Data Engineering Associate with Databricks Practice Exam

What is a proactive measure for monitoring ELT job performance?

1. Running jobs on a common scheduler.

2. Setting a threshold for execution time alert.

3. Reviewing logs every week.

4. Creating comprehensive documentation.

The correct answer is: Setting a threshold for execution time alert.

Setting a threshold for execution time alerts is a proactive measure for monitoring ELT job performance because it establishes predefined metrics that allow data engineers to quickly identify and respond to potential issues. By defining a threshold, you can automatically trigger alerts if the execution time exceeds expected limits, enabling timely interventions before problems escalate. This proactive approach helps maintain optimal performance and ensures that jobs run within acceptable parameters, thereby improving overall system reliability. In contrast, running jobs on a common scheduler primarily focuses on job management and scheduling rather than monitoring performance metrics. While useful, it does not provide the same level of proactive monitoring. Reviewing logs every week contributes to performance insights but is a reactive measure. It identifies issues after they have occurred rather than preventing them from happening in the first place. Creating comprehensive documentation is essential for understanding processes and troubleshooting but does not directly monitor job performance or provide real-time alerts for performance issues.