Labour Day Special - Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: top65certs

Professional-Cloud-Architect Exam Results

Google Cloud Certified - Professional Cloud Architect exam Questions and Answers

Question 49

For this question, refer to the TerramEarth case study.

TerramEarth's 20 million vehicles are scattered around the world. Based on the vehicle's location its telemetry data is stored in a Google Cloud Storage (GCS) regional bucket (US. Europe, or Asia). The CTO has asked you to run a report on the raw telemetry data to determine why vehicles are breaking down after 100 K miles. You want to run this job on all the data. What is the most cost-effective way to run this job?

Options:

A.

Move all the data into 1 zone, then launch a Cloud Dataproc cluster to run the job.

B.

Move all the data into 1 region, then launch a Google Cloud Dataproc cluster to run the job.

C.

Launch a cluster in each region to preprocess and compress the raw data, then move the data into a multi region bucket and use a Dataproc cluster to finish the job.

D.

Launch a cluster in each region to preprocess and compress the raw data, then move the data into a region bucket and use a Cloud Dataproc cluster to finish the jo

Question 50

For this question, refer to the TerramEarth case study.

The TerramEarth development team wants to create an API to meet the company's business requirements. You want the development team to focus their development effort on business value versus creating a custom framework. Which method should they use?

Options:

A.

Use Google App Engine with Google Cloud Endpoints. Focus on an API for dealers and partners.

B.

Use Google App Engine with a JAX-RS Jersey Java-based framework. Focus on an API for the public.

C.

Use Google App Engine with the Swagger (open API Specification) framework. Focus on an API for the public.

D.

Use Google Container Engine with a Django Python container. Focus on an API for the public.

E.

Use Google Container Engine with a Tomcat container with the Swagger (Open API Specification) framework. Focus on an API for dealers and partners.

Question 51

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 52

For this question, refer to the TerramEarth case study.

To speed up data retrieval, more vehicles will be upgraded to cellular connections and be able to transmit data to the ETL process. The current FTP process is error-prone and restarts the data transfer from the start of the file when connections fail, which happens often. You want to improve the reliability of the solution and minimize data transfer time on the cellular connections. What should you do?

Options:

A.

Use one Google Container Engine cluster of FTP servers. Save the data to a Multi-Regional bucket. Run the ETL process using data in the bucket.

B.

Use multiple Google Container Engine clusters running FTP servers located in different regions. Save the data to Multi-Regional buckets in us, eu, and asia. Run the ETL process using the data in the bucket.

C.

Directly transfer the files to different Google Cloud Multi-Regional Storage bucket locations in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process using the data in the bucket.

D.

Directly transfer the files to a different Google Cloud Regional Storage bucket location in us, eu, and asia using Google APIs over HTTP(S). Run the ETL process to retrieve the data from each Regional bucket.