Using the Python SDK, you can create a model monitor for data quality, model quality, bias drift, or feature attribution drift. For more information about using SageMaker Model Monitor, see Data and model quality monitoring with Amazon SageMaker Model Monitor. The Model Dashboard populates information from all the monitors you create on all your models in your account. You can track the status of each monitor, which indicates whether your monitor is running as expected or failed due to an internal error. You can also activate or deactivate any monitor in the model details page itself. For instructions about how to view scheduled monitors for a model, see View scheduled monitors. For instructions about how to activate or deactivate model monitors, see Activate or deactivate a model monitor.
A properly-configured and actively-running model monitor might raise alerts, in which case the monitoring executions produce violation reports. For details about how alerts work and how to view alert results, history, and links to job reports for debug, see View and edit alerts.
