# Feature Drift
source: https://docs.chalk.ai/docs/featuredrift

## Detect and setup alerting for drift in feature values

Chalk provides a simple way to monitor feature drift by running
the Kolmogorov-Smirnov test for
features values over a given time period.

### Kolmogorov–Smirnov test

The K-S test is a statistical test that can be used to determine if two samples
are drawn from the same distribution. Chalk runs the test on
samples from the online store and data from a given dataset to determine if the
feature values are drawn from the same distribution.

Note that the K-S test can not be used if the feature values in the dataset are all null, if they are
not numeric or if there is only one unique value.

### Charts and Alerts

To setup a chart and alert for the Kolmogorov-Smirnov test, start by creating a
named dataset for the features you want to monitor.

Then under Alerting > Metric Charts, create a new chart and click on Add Formula, choosing KS TEST as the function.
Next select the dataset you created and the feature you want to monitor.

The y-axis of the chart displays the difference between the Kolmogorov-Smirnov test statistic and the critical value at
significance level 0.05. When the value is greater than 0, the feature values are considered to be drawn from different
distributions.

KS Test Chart

To create an Alert, click on Add Alert Trigger and configure the alert to trigger when the KS Test value is greater than 0.