Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 266 of 279

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

Google Professional Data Engineer Question 266

Select 3Google Cloud Platform

You are managing a data pipeline that processes streaming data using Google Cloud Dataflow. Recently, your team has noticed intermittent failures in the pipeline due to upstream service outages. To minimize the impact of these failures on the availability of your pipeline, what actions should you take?

  1. A

    Implement Dataflow's built-in retry logic for transient errors.

  2. B

    Enable dead-letter queues for failed messages to ensure they can be reprocessed later.

  3. C

    Configure Dataflow jobs to run on preemptible virtual machines to reduce costs.

  4. D

    Set up monitoring and alerting with Cloud Monitoring to track pipeline health and failure rates.

  5. E

    Use a global Spanner database to store intermediate data between processing stages.

Show answer and explanation

Correct answers: A, B, D

Explanation

To mitigate the impact of failures in a streaming data pipeline, you should focus on mechanisms that enhance reliability, ensure recoverability, and provide visibility into the pipeline's health. Using Dataflow's retry logic, enabling dead-letter queues, and setting up monitoring are all effective strategies for maintaining awareness of failures and minimizing their impact. Preemptible VMs and a global Spanner database are unrelated to the specific challenge of mitigating upstream service outages.

  • A. Correct.

    Implementing Dataflow's built-in retry logic ensures that transient errors are automatically retried, reducing the likelihood of pipeline disruptions caused by temporary upstream failures.

  • B. Correct.

    Dead-letter queues provide a mechanism to isolate and store failed messages, allowing for later reprocessing and preventing the pipeline from halting due to unprocessable data.

  • C. Incorrect.

    Using preemptible virtual machines is primarily a cost-saving measure and does not directly address pipeline reliability or failure mitigation.

  • D. Correct.

    Setting up monitoring and alerting allows the team to detect failures quickly and take corrective actions, which is essential for maintaining pipeline availability.

  • E. Incorrect.

    While a global Spanner database can provide strong consistency and availability for storing intermediate data, it is not directly relevant to mitigating the impact of upstream service outages in this scenario.

Timed practice exam

Take a Google Professional Data Engineer practice test under exam conditions

60 questions in 120 minutes, drawn from this bank, with a score report and a per-question review when you finish.

Start timed exam