A team runs a GKE cluster and wants to deploy a new version of their application with zero downtime. They need to be able to quickly roll back if the new version fails. They also want to verify the new version with a small percentage of live traffic before full rollout. Which deployment strategy should they use?

Blue-green deployment with a single service

Rolling update with maxSurge=25% and maxUnavailable=25%

Canary deployment with a separate canary service and traffic splitting

A company's release process requires that a senior engineer manually approve deployments to the production environment. They use Cloud Build for CI/CD. They want to enforce this approval gate only for production, not for staging. What should they do?

Use Cloud Build's built-in approval feature and configure it for the production trigger

Add a Cloud Build step that runs a script to check for an approval file in the repository

Use a Cloud Function to send an email to the senior engineer for every build

Create a separate pipeline for production that requires a manual step in Cloud Build

What is the primary benefit of implementing a continuous integration (CI) pipeline for application code?

It ensures that code changes are integrated and validated frequently, reducing integration issues.

It eliminates the need for automated testing.

It replaces the need for version control.

It guarantees zero defects in production.

Google CloudProfessional Cloud DevOps Engineer

Domain 2Objective 1

2.1 Designing Pipelines PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Practice Questions (Page 2)

Part of the Section 2: Building and implementing CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads domain, which accounts for ~25% of the exam of the PROFESSIONAL-CLOUD-DEVOPS-ENGINEER exam.

28questions here

6free pages

10concepts

~25% of the examof the exam

10 Concepts in This Objective

CI/CD for Applications
CI/CD for Infrastructure
Artifact Registry Fundamentals
Artifact Lifecycle and Security
Hybrid and Multi-Cloud Deployment
GKE Deployment Strategies
Pipeline Trigger Types
Trigger Conditions and Filtering
Approval Flows in Deployments
Deployment Process Configuration

Questions 6–10

6foundation · easy
To ensure that only authorized users can push or pull artifacts from a repository, which Artifact Registry configuration should be set?
Select an answer first
7application · medium
A team runs a GKE cluster and wants to deploy a new version of their application with zero downtime. They need to be able to quickly roll back if the new version fails. They also want to verify the new version with a small percentage of live traffic before full rollout. Which deployment strategy should they use?
Select an answer first
8application · medium
A company's release process requires that a senior engineer manually approve deployments to the production environment. They use Cloud Build for CI/CD. They want to enforce this approval gate only for production, not for staging. What should they do?
Select an answer first
9foundation · easy
What is the primary benefit of implementing a continuous integration (CI) pipeline for application code?
Select an answer first
10foundation · easy
Which of the following is a valid repository format supported by Artifact Registry?
Select an answer first

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2.1 Designing Pipelines PROFESSIONAL-CLOUD-DEVOPS-ENGINEER Practice Questions (Page 2)

Questions 6–10

To ensure that only authorized users can push or pull artifacts from a repository, which Artifact Registry configuration should be set?

A company's release process requires that a senior engineer manually approve deployments to the production environment. They use Cloud Build for CI/CD. They want to enforce this approval gate only for production, not for staging. What should they do?

What is the primary benefit of implementing a continuous integration (CI) pipeline for application code?

Which of the following is a valid repository format supported by Artifact Registry?

Keep studying — Section 2: Building and implementing CI/CD pipelines, including continuous testing, for application, infrastructure, and machine learning workloads