MonitoringSchedule
The MonitoringSchedule resource lets you manage AWS SageMaker MonitoringSchedules for monitoring model performance and data quality over time.
Minimal Example
Section titled “Minimal Example”Create a basic monitoring schedule with required properties and one optional property.
import AWS from "alchemy/aws/control";
const basicMonitoringSchedule = await AWS.SageMaker.MonitoringSchedule("basicMonitoringSchedule", { MonitoringScheduleName: "ModelPerformanceMonitoring", MonitoringScheduleConfig: { // Example configuration for monitoring MonitoringJobDefinition: { // Define the monitoring job here BaselineConfig: { BaselineParameters: { // Parameters for baseline }, Statistics: { // Statistics for monitoring } }, // Additional configurations... } }, EndpointName: "my-endpoint" // Optional});
Advanced Configuration
Section titled “Advanced Configuration”Configure a monitoring schedule with detailed settings and tags for resource management.
const advancedMonitoringSchedule = await AWS.SageMaker.MonitoringSchedule("advancedMonitoringSchedule", { MonitoringScheduleName: "AdvancedModelMonitoring", MonitoringScheduleConfig: { MonitoringJobDefinition: { BaselineConfig: { BaselineParameters: { // Define baseline parameters }, Statistics: { // Define statistics } }, // Additional configurations... } }, Tags: [ { Key: "Environment", Value: "Production" }, { Key: "Project", Value: "ModelMonitoring" } ]});
Error Handling
Section titled “Error Handling”Create a monitoring schedule with options to handle failure scenarios.
const errorHandlingMonitoringSchedule = await AWS.SageMaker.MonitoringSchedule("errorHandlingMonitoringSchedule", { MonitoringScheduleName: "ErrorHandlingMonitoring", MonitoringScheduleConfig: { MonitoringJobDefinition: { BaselineConfig: { BaselineParameters: { // Baseline parameters }, Statistics: { // Statistics } }, // Additional configurations... } }, FailureReason: "Invalid configuration provided" // Optional, to log the failure reason});