How do you monitor the performance of dbt jobs?

Monitoring the performance of dbt jobs can effectively be achieved through dbt Cloud's job logs or custom logging solutions. These logs provide insights into how dbt runs the models, the time taken for the jobs to complete, any errors encountered, and other relevant metrics that help in understanding performance and identifying potential issues. This detail allows users to optimize their dbt runs and troubleshoot problems as they arise.

While real-time dashboards can provide useful visualizations of data and insights, they may not specifically track the performance of the dbt jobs in the same way that job logs can. Similarly, using CPU performance metrics focuses more on the underlying hardware's performance rather than the performance of the dbt jobs themselves. Finally, analyzing data warehouse health checks pertains to the overall functioning and health of the data warehouse rather than the specific execution and performance of dbt jobs. Thus, leveraging job logs or a custom logging solution remains the most direct and insightful method for monitoring dbt job performance.