Google Professional Data Engineer Question 25
Select 3Google Cloud PlatformYou are managing a data pipeline in Google Cloud that ingests streaming data from IoT devices, processes it using Dataflow, and stores the output in BigQuery. You notice some delays in the pipeline and need to monitor its health and resolve bottlenecks. Which of the following actions can help you effectively monitor and troubleshoot the pipeline?
- A
Use Cloud Monitoring to set up custom alerts based on Dataflow job metrics.
- B
Enable Dataflow's built-in job visualizations to identify stage-level bottlenecks.
- C
Configure Stackdriver Logging to view detailed logs for Dataflow transformations.
- D
Use BigQuery's query execution logs to monitor upstream pipeline delays.
- E
Enable Dataflow's autoscaling feature to automatically resolve bottlenecks.
Show answer and explanation
Correct answers: A, B, C
Explanation
Monitoring and troubleshooting a Dataflow pipeline require tools that give insight into job metrics, stage performance, and detailed logs. Cloud Monitoring, Dataflow's job visualizations, and Cloud Logging are key tools for effectively identifying and resolving pipeline issues. While autoscaling and BigQuery monitoring are useful in their respective contexts, they do not directly address monitoring and troubleshooting pipeline performance.
- A. Correct.
Using Cloud Monitoring to set up custom alerts based on Dataflow job metrics allows you to proactively monitor key metrics like throughput, latency, and error rates. This helps in identifying and addressing issues quickly.
- B. Correct.
Dataflow's built-in job visualizations provide a graphical representation of pipeline stages, making it easier to identify bottlenecks or underperforming components in the pipeline.
- C. Correct.
Stackdriver Logging (now part of Google Cloud Logging) can provide detailed logs for each transformation in your Dataflow pipeline. These logs are essential for debugging and troubleshooting issues.
- D. Incorrect.
BigQuery's query execution logs are specific to queries run within BigQuery and do not provide insights into upstream pipeline delays. Monitoring the pipeline itself requires Dataflow and Cloud Logging tools.
- E. Incorrect.
Enabling autoscaling in Dataflow can help with resource management but does not directly help in monitoring or troubleshooting bottlenecks. It is a reactive feature rather than a monitoring tool.