Free Google Professional-Cloud-Developer Exam Questions

Become Google Certified with updated Professional-Cloud-Developer exam questions and correct answers

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Total 623 Questions | Updated On: Nov 17, 2019

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Question 1

What is the recommended approach to prevent cache update problems when exposing dynamic data in a canary release strategy?

A : Use a REST API service indirectly

B : Configure Cache Control and Expires headers

C : Use a version control system

D : Use a different hosting provider

Answer: B

Question 2

After deploying your application in Google Kubernetes Engine, you now require the release of a new version of the application. It is essential to have the capability to promptly revert to the previous version in case complications arise with the latest version.

What would be the most suitable deployment model to use?

A : Perform a rolling deployment, and test your new application after the deployment is complete.

B : Perform A/B testing, and test your application periodically after the new tests are implemented.

C : Perform a blue/green deployment, and test your new application after the deployment is complete.

D : Perform a canary deployment, and test your new application periodically after the new version is deployed.

Answer: C

Question 3

The application on Google Kubernetes Engine (GKE) is currently using a logging library and outputting to standard output. To export the logs to Cloud Logging, including metadata about each request, the simplest method will be used.

What actions are recommended?

A : Change your application's logging library to the Cloud Logging library, and configure your application to export logs to Cloud Logging.

B : Update your application to output logs in JSON format, and include the required metadata in the JSON.

C : Modify your application to output logs in CSV format, and add the necessary metadata to the CSV.

D : Install the Fluent Bit agent on each of your GKE nodes, and have the agent export all logs from /var/log.

Answer: C

Question 4

You are developing a new application that has the following design requirements:

Creation and changes to the application infrastructure are versioned and auditable.

The application and deployment infrastructure uses Google-managed services as much as possible.

The application runs on a serverless compute platform.

How should you design the application’s architecture?

A : 1. Store the application and infrastructure source code in a Git repository.2. Use Cloud Build to deploy the application infrastructure with Terraform.3. Deploy the application to a Cloud Function as a pipeline step.

B : 1. Deploy Jenkins from the Google Cloud Marketplace, and define a continuous integration pipeline inJenkins.2. Configure a pipeline step to pull the application source code from a Git repository.3. Deploy the application source code to App Engine as a pipeline step.

C : 1. Create a continuous integration pipeline on Cloud Build, and configure the pipeline to deploy theapplication infrastructure using Deployment Manager templates.2. Configure a pipeline step to create a container with the latest application source code.3. Deploy the container to a Compute Engine instance as a pipeline step.

D : 1. Deploy the application infrastructure using gcloud commands.2. Use Cloud Build to define a continuous integration pipeline for changes to the application source code.3. Configure a pipeline step to pull the application source code from a Git repository, and create acontainerized application.4. Deploy the new container on Cloud Run as a pipeline step.

Answer: D

Question 5

The analytics system is currently facing a permission error while executing queries against a BigQuery dataset. The SQL query is executed in batch by passing the contents of a SQL file to the BigQuery CLI, which in turn redirects the output to another process. To resolve this issue, you need to identify the root cause of the permission error and take necessary steps to fix it.

What actions are recommended in this situation?

A : Create a view in BigQuery from an SQL query and SELECT* from the view in the command-line interface.

B : Grant the service account BigQuery Data Editor and BigQuery Data Viewer roles.

C : Grant the service account BigQuery Data Viewer and BigQuery Job User roles.

D : Create a new dataset in BigQuery, copy the source table to the new dataset, and query the new dataset and table from the command-line interface.

Answer: C

Page: 1 / 125

Total 623 Questions | Updated On: Nov 17, 2019

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