DeepchecksModelClient.add_alert_rule#

DeepchecksModelClient.add_alert_rule(check_name: str, threshold: float, frequency: Union[int, str], alert_severity: str = 'medium', aggregation_window: Optional[int] = None, greater_than: bool = True, kwargs_for_check: Optional[Dict[str, Any]] = None, monitor_name: Optional[str] = None, add_monitor_to_dashboard: bool = False) int#

Create a new alert rule for provided model based on selected check.

The alert will run the selected check on data in defined time intervals and verify if the check return value meets the defined condition.

Parameters
check_name: str

The check to monitor. The alert will monitor the value produced by the check’s reduce function.

threshold: float

The value to compare the check value to.

frequency: int, default: None

Control the frequency the alert will be calculated, provided in seconds.

aggregation_window: int

The aggregation window of each calculation of the alert. If None, the aggregation window will be the same as the frequency. TODO: better explanation

alert_severity: str, default: “medium”

The severity level associated with the alert. Possible values are: critical, high, medium and low.

greater_than: bool, default: True

Whether the alert condition requires the check value to be larger or smaller than provided threshold.

kwargs_for_check: t.Dict, default = None

Additional kwargs to pass on to check.

monitor_name: str, default: None

Name for the created monitor.

add_monitor_to_dashboard: bool, default: False

Whether to add a corresponding monitor to the dashboard screen.

Returns
int

The alert rule ID.