Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 119 of 279

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

Google Professional Data Engineer Question 119

Select 3Google Cloud Platform

You are working as a data engineer for a company that has adopted Google Cloud for its data pipeline workloads. The team wants to implement a CI/CD pipeline for deploying Dataflow jobs as part of their ETL process. Which of the following steps should you include in your CI/CD pipeline to ensure proper deployment and version control of the Dataflow jobs?

  1. A

    Use Cloud Build to automate the testing and deployment of Dataflow job templates.

  2. B

    Store your Dataflow job code and configuration files in a version control system such as Git.

  3. C

    Deploy Dataflow jobs to production directly from a developer's local machine to save time.

  4. D

    Implement automated unit and integration testing for the Dataflow job code as part of the CI/CD pipeline.

  5. E

    Manually monitor the Dataflow job execution logs before deploying the job to production.

Show answer and explanation

Correct answers: A, B, D

Explanation

To implement a CI/CD pipeline for Dataflow jobs, you need to focus on automation, version control, and testing. Using Cloud Build for automation, storing code in a version control system, and implementing automated testing are all critical components of a robust CI/CD pipeline. Avoid practices like manual monitoring and direct deployment from local machines, as they go against CI/CD principles and can introduce errors or inconsistencies in the deployment process.

  • A. Correct.

    Using Cloud Build is essential for automating the CI/CD pipeline, including building, testing, and deploying Dataflow job templates.

  • B. Correct.

    Version control systems like Git are critical for tracking changes to your Dataflow job code and ensuring collaboration among team members.

  • C. Incorrect.

    Deploying directly from a developer's local machine is not a best practice because it bypasses CI/CD principles like automated testing and controlled environments.

  • D. Correct.

    Automated unit and integration testing ensure the reliability of your Dataflow jobs before deployment, which is a key component of a robust CI/CD pipeline.

  • E. Incorrect.

    Manually monitoring execution logs before deployment is inefficient and does not align with the automation principles of CI/CD.

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