Free Google Professional-Cloud-Developer Exam Questions

Question 1

A CI/CD pipeline is being developed, which includes a version control system, Cloud Build, and Container Registry. Whenever a new tag is added to the repository, a Cloud Build job is activated. This job performs unit tests on the latest code, creates a new Docker container image, and saves it to the Container Registry. The final phase of the pipeline is to deploy the updated container to the production Google Kubernetes Engine (GKE) cluster.

What options are available to choose a tool and deployment strategy that satisfies these conditions:

• No downtime should be experienced

• Automated testing should be comprehensive

• Testing before release should be possible

• Quick rollbacks should be supported

A : Trigger a Spinnaker pipeline configured as an A/B test of your new code and, if successful, deploy the container to production.

B : Trigger a Cloud Build job that utilizes Kubernetes CLI tools to deploy your new container to your GKE cluster, allowing for a canary test.

C : Trigger a Cloud Build job that utilizes Kubernetes CLI tools to deploy your new container to your GKE cluster, allowing for a shadow test.

D : Trigger a Spinnaker pipeline configured as a canary test of your new code and, if successful, deploy the container to production.

Answer: C

Question 2

Your company is planning to migrate their on-premises Hadoop environment to the cloud. Increasing storage cost and maintenance of data stored in HDFS is a major concern for your company. You also want to make minimal changes to existing data analytics jobs and existing architecture. How should you proceed with the migration?

A : grate your data stored in Hadoop to BigQuery. Change your jobs to source their information from BigQuery instead of the on-premises Hadoop environment.

B : eate Compute Engine instances with HDD instead of SSD to save costs. Then perform a full migration of your existing environment into the new one in Compute Engine instances.

C : eate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop environment to the new Cloud Dataproc cluster. Move your HDFS data into larger HDD disks to save on storage costs.

D : eate a Cloud Dataproc cluster on Google Cloud Platform, and then migrate your Hadoop code objects to the new cluster. Move your data to Cloud Storage and leverage the Cloud Dataproc connector to run jobs on that data.

Answer: D

Question 3

Working alongside the CI/CD team, you, as a developer, are tasked with identifying and resolving a problem that has arisen with a new feature that your team has recently introduced. The CI/CD team employed HashiCorp Packer to generate a fresh Compute Engine image from your development branch, which proved successful in its creation. However, the image is currently unable to start up and requires investigation by the CI/CD team.

What actions are recommended?

A : Install Packer on your device, build the Compute Engine image locally, and then run it in your personal Google Cloud project.

B : Verify the Compute Engine OS logs through the serial port and confirm access to the serial port by checking the Cloud Logging logs.

C : Create a new feature branch and request the build team to reconstruct the image.

D : Power off the virtual machine in use, export the disk, and mount it locally to access the boot logs.

Answer: B

Question 4

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like

to complete each case. However, there may be additional case studies and sections on this exam. You must

manage your time to ensure that you are able to complete all questions included on this exam in the time

provided.

To answer the questions included in a case study, you will need to reference information that is provided in the

case study. Case studies might contain exhibits and other resources that provide more information about the

scenario that is described in the case study. Each question is independent of the other questions in this case

study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to

make changes before you move to the next section of the exam. After you begin a new section, you cannot

return to this section.

To start the case study

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore

the content of the case study before you answer the questions. Clicking these buttons displays information such

as business requirements, existing environment, and problem statements. If the case study has an All

Information tab, note that the information displayed is identical to the information displayed on the subsequent

tabs. When you are ready to answer a question, click the Question button to return to the question.

Company Overview

HipLocal is a community application designed to facilitate communication between people in close proximity. It

is used for event planning and organizing sporting events, and for businesses to connect with their local

communities. HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global

phenomenon. Its unique style of hyper-local community communication and business outreach is in demand

around the world.

Executive Statement

We are the number one local community app; it's time to take our local community services global. Our venture

capital investors want to see rapid growth and the same great experience for new local and virtual communities

that come online, whether their members are 10 or 10000 miles away from each other.

Solution Concept

HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their

global customers. They want to hire and train a new team to support these regions in their time zones. They will

need to ensure that the application scales smoothly and provides clear uptime data.

Existing Technical Environment

HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform.

The HipLocal team understands their application well, but has limited experience in global scale applications.

Their existing technical environment is as follows:

• Existing APIs run on Compute Engine virtual machine instances hosted in GCP.

• State is stored in a single instance MySQL database in GCP.

• Data is exported to an on-premises Teradata/Vertica data warehouse.

• Data analytics is performed in an on-premises Hadoop environment.

• The application has no logging.

• There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.

Business Requirements

HipLocal's investors want to expand their footprint and support the increase in demand they are seeing. Their

requirements are:

• Expand availability of the application to new regions.

• Increase the number of concurrent users that can be supported.

• Ensure a consistent experience for users when they travel to different regions.

• Obtain user activity metrics to better understand how to monetize their product.

• Ensure compliance with regulations in the new regions (for example, GDPR).

• Reduce infrastructure management time and cost.

• Adopt the Google-recommended practices for cloud computing.

Technical Requirements

• The application and backend must provide usage metrics and monitoring.

• APIs require strong authentication and authorization.

• Logging must be increased, and data should be stored in a cloud analytics platform.

• Move to serverless architecture to facilitate elastic scaling.

• Provide authorized access to internal apps in a secure manner.

HipLocal wants to reduce the number of on-call engineers and eliminate manual scaling.

Which two services should they choose? (Choose two.)

A : Google App Engine services.

B : serverless Google Cloud Functions.

C : Knative to build and deploy serverless applications.

D : Google Kubernetes Engine for automated deployments.

E : a large Google Compute Engine cluster for deployments.

Answer: B,C

Question 5

Azgomi is a community application designed to facilitate communication between people in close proximity. It is used for event planning, organizing sporting events, and for businesses to connect with their local communities. Azgomi launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon. Its unique style of hyper-local community communication and business outreach is in demand around the world.

The company's executive statement is to take their local community services global. Azgomi wants to expand their existing service, with updated functionality, in new regions to better serve their global customers. They want to hire and train a new team to support these regions in their time zones. They will need to ensure that the application scales smoothly and provides clear uptime data.

Azgomi's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform. The Azgomi team understands their application well, but has limited experience in global scale applications. Existing APIs run on Compute Engine virtual machine instances hosted in GCP. State is stored in a single instance MySQL database in GCP. Data is exported to an on-premises Teradata/Vertica data warehouse. Data analytics is performed in an on-premises Hadoop environment. The application has no logging. There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.

Azgomi's investors want to expand their footprint and support the increase in demand they are seeing. Their requirements are to expand availability of the application to new regions, increase the number of concurrent users that can be supported, ensure a consistent experience for users when they travel to different regions, obtain user activity metrics to better understand how to monetize their product, ensure compliance with regulations in the new regions (for example, GDPR), reduce infrastructure management time and cost, and adopt the Google-recommended practices for cloud computing.

Technical requirements include providing usage metrics and monitoring, APIs requiring strong authentication and authorization, increased logging, and data stored in a cloud analytics platform. The application and backend must be moved to a serverless architecture to facilitate elastic scaling. The authorized access to internal apps should be provided in a secure manner. Azgomi has connected their Hadoop infrastructure to GCP using Cloud Interconnect in order to query data stored on persistent disks.

What would be the most appropriate IP strategy for them to implement?

A : Provision a single instance for NAT.

B : Create manual subnets.

C : Create multiple peered VPCs.

D : Create an auto mode subnet.

Answer: B