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public sealed class ModelDeploymentMonitoringScheduleConfig : IMessage<ModelDeploymentMonitoringScheduleConfig>, IEquatable<ModelDeploymentMonitoringScheduleConfig>, IDeepCloneable<ModelDeploymentMonitoringScheduleConfig>, IBufferMessage, IMessage
Reference documentation and code samples for the Cloud AI Platform v1 API class ModelDeploymentMonitoringScheduleConfig.
The config for scheduling monitoring job.
Implements
IMessage<ModelDeploymentMonitoringScheduleConfig>, IEquatable<ModelDeploymentMonitoringScheduleConfig>, IDeepCloneable<ModelDeploymentMonitoringScheduleConfig>, IBufferMessage, IMessageNamespace
Google.Cloud.AIPlatform.V1Assembly
Google.Cloud.AIPlatform.V1.dll
Constructors
ModelDeploymentMonitoringScheduleConfig()
public ModelDeploymentMonitoringScheduleConfig()
ModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig)
public ModelDeploymentMonitoringScheduleConfig(ModelDeploymentMonitoringScheduleConfig other)
Parameter | |
---|---|
Name | Description |
other | ModelDeploymentMonitoringScheduleConfig |
Properties
MonitorInterval
public Duration MonitorInterval { get; set; }
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.
Property Value | |
---|---|
Type | Description |
Duration |
MonitorWindow
public Duration MonitorWindow { get; set; }
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][google.cloud.aiplatform.v1.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.
Property Value | |
---|---|
Type | Description |
Duration |