Winter Sale - Limited Time 65% Discount Offer - Ends in 0d 00h 00m 00s - Coupon code: top65certs

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

Exam Code:
Professional-Cloud-Developer
Exam Name:
Google Certified Professional - Cloud Developer
Certification:
Vendor:
Questions:
265
Last Updated:
Dec 12, 2025
Exam Status:
Stable
Google Professional-Cloud-Developer

Professional-Cloud-Developer: Cloud Developer Exam 2025 Study Guide Pdf and Test Engine

Are you worried about passing the Google Professional-Cloud-Developer (Google Certified Professional - Cloud Developer) exam? Download the most recent Google Professional-Cloud-Developer braindumps with answers that are 100% real. After downloading the Google Professional-Cloud-Developer exam dumps training , you can receive 99 days of free updates, making this website one of the best options to save additional money. In order to help you prepare for the Google Professional-Cloud-Developer exam questions and verified answers by IT certified experts, CertsTopics has put together a complete collection of dumps questions and answers. To help you prepare and pass the Google Professional-Cloud-Developer exam on your first attempt, we have compiled actual exam questions and their answers. 

Our (Google Certified Professional - Cloud Developer) Study Materials are designed to meet the needs of thousands of candidates globally. A free sample of the CompTIA Professional-Cloud-Developer test is available at CertsTopics. Before purchasing it, you can also see the Google Professional-Cloud-Developer practice exam demo.

Google Certified Professional - Cloud Developer Questions and Answers

Question 1

Your team detected a spike of errors in an application running on Cloud Run in your production project. The application is configured to read messages from Pub/Sub topic A, process the messages, and write the messages to topic B. You want to conduct tests to identify the cause of the errors. You can use a set of mock messages for testing. What should you do?

Options:

A.

Deploy the Pub/Sub and Cloud Run emulators on your local machine. Deploy the application locally, and change the logging level in the application to DEBUG or INFO. Write mock messages to topic A, and then analyze the logs.

B.

Use the gcloud CLI to write mock messages to topic A. Change the logging level in the application to DEBUG or INFO, and then analyze the logs.

C.

Deploy the Pub/Sub emulator on your local machine. Point the production application to your local Pub/Sub topics. Write mock messages to topic A, and then analyze the logs.

D.

Use the Google Cloud console to write mock messages to topic A. Change the logging level in the application to DEBUG or INFO, and then analyze the logs.

Buy Now
Question 2

HipLocal wants to improve the resilience of their MySQL deployment, while also meeting their business and technical requirements.

Which configuration should they choose?

Options:

A.

Use the current single instance MySQL on Compute Engine and several read-only MySQL servers on

Compute Engine.

B.

Use the current single instance MySQL on Compute Engine, and replicate the data to Cloud SQL in an

external master configuration.

C.

Replace the current single instance MySQL instance with Cloud SQL, and configure high availability.

D.

Replace the current single instance MySQL instance with Cloud SQL, and Google provides redundancy

without further configuration.

Question 3

For this question, refer to the HipLocal case study.

How should HipLocal redesign their architecture to ensure that the application scales to support a large increase in users?

Options:

A.

Use Google Kubernetes Engine (GKE) to run the application as a microservice. Run the MySQL database on a dedicated GKE node.

B.

Use multiple Compute Engine instances to run MySQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

C.

Use Memorystore to store session information and CloudSQL to store state information. Use a Google Cloud-managed load balancer to distribute the load between instances. Use managed instance groups for scaling.

D.

Use a Cloud Storage bucket to serve the application as a static website, and use another Cloud Storage bucket to store user state information.