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Google Professional-Cloud-Architect Exam With Confidence Using Practice Dumps

Exam Code:
Professional-Cloud-Architect
Exam Name:
Google Certified Professional - Cloud Architect (GCP)
Certification:
Vendor:
Questions:
333
Last Updated:
Apr 25, 2026
Exam Status:
Stable
Google Professional-Cloud-Architect

Professional-Cloud-Architect: Google Cloud Certified Exam 2025 Study Guide Pdf and Test Engine

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

Question 1

For this question, refer to the Mountkirk Games case study.

Mountkirk Games' gaming servers are not automatically scaling properly. Last month, they rolled out a new feature, which suddenly became very popular. A record number of users are trying to use the service, but many of them are getting 503 errors and very slow response times. What should they investigate first?

Options:

A.

Verify that the database is online.

B.

Verify that the project quota hasn't been exceeded.

C.

Verify that the new feature code did not introduce any performance bugs.

D.

Verify that the load-testing team is not running their tool against production.

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Question 2

For this question, refer to the JencoMart case study.

The migration of JencoMart’s application to Google Cloud Platform (GCP) is progressing too slowly. The infrastructure is shown in the diagram. You want to maximize throughput. What are three potential bottlenecks? (Choose 3 answers.)

Options:

A.

A single VPN tunnel, which limits throughput

B.

A tier of Google Cloud Storage that is not suited for this task

C.

A copy command that is not suited to operate over long distances

D.

Fewer virtual machines (VMs) in GCP than on-premises machines

E.

A separate storage layer outside the VMs, which is not suited for this task

F.

Complicated internet connectivity between the on-premises infrastructure and GCP

Question 3

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.