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Google Cloud Certified Professional-Cloud-Architect Google Study Notes

Google Certified Professional - Cloud Architect (GCP) Questions and Answers

Question 5

For this question, refer to the TerramEarth case study. You are asked to design a new architecture for the

ingestion of the data of the 200,000 vehicles that are connected to a cellular network. You want to follow

Google-recommended practices.

Considering the technical requirements, which components should you use for the ingestion of the data?

Options:

A.

Google Kubernetes Engine with an SSL Ingress

B.

Cloud IoT Core with public/private key pairs

C.

Compute Engine with project-wide SSH keys

D.

Compute Engine with specific SSH keys

Question 6

TerramEarth has a legacy web application that you cannot migrate to cloud. However, you still want to build a cloud-native way to monitor the application. If the application goes down, you want the URL to point to a "Site is unavailable" page as soon as possible. You also want your Ops team to receive a notification for the issue. You need to build a reliable solution for minimum cost

What should you do?

Options:

A.

Create a scheduled job in Cloud Run to invoke a container every minute. The container will check the application URL If the application is down, switch the URL to the "Site is unavailable" page, and notify the Ops team.

B.

Create a cron job on a Compute Engine VM that runs every minute. The cron job invokes a Python program to check the application URL If the application is down, switch the URL to the "Site is unavailable" page, and notify the Ops team.

C.

Create a Cloud Monitoring uptime check to validate the application URL If it fails, put a message in a Pub/Sub queue that triggers a Cloud Function to switch the URL to the "Site is unavailable" page, and notify the Ops team.

D.

Use Cloud Error Reporting to check the application URL If the application is down, switch the URL to the "Site is unavailable" page, and notify the Ops team.

Question 7

For this question, refer to the TerramEarth case study. To be compliant with European GDPR regulation, TerramEarth is required to delete data generated from its European customers after a period of 36 months when it contains personal data. In the new architecture, this data will be stored in both Cloud Storage and BigQuery. What should you do?

Options:

A.

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.

B.

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.

C.

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.

D.

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.

Question 8

For this question, refer to the TerramEarth case study. A new architecture that writes all incoming data to

BigQuery has been introduced. You notice that the data is dirty, and want to ensure data quality on an

automated daily basis while managing cost.

What should you do?

Options:

A.

Set up a streaming Cloud Dataflow job, receiving data by the ingestion process. Clean the data in a Cloud Dataflow pipeline.

B.

Create a Cloud Function that reads data from BigQuery and cleans it. Trigger it. Trigger the Cloud Function from a Compute Engine instance.

C.

Create a SQL statement on the data in BigQuery, and save it as a view. Run the view daily, and save the result to a new table.

D.

Use Cloud Dataprep and configure the BigQuery tables as the source. Schedule a daily job to clean the data.