SSH to always use the same gcloud installation when interacting with Google Cloud

D. Use Google Cloud Shell in the Google Cloud Console to interact with Google Cloud