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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:
May 11, 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

Refer to the Altostrat Media case study for the following solution regarding the performance analysis of their media processing pipeline.

Altostrat needs to analyze the performance of its media processing pipeline running on Java-based Cloud Run function. You need to select the most effective tool for the task. What should you do?

Options:

A.

Query logs in Cloud Logging.

B.

Analyze the data via Cloud Profiler.

C.

Instrument the code to use Cloud Trace.

D.

Inspect data from Snapshot Debugger.

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Question 2

You are implementing Firestore for Mountkirk Games. Mountkirk Games wants to give a new game

programmatic access to a legacy game's Firestore database. Access should be as restricted as possible. What

should you do?

Options:

A.

Create a service account (SA) in the legacy game's Google Cloud project, add this SA in the new game's IAM page, and then give it the Firebase Admin role in both projects

B.

Create a service account (SA) in the legacy game's Google Cloud project, add a second SA in the new game's IAM page, and then give the Organization Admin role to both SAs

C.

Create a service account (SA) in the legacy game's Google Cloud project, give it the Firebase Admin role, and then migrate the new game to the legacy game's project.

D.

Create a service account (SA) in the lgacy game's Google Cloud project, give the SA the Organization Admin rule and then give it the Firebase Admin role in both projects

Question 3

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.