Google examstopics google Cloud Certified Professional-cloud-architect Reddit Questions by Alyssia q182 vce pdf

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Exam Name:	Google Certified Professional - Cloud Architect (GCP)
Exam Code:	Professional-Cloud-Architect Dumps
Vendor:	Google	Certification:	Google Cloud Certified
Questions:	275 Q&A's	Shared By:	alyssia

Question 44

For this question, refer to the Helicopter Racing League (HRL) case study. A recent finance audit of cloud

infrastructure noted an exceptionally high number of Compute Engine instances are allocated to do video

encoding and transcoding. You suspect that these Virtual Machines are zombie machines that were not deleted

after their workloads completed. You need to quickly get a list of which VM instances are idle. What should you

do?

Options:

Log into each Compute Engine instance and collect disk, CPU, memory, and network usage statistics for

analysis.

Use the gcloud compute instances list to list the virtual machine instances that have the idle: true label set.

Use the gcloud recommender command to list the idle virtual machine instances.

From the Google Console, identify which Compute Engine instances in the managed instance groups are

no longer responding to health check probes.

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Question 45

For this question, refer to the Helicopter Racing League (HRL) case study. HRL is looking for a cost-effective

approach for storing their race data such as telemetry. They want to keep all historical records, train models

using only the previous season's data, and plan for data growth in terms of volume and information collected.

You need to propose a data solution. Considering HRL business requirements and the goals expressed by

CEO S. Hawke, what should you do?

Options:

Use Firestore for its scalable and flexible document-based database. Use collections to aggregate race data

by season and event.

Use Cloud Spanner for its scalability and ability to version schemas with zero downtime. Split race data

using season as a primary key.

Use BigQuery for its scalability and ability to add columns to a schema. Partition race data based on

season.

Use Cloud SQL for its ability to automatically manage storage increases and compatibility with MySQL. Use

separate database instances for each season.

Discussion

Question 46

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:

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

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

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

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

Discussion

Question 47

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:

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.

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.

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.

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.