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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:
Cloud Developer
Vendor:
Google
Questions:
265
Last Updated:
Dec 8, 2025
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

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Question 1

You have recently instrumented a new application with OpenTelemetry, and you want to check the latency of your application requests in Trace. You want to ensure that a specific request is always traced. What should you do?

Options:

A.

Wait 10 minutes, then verify that Trace captures those types of requests automatically.

B.

Write a custom script that sends this type of request repeatedly from your dev project.

C.

Use the Trace API to apply custom attributes to the trace.

D.

Add the X-Cloud-Trace-Context header to the request with the appropriate parameters.

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Question 2

HipLocal is configuring their access controls.

Which firewall configuration should they implement?

Options:

A.

Block all traffic on port 443.

B.

Allow all traffic into the network.

C.

Allow traffic on port 443 for a specific tag.

D.

Allow all traffic on port 443 into the network.

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.

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