Monitoring the performance of your data pipeline is critical for maintaining data quality, reliability, and operational efficiency. Proactively monitoring performance issues enables to detect bottlenecks and opportunities for optimization, prevent data delays, and avoid unnecessary costs. There are two ways to identify and act on performance issues in Elementary:Documentation Index
Fetch the complete documentation index at: https://docs.elementary-data.com/llms.txt
Use this file to discover all available pages before exploring further.
- Performance pages — explore execution times, trends, and fail rates for models and tests across your pipeline
- Performance & Cost Agent — analyzes patterns across your pipeline, surfaces inefficiencies, suggests query improvements, and flags redundant tests that are slowing things down
Models performance
Navigate to theModel Duration tab.
The table displays the latest execution time, median execution time, and execution time trend for each model. You can sort the table by these metrics and explore the execution times over time for the models with the longest durations
It is also useful to use the navigation bar to filter the results, and see run times per tag/owner/folder.
Tests performance
Navigate to theTest Execution History tab.
On the table you can see the median execution time and fail rate per test.
You can sort the table by this time column, and detect tests that are compute heavy.
It is also useful to use the navigation bar to filter the results, and see run times per tag/owner/folder.

