HSFS supports monitoring, validation, and alerting for features:
- transparently compute statistics over features on writing to a feature group;
- validation of data written to feature groups using Great Expectations
- alerting users when there was a problem writing or update features.
When you create a Feature Group in HSFS, you can configure it to compute statistics over the features inserted into the fFeature Group by setting the
statistics_config dict parameter, see Feature Group Statistics for details. Every time you write to the Feature Group, new statistics will be computed over all of the data in the Feature Group.
You can define expectation suites in Great Expectations and associate them with feature groups. When you write to a feature group, the expectations are executed, then you can define a policy on the feature group for what to do if any expectation fails.
HSFS also supports alerts, that can be triggered when there are problems in your feature pipelines, for example, when a write fails due to an error or a failed expectation. You can send alerts to different alerting endpoints, such as email or Slack, that can be configured in the Hopsworks UI. For example, you can send a slack message if features being written to a feature group are missing some input data.