When encountering intermittent failures in a series of Databricks jobs without a clear pattern, what approach should you take to diagnose and resolve these issues?

Real Exam

Implementing a comprehensive logging system within each job to gather detailed execution logs, followed by a post-failure analysis of these logs.

17.2%

Employing a specialized monitoring tool tailored for Spark applications to obtain in-depth insights into job failures and performance challenges.

10.1%

Leveraging Azure Databricks' built-in job monitoring capabilities to examine execution history and error logs for failure-inducing patterns.

64.6%

Setting up Azure Monitor to alert on job failures and initiate Azure Logic Apps for prompt investigation and alerts.

8.1%

Databricks Certified Data Engineer - Professional