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Google Professional-Cloud-Architect Online Access

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

Question 45

For this question, refer to the JencoMart case study.

JencoMart has built a version of their application on Google Cloud Platform that serves traffic to Asia. You want to measure success against their business and technical goals. Which metrics should you track?

Options:

A.

Error rates for requests from Asia

B.

Latency difference between US and Asia

C.

Total visits, error rates, and latency from Asia

D.

Total visits and average latency for users in Asia

E.

The number of character sets present in the database

Question 46

For this question, refer to the JencoMart case study.

JencoMart wants to move their User Profiles database to Google Cloud Platform. Which Google Database should they use?

Options:

A.

Cloud Spanner

B.

Google BigQuery

C.

Google Cloud SQL

D.

Google Cloud Datastore

Question 47

For this question, refer to the TerramEarth case study

You analyzed TerramEarth's business requirement to reduce downtime, and found that they can achieve a majority of time saving by reducing customers' wait time for parts You decided to focus on reduction of the 3 weeks aggregate reporting time Which modifications to the company's processes should you recommend?

Options:

A.

Migrate from CSV to binary format, migrate from FTP to SFTP transport, and develop machine learning analysis of metrics.

B.

Migrate from FTP to streaming transport, migrate from CSV to binary format, and develop machine learning analysis of metrics.

C.

Increase fleet cellular connectivity to 80%, migrate from FTP to streaming transport, and develop machine learning analysis of metrics.

D.

Migrate from FTP to SFTP transport, develop machine learning analysis of metrics, and increase dealer local inventory by a fixed factor.

Question 48

For this question, refer to the TerramEarth case study.

TerramEarth has equipped unconnected trucks with servers and sensors to collet telemetry data. Next year they want to use the data to train machine learning models. They want to store this data in the cloud while reducing costs. What should they do?

Options:

A.

Have the vehicle’ computer compress the data in hourly snapshots, and store it in a Google Cloud storage (GCS) Nearline bucket.

B.

Push the telemetry data in Real-time to a streaming dataflow job that compresses the data, and store it in Google BigQuery.

C.

Push the telemetry data in real-time to a streaming dataflow job that compresses the data, and store it in Cloud Bigtable.

D.

Have the vehicle's computer compress the data in hourly snapshots, a Store it in a GCS Coldline bucket.