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Professional-Cloud-Developer Exam Dumps : Google Certified Professional - Cloud Developer

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Google Certified Professional - Cloud Developer Questions and Answers

Question 1

You are developing an application that reads credit card data from a Pub/Sub subscription. You have written code and completed unit testing. You need to test the Pub/Sub integration before deploying to Google Cloud. What should you do?

Options:

A.

Create a service to publish messages, and deploy the Pub/Sub emulator. Generate random content in the publishing service, and publish to the emulator.

B.

Create a service to publish messages to your application. Collect the messages from Pub/Sub in production, and replay them through the publishing service.

C.

Create a service to publish messages, and deploy the Pub/Sub emulator. Collect the messages from Pub/Sub in production, and publish them to the emulator.

D.

Create a service to publish messages, and deploy the Pub/Sub emulator. Publish a standard set of testing messages from the publishing service to the emulator.

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Question 2

Your team is developing an ecommerce platform for your company. Users will log in to the website and add items to their shopping cart. Users will be automatically logged out after 30 minutes of inactivity. When users log back in, their shopping cart should be saved. How should you store users’ session and shopping cart information while following Google-recommended best practices?

Options:

A.

Store the session information in Pub/Sub, and store the shopping cart information in Cloud SQL.

B.

Store the shopping cart information in a file on Cloud Storage where the filename is the SESSION ID.

C.

Store the session and shopping cart information in a MySQL database running on multiple Compute Engine instances.

D.

Store the session information in Memorystore for Redis or Memorystore for Memcached, and store the shopping cart information in Firestore.

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.