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Create Monitoring Schedule

sagemaker_create_monitoring_schedule R Documentation

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint

Description

Creates a schedule that regularly starts Amazon SageMaker Processing Jobs to monitor the data captured for an Amazon SageMaker Endpoint.

Usage

sagemaker_create_monitoring_schedule(MonitoringScheduleName,
  MonitoringScheduleConfig, Tags)

Arguments

MonitoringScheduleName

[required] The name of the monitoring schedule. The name must be unique within an Amazon Web Services Region within an Amazon Web Services account.

MonitoringScheduleConfig

[required] The configuration object that specifies the monitoring schedule and defines the monitoring job.

Tags

(Optional) An array of key-value pairs. For more information, see Using Cost Allocation Tags in the Amazon Web Services Billing and Cost Management User Guide.

Value

A list with the following syntax:

list(
  MonitoringScheduleArn = "string"
)

Request syntax

svc$create_monitoring_schedule(
  MonitoringScheduleName = "string",
  MonitoringScheduleConfig = list(
    ScheduleConfig = list(
      ScheduleExpression = "string",
      DataAnalysisStartTime = "string",
      DataAnalysisEndTime = "string"
    ),
    MonitoringJobDefinition = list(
      BaselineConfig = list(
        BaseliningJobName = "string",
        ConstraintsResource = list(
          S3Uri = "string"
        ),
        StatisticsResource = list(
          S3Uri = "string"
        )
      ),
      MonitoringInputs = list(
        list(
          EndpointInput = list(
            EndpointName = "string",
            LocalPath = "string",
            S3InputMode = "Pipe"|"File",
            S3DataDistributionType = "FullyReplicated"|"ShardedByS3Key",
            FeaturesAttribute = "string",
            InferenceAttribute = "string",
            ProbabilityAttribute = "string",
            ProbabilityThresholdAttribute = 123.0,
            StartTimeOffset = "string",
            EndTimeOffset = "string",
            ExcludeFeaturesAttribute = "string"
          ),
          BatchTransformInput = list(
            DataCapturedDestinationS3Uri = "string",
            DatasetFormat = list(
              Csv = list(
                Header = TRUE|FALSE
              ),
              Json = list(
                Line = TRUE|FALSE
              ),
              Parquet = list()
            ),
            LocalPath = "string",
            S3InputMode = "Pipe"|"File",
            S3DataDistributionType = "FullyReplicated"|"ShardedByS3Key",
            FeaturesAttribute = "string",
            InferenceAttribute = "string",
            ProbabilityAttribute = "string",
            ProbabilityThresholdAttribute = 123.0,
            StartTimeOffset = "string",
            EndTimeOffset = "string",
            ExcludeFeaturesAttribute = "string"
          )
        )
      ),
      MonitoringOutputConfig = list(
        MonitoringOutputs = list(
          list(
            S3Output = list(
              S3Uri = "string",
              LocalPath = "string",
              S3UploadMode = "Continuous"|"EndOfJob"
            )
          )
        ),
        KmsKeyId = "string"
      ),
      MonitoringResources = list(
        ClusterConfig = list(
          InstanceCount = 123,
          InstanceType = "ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.g5.xlarge"|"ml.g5.2xlarge"|"ml.g5.4xlarge"|"ml.g5.8xlarge"|"ml.g5.16xlarge"|"ml.g5.12xlarge"|"ml.g5.24xlarge"|"ml.g5.48xlarge"|"ml.r5d.large"|"ml.r5d.xlarge"|"ml.r5d.2xlarge"|"ml.r5d.4xlarge"|"ml.r5d.8xlarge"|"ml.r5d.12xlarge"|"ml.r5d.16xlarge"|"ml.r5d.24xlarge",
          VolumeSizeInGB = 123,
          VolumeKmsKeyId = "string"
        )
      ),
      MonitoringAppSpecification = list(
        ImageUri = "string",
        ContainerEntrypoint = list(
          "string"
        ),
        ContainerArguments = list(
          "string"
        ),
        RecordPreprocessorSourceUri = "string",
        PostAnalyticsProcessorSourceUri = "string"
      ),
      StoppingCondition = list(
        MaxRuntimeInSeconds = 123
      ),
      Environment = list(
        "string"
      ),
      NetworkConfig = list(
        EnableInterContainerTrafficEncryption = TRUE|FALSE,
        EnableNetworkIsolation = TRUE|FALSE,
        VpcConfig = list(
          SecurityGroupIds = list(
            "string"
          ),
          Subnets = list(
            "string"
          )
        )
      ),
      RoleArn = "string"
    ),
    MonitoringJobDefinitionName = "string",
    MonitoringType = "DataQuality"|"ModelQuality"|"ModelBias"|"ModelExplainability"
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)