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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 6, 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

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.

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Question 2

You have an application deployed in Google Kubernetes Engine (GKE). You need to update the application to make authorized requests to Google Cloud managed services. You want this to be a one-time setup, and you need to follow security best practices of auto-rotating your security keys and storing them in an encrypted store. You already created a service account with appropriate access to the Google Cloud service. What should you do next?

Options:

A.

Assign the Google Cloud service account to your GKE Pod using Workload Identity.

B.

Export the Google Cloud service account, and share it with the Pod as a Kubernetes Secret.

C.

Export the Google Cloud service account, and embed it in the source code of the application.

D.

Export the Google Cloud service account, and upload it to HashiCorp Vault to generate a dynamic service account for your application.

Question 3

You are developing a marquee stateless web application that will run on Google Cloud. The rate of the incoming user traffic is expected to be unpredictable, with no traffic on some days and large spikes on other days. You need the application to automatically scale up and down, and you need to minimize the cost associated with running the application. What should you do?

Options:

A.

Build the application in Python with Firestore as the database. Deploy the application to Cloud Run.

B.

Build the application in C# with Firestore as the database. Deploy the application to App Engine flexible environment.

C.

Build the application in Python with CloudSQL as the database. Deploy the application to App Engine standard environment.

D.

Build the application in Python with Firestore as the database. Deploy the application to a Compute Engine managed instance group with autoscaling.