ModelDashboardMonitoringSchedule - Amazon SageMaker
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ModelDashboardMonitoringSchedule

A monitoring schedule for a model displayed in the Amazon SageMaker Model Dashboard.

Contents

BatchTransformInput

Input object for the batch transform job.

Type: BatchTransformInput object

Required: No

CreationTime

A timestamp that indicates when the monitoring schedule was created.

Type: Timestamp

Required: No

EndpointName

The endpoint which is monitored.

Type: String

Length Constraints: Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}

Required: No

FailureReason

If a monitoring job failed, provides the reason.

Type: String

Length Constraints: Maximum length of 1024.

Required: No

LastModifiedTime

A timestamp that indicates when the monitoring schedule was last updated.

Type: Timestamp

Required: No

LastMonitoringExecutionSummary

Summary of information about the last monitoring job to run.

Type: MonitoringExecutionSummary object

Required: No

MonitoringAlertSummaries

A JSON array where each element is a summary for a monitoring alert.

Type: Array of MonitoringAlertSummary objects

Array Members: Minimum number of 1 item. Maximum number of 100 items.

Required: No

MonitoringScheduleArn

The Amazon Resource Name (ARN) of a monitoring schedule.

Type: String

Length Constraints: Maximum length of 256.

Pattern: .*

Required: No

MonitoringScheduleConfig

Configures the monitoring schedule and defines the monitoring job.

Type: MonitoringScheduleConfig object

Required: No

MonitoringScheduleName

The name of a monitoring schedule.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}$

Required: No

MonitoringScheduleStatus

The status of the monitoring schedule.

Type: String

Valid Values: Pending | Failed | Scheduled | Stopped

Required: No

MonitoringType

The monitor type of a model monitor.

Type: String

Valid Values: DataQuality | ModelQuality | ModelBias | ModelExplainability

Required: No

See Also

For more information about using this API in one of the language-specific Amazon SDKs, see the following: