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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:
May 30, 2026
Exam Status:
Stable
Google Professional-Cloud-Developer

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

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Google Certified Professional - Cloud Developer Questions and Answers

Question 1

For this question refer to the HipLocal case study.

HipLocal wants to reduce the latency of their services for users in global locations. They have created read replicas of their database in locations where their users reside and configured their service to read traffic using those replicas. How should they further reduce latency for all database interactions with the least amount of effort?

Options:

A.

Migrate the database to Bigtable and use it to serve all global user traffic.

B.

Migrate the database to Cloud Spanner and use it to serve all global user traffic.

C.

Migrate the database to Firestore in Datastore mode and use it to serve all global user traffic.

D.

Migrate the services to Google Kubernetes Engine and use a load balancer service to better scale the application.

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Question 2

You are deploying your application to a Compute Engine virtual machine instance. Your application is

configured to write its log files to disk. You want to view the logs in Stackdriver Logging without changing the

application code.

What should you do?

Options:

A.

Install the Stackdriver Logging Agent and configure it to send the application logs.

B.

Use a Stackdriver Logging Library to log directly from the application to Stackdriver Logging.

C.

Provide the log file folder path in the metadata of the instance to configure it to send the application logs.

D.

Change the application to log to /var/log so that its logs are automatically sent to Stackdriver Logging.

Question 3

You are configuring a continuous integration pipeline using Cloud Build to automate the deployment of new container images to Google Kubernetes Engine (GKE). The pipeline builds the application from its source code, runs unit and integration tests in separate steps, and pushes the container to Container Registry. The application runs on a Python web server.

The Dockerfile is as follows:

FROM python:3.7-alpine -

COPY . /app -

WORKDIR /app -

RUN pip install -r requirements.txt

CMD [ "gunicorn", "-w 4", "main:app" ]

You notice that Cloud Build runs are taking longer than expected to complete. You want to decrease the build time. What should you do? (Choose two.)

Options:

A.

Select a virtual machine (VM) size with higher CPU for Cloud Build runs.

B.

Deploy a Container Registry on a Compute Engine VM in a VPC, and use it to store the final images.

C.

Cache the Docker image for subsequent builds using the -- cache-from argument in your build config file.

D.

Change the base image in the Dockerfile to ubuntu:latest, and install Python 3.7 using a package manager utility.

E.

Store application source code on Cloud Storage, and configure the pipeline to use gsutil to download the source code.