Google Professional Cloud DevOps Engineer exam dumps

Google Professional Cloud DevOps Engineer practice question 190 of 268

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

Google Professional Cloud DevOps Engineer Question 190

Select 3Google Cloud Platform

Your team is deploying a new feature to a Google Kubernetes Engine (GKE) cluster, and you want to automate the deployment process using Python. The deployment script should apply a Kubernetes manifest file, monitor the deployment status, and roll back if the deployment fails. Which of the following Python libraries and practices should you use to achieve this?

  1. A

    Use the Kubernetes Python client library to interact with the Kubernetes API.

  2. B

    Use the Google Cloud SDK's subprocess calls to kubectl for all Kubernetes operations.

  3. C

    Implement exception handling to capture and manage deployment errors in the script.

  4. D

    Directly modify the GKE cluster configuration YAML files and apply them without validation.

  5. E

    Include a retry mechanism in the script for transient errors during API calls.

Show answer and explanation

Correct answers: A, C, E

Explanation

To automate the deployment process for a GKE cluster using Python, leveraging the Kubernetes Python client library allows direct and reliable interaction with the Kubernetes API. Exception handling ensures the script can identify and respond to errors, such as rolling back a failed deployment. Additionally, a retry mechanism improves resilience against transient issues. Avoid practices like relying solely on subprocess calls to kubectl or making unvalidated changes to YAML files, as these can lead to maintenance challenges or errors.

  • A. Correct.

    Correct: The Kubernetes Python client library is a robust and recommended way to interact with the Kubernetes API programmatically, enabling automation of GKE operations.

  • B. Incorrect.

    Incorrect: While subprocess calls to kubectl can work, they are less reliable and harder to maintain compared to using the Kubernetes Python client library.

  • C. Correct.

    Correct: Exception handling is crucial to ensure the script can gracefully handle deployment errors and provide the opportunity to implement a rollback if necessary.

  • D. Incorrect.

    Incorrect: Directly modifying and applying YAML files without validation is risky and can lead to misconfigurations or unexpected behavior.

  • E. Correct.

    Correct: Implementing a retry mechanism helps handle transient errors, such as temporary API unavailability, improving the reliability of the automation script.

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