Answer: They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.

## Explanation To identify why a notebook is running slowly in a Databricks Job, the correct approach is: **C. They can navigate to the Runs tab in the Jobs UI and click on the active run to review the processing notebook.** Here's why: 1. **Runs Tab vs Tasks Tab**: In Databricks Jobs UI, the **Runs tab** shows all job runs (both active and completed), while the **Tasks tab** shows the job definition and configuration. 2. **Accessing Active Run Details**: To investigate a currently running notebook, you need to: - Go to the **Runs tab** (not Tasks tab) - Click on the **active run** (not just navigate to the tab) - From there, you can access the notebook execution details, logs, and metrics 3. **Why other options are incorrect**: - **A**: Simply navigating to the Runs tab doesn't show the processing notebook - you need to click on the specific run. - **B**: The Tasks tab shows job configuration, not active run details for troubleshooting performance. - **D**: The Tasks tab doesn't provide immediate access to running notebook details. 4. **Troubleshooting Performance**: Once you access the active run from the Runs tab, you can: - View notebook cell execution times - Check Spark UI for job/stage details - Review logs for errors or warnings - Monitor resource utilization - Identify bottlenecks in the execution This approach allows the tech lead to directly investigate the performance issues of the specific notebook task that's currently running slowly.

Author: Keng Suppaseth