Class: Google::Cloud::AIPlatform::V1::ModelDeploymentMonitoringScheduleConfig

Inherits:

Object

Object
Google::Cloud::AIPlatform::V1::ModelDeploymentMonitoringScheduleConfig

show all

Extended by:: Protobuf::MessageExts::ClassMethods

Includes:: Protobuf::MessageExts

Defined in:: proto_docs/google/cloud/aiplatform/v1/model_deployment_monitoring_job.rb

Overview

The config for scheduling monitoring job.

Instance Attribute Summary collapse

#monitor_interval ⇒ ::Google::Protobuf::Duration
Required.
#monitor_window ⇒ ::Google::Protobuf::Duration
The time window of the prediction data being included in each prediction dataset.

Instance Attribute Details

#monitor_interval ⇒ `::Google::Protobuf::Duration`

Returns 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.

# File 'proto_docs/google/cloud/aiplatform/v1/model_deployment_monitoring_job.rb', line 267

class ModelDeploymentMonitoringScheduleConfig
  include ::Google::Protobuf::MessageExts
  extend ::Google::Protobuf::MessageExts::ClassMethods
end

#monitor_window ⇒ `::Google::Protobuf::Duration`

Returns 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.