Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?
A.
Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.
B.
Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
C.
Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.
D.
Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.
To troubleshoot a failed Dataflow job as quickly as possible, you should navigate to theDataflow Jobs page in the Google Cloud console. The console provides access to detailed job logs and worker logs, which can help you identify the cause of the failure. The graphical interface also allows you to visualize pipeline stages, monitor performance metrics, and pinpoint where the error occurred, making it the most efficient way to diagnose and resolve the issue promptly.
Extract from Google Documentation: From "Monitoring Dataflow Jobs" (https://cloud.google.com/dataflow/docs/guides/monitoring-jobs ):"To troubleshoot a failed Dataflow job quickly, go to the Dataflow Jobs page in the Google Cloud Console, where you can view job logs andworker logs to identify errors and their root causes."
[: Google Cloud Documentation - "Dataflow Monitoring" (https://cloud.google.com/dataflow/docs/guides/monitoring-jobs)., , ]
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