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Cloud DevOps Engineer Professional-Cloud-DevOps-Engineer Dumps PDF

Google Cloud Certified - Professional Cloud DevOps Engineer Exam Questions and Answers

Question 29

The new version of your containerized application has been tested and is ready to be deployed to production on Google Kubernetes Engine (GKE) You could not fully load-test the new version in your pre-production environment and you need to ensure that the application does not have performance problems after deployment Your deployment must be automated What should you do?

Options:

A.

Deploy the application through a continuous delivery pipeline by using canary deployments Use Cloud Monitoring to look for performance issues, and ramp up traffic as supported by the metrics

B.

Deploy the application through a continuous delivery pipeline by using blue/green deployments Migrate traffic to the new version of the application and use Cloud Monitoring to look for performance issues

C.

Deploy the application by using kubectl and use Config Connector to slowly ramp up traffic between versions. Use Cloud Monitoring to look for performance issues

D.

Deploy the application by using kubectl and set the spec. updatestrategy. type field to RollingUpdate Use Cloud Monitoring to look for performance issues, and run the kubectl rollback command if there are any issues.

Question 30

You have an application that runs on Cloud Run. You want to use live production traffic to test a new version of the application while you let the quality assurance team perform manual testing. You want to limit the potential impact of any issues while testing the new version, and you must be able to roll back to a previous version of the application if needed. How should you deploy the new version?

Choose 2 answers

Options:

A.

Deploy the application as a new Cloud Run service.

B.

Deploy a new Cloud Run revision with a tag and use the —no-traffic option.

C.

Deploy a new Cloud Run revision without a tag and use the —no-traffic option.

D.

Deploy the new application version and use the —no-traffic option Route production traffic to the revision's URL.

E.

Deploy the new application version and split traffic to the new version.

Question 31

You deploy a new release of an internal application during a weekend maintenance window when there is minimal user traffic. After the window ends, you learn that one of the new features isn't working as expected in the production environment. After an extended outage, you roll back the new release and deploy a fix. You want to modify your release process to reduce the mean time to recovery so you can avoid extended outages in the future. What should you do?

Choose 2 answers

Options:

A.

Before merging new code, require 2 different peers to review the code changes.

B.

Adopt the blue/green deployment strategy when releasing new code via a CD server.

C.

Integrate a code linting tool to validate coding standards before any code is accepted into the repository.

D.

Require developers to run automated integration tests on their local development environments before release.

E.

Configure a CI server.Add a suite of unit tests to your code and have your CI server run them on commit and verify any changes.

Question 32

You are configuring your CI/CD pipeline natively on Google Cloud. You want builds in a pre-production Google Kubernetes Engine (GKE) environment to be automatically load-tested before being promoted to the production GKE environment. You need to ensure that only builds that have passed this test are deployed to production. You want to follow Google-recommended practices. How should you configure this pipeline with Binary Authorization?

Options:

A.

Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using a key stored in Cloud Key Management Service (Cloud KMS).

B.

Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) authenticated through Workload Identity.

C.

Create an attestation for the builds that pass the load test by using a private key stored in Cloud Key Management Service (Cloud KMS) with a service account JSON key stored as a Kubernetes Secret.

D.

Create an attestation for the builds that pass the load test by requiring the lead quality assurance engineer to sign the attestation by using their personal private key.