Google Professional Data Engineer exam dumps

Google Professional Data Engineer practice question 28 of 279

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

Google Professional Data Engineer Question 28

Select 3Google Cloud Platform

Your company runs a critical analytics application on Google Cloud using BigQuery, Cloud Storage, and Dataflow. The application processes real-time data and requires high availability with minimal downtime in case of a disaster. To ensure disaster recovery and fault tolerance, what combination of strategies should you implement?

  1. A

    Enable BigQuery dataset replication across multiple regions using BigQuery's multi-region capabilities.

  2. B

    Set up versioning on Cloud Storage buckets to retain previous versions of files in case of accidental deletion.

  3. C

    Configure Dataflow to use the 'drain' option when a pipeline fails to ensure data consistency.

  4. D

    Leverage a managed backup solution to regularly back up BigQuery tables to another region.

  5. E

    Use regional resources only to minimize network latency and reduce costs.

Show answer and explanation

Correct answers: A, B, D

Explanation

To ensure disaster recovery and fault tolerance for critical applications in Google Cloud, it is essential to use multi-region replication for key services like BigQuery, enable versioning to protect Cloud Storage objects, and implement backups for critical datasets. These strategies ensure that your data and application can recover from regional failures or accidental data loss. While other options like 'drain' in Dataflow or using regional resources can be useful in certain scenarios, they do not directly address disaster recovery or fault tolerance.

  • A. Correct.

    BigQuery's multi-region capabilities allow datasets to be replicated across multiple regions, ensuring high availability and disaster recovery.

  • B. Correct.

    Enabling versioning on Cloud Storage buckets helps retain previous versions of objects, providing fault tolerance in case of accidental data loss or corruption.

  • C. Incorrect.

    The 'drain' option in Dataflow is used to gracefully stop a pipeline but does not directly address disaster recovery or fault tolerance.

  • D. Correct.

    Regularly backing up BigQuery tables to another region is a critical strategy for disaster recovery, allowing data to be restored in case of regional outages.

  • E. Incorrect.

    Using regional resources may reduce costs and latency but does not provide fault tolerance or disaster recovery in case of a regional failure.

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