improved
[In preview] Improvements to Volume Monitor
8 days ago
The volume monitor has been rebuilt to address a broad set of customer feedback from the past year. This will be a phased release to customers over the next few weeks, and it is currently available to just a subset of customers. These improvements apply just to Volume, but we intend to expand them to all monitors over the coming months.
Key improvements:
- Dramatically better anomaly detection. The thresholds are much tighter, particularly for very regular tables.
- Thresholds don't automatically widen after an anomaly. Instead, anomalies are excluded by default from the set of training data. If users don’t want to be alerted to similar anomalies in the future, they can ‘Mark as normal’. This will re-introduce the anomalous data point to the training set and widen the threshold.
- Users can 'select training data' directly in the chart. This gives the user control over which data is used to train the model. This is especially useful for excluding undesirable data when the monitor is initially training.
Read more about these improvements.

Anomalies are now excluded from the set of training data by default, so that thresholds don't widen.
If the user does not want to be alerted to similar anomalies in the future, they can "Mark as normal" to re-introduce the anomaly to the set of training data.

Easily exclude periods of undesirable behavior from the set of training data.