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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 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.

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Question 2

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.

Question 3

You have an application running in a production Google Kubernetes Engine (GKE) cluster. You use Cloud Deploy to automatically deploy your application to your production GKE cluster. As part of your development process: you are planning to make frequent changes to the applications source code and need to select the tools to test the changes before pushing them to your remote source code repository. Your toolset must meet the following requirements:

• Test frequent local changes automatically.

• Local deployment emulates production deployment.

Which tools should you use to test building and running a container on your laptop using minimal resources'?

Options:

A.

Terraform and kubeadm

B.

Docker Compose and dockerd

C.

Minikube and Skaffold

D.

kaniko and Tekton