Google Professional Data Engineer Question 27
Select 3Google Cloud PlatformYou are managing a data pipeline in Google Cloud that processes streaming data using Dataflow. The pipeline occasionally fails due to resource constraints or transient errors. You want to monitor and orchestrate the pipeline to ensure it runs reliably and minimizes downtime. Which of the following actions should you take to achieve this?
- A
Set up Cloud Monitoring alerts for Dataflow pipeline metrics such as CPU utilization and system lag.
- B
Use Cloud Composer to schedule periodic restarts of the Dataflow job to prevent errors.
- C
Enable Dataflow's built-in autoscaling to dynamically adjust resources based on the workload.
- D
Implement retries and dead-letter queues within the Dataflow pipeline to handle transient errors.
- E
Use BigQuery to directly monitor the pipeline's performance and optimize job execution.
Show answer and explanation
Correct answers: A, C, D
Explanation
A reliable data pipeline requires both proactive monitoring and robust error handling. Cloud Monitoring alerts help you identify and respond to potential issues in real time, while Dataflow's autoscaling ensures resource availability during variable workloads. Implementing retries and dead-letter queues within the pipeline provides resilience against transient errors. These solutions collectively ensure the pipeline runs reliably. Using tools like Cloud Composer for periodic restarts or relying on BigQuery for monitoring are not best practices in this scenario.
- A. Correct.
Setting up Cloud Monitoring alerts allows you to proactively monitor key metrics and be notified of potential issues, which is essential for reliable pipeline orchestration.
- B. Incorrect.
Using Cloud Composer for periodic restarts is not a recommended practice for handling errors in a streaming pipeline. Instead, proper error handling and monitoring should be implemented.
- C. Correct.
Enabling Dataflow's built-in autoscaling ensures the pipeline has sufficient resources to handle varying workloads, reducing the likelihood of resource-related failures.
- D. Correct.
Retries and dead-letter queues are critical for handling transient errors, ensuring that the pipeline can process problematic data without crashing.
- E. Incorrect.
BigQuery is a data warehouse, and while it can be used to analyze processed data, it is not a tool designed for directly monitoring or orchestrating Dataflow pipelines.