Google Professional Cloud Developer exam dumps

Google Professional Cloud Developer practice question 304 of 481

Professional Cloud Developer. Professional level, Google Cloud. Free question with the correct answer and a full explanation.

Google Professional Cloud Developer Question 304

Single answerGoogle Cloud Platform

You are developing a new feature for a web application running on Google Cloud. The team wants to roll out the feature to a small subset of users to test its performance and gather initial feedback before releasing it to all users. Which strategy should you use to achieve this goal?

  1. A

    Blue/Green Deployment

  2. B

    Canary Deployment

  3. C

    Rolling Deployment

  4. D

    Big Bang Deployment

Show answer and explanation

Correct answer: B

Explanation

The Canary Deployment strategy is ideal for rolling out a new feature to a small subset of users. It allows the team to monitor the feature's performance, collect feedback, and ensure stability before a full rollout. Other strategies, such as Blue/Green and Rolling Deployments, may not focus on targeting a subset of users, while Big Bang Deployment introduces all changes to all users simultaneously, which can be risky.

  • A. Incorrect.

    Blue/Green Deployment involves having two separate environments (blue and green) where one is live and the other is used for testing. It is not designed for testing new features with a small subset of users.

  • B. Correct.

    Canary Deployment is a strategy where a new feature or version is rolled out to a small subset of users first, allowing you to monitor its impact and performance before rolling it out to the entire user base. This is the correct choice for the scenario.

  • C. Incorrect.

    Rolling Deployment gradually replaces instances of the old version with the new version across the entire infrastructure, but it does not specifically target a small subset of users, making it less suitable for this scenario.

  • D. Incorrect.

    Big Bang Deployment involves releasing the feature to all users at once. This approach does not allow for testing with a small subset of users and carries higher risks of widespread issues.

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