Vertex AI V1 API - Class Google::Cloud::AIPlatform::V1::ModelDeploymentMonitoringScheduleConfig (v0.15.0)

Reference documentation and code samples for the Vertex AI V1 API class Google::Cloud::AIPlatform::V1::ModelDeploymentMonitoringScheduleConfig.

The config for scheduling monitoring job.

Inherits

  • Object

Extended By

  • Google::Protobuf::MessageExts::ClassMethods

Includes

  • Google::Protobuf::MessageExts

Methods

#monitor_interval

def monitor_interval() -> ::Google::Protobuf::Duration
Returns
  • (::Google::Protobuf::Duration) — Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.

#monitor_interval=

def monitor_interval=(value) -> ::Google::Protobuf::Duration
Parameter
  • value (::Google::Protobuf::Duration) — Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.
Returns
  • (::Google::Protobuf::Duration) — Required. The model monitoring job scheduling interval. It will be rounded up to next full hour. This defines how often the monitoring jobs are triggered.

#monitor_window

def monitor_window() -> ::Google::Protobuf::Duration
Returns
  • (::Google::Protobuf::Duration) — The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.

#monitor_window=

def monitor_window=(value) -> ::Google::Protobuf::Duration
Parameter
  • value (::Google::Protobuf::Duration) — The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.
Returns
  • (::Google::Protobuf::Duration) — The time window of the prediction data being included in each prediction dataset. This window specifies how long the data should be collected from historical model results for each run. If not set, ModelDeploymentMonitoringScheduleConfig.monitor_interval will be used. e.g. If currently the cutoff time is 2022-01-08 14:30:00 and the monitor_window is set to be 3600, then data from 2022-01-08 13:30:00 to 2022-01-08 14:30:00 will be retrieved and aggregated to calculate the monitoring statistics.