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Creates a definition for a job that monitors data quality and drift

Description

Creates a definition for a job that monitors data quality and drift. For information about model monitor, see Amazon SageMaker AI Model Monitor.

Usage

sagemaker_create_data_quality_job_definition(JobDefinitionName,
  DataQualityBaselineConfig, DataQualityAppSpecification,
  DataQualityJobInput, DataQualityJobOutputConfig, JobResources,
  NetworkConfig, RoleArn, StoppingCondition, Tags)

Arguments

  • JobDefinitionName

    [required] The name for the monitoring job definition.

  • DataQualityBaselineConfig

    Configures the constraints and baselines for the monitoring job.

  • DataQualityAppSpecification

    [required] Specifies the container that runs the monitoring job.

  • DataQualityJobInput

    [required] A list of inputs for the monitoring job. Currently endpoints are supported as monitoring inputs.

  • DataQualityJobOutputConfig

    [required] The output configuration for monitoring jobs.

  • JobResources

    [required] Identifies the resources to deploy for a monitoring job.

  • NetworkConfig

    Specifies networking configuration for the monitoring job.

  • RoleArn

    [required] The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform tasks on your behalf.

  • StoppingCondition

    Specifies a limit to how long a job can run. When the job reaches the time limit, SageMaker ends the job. Use this API to cap costs.

    To stop a training job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

    The training algorithms provided by SageMaker automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with create_model.

    The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.

  • 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(
  JobDefinitionArn = "string"
)

Request syntax

svc$create_data_quality_job_definition(
  JobDefinitionName = "string",
  DataQualityBaselineConfig = list(
    BaseliningJobName = "string",
    ConstraintsResource = list(
      S3Uri = "string"
    ),
    StatisticsResource = list(
      S3Uri = "string"
    )
  ),
  DataQualityAppSpecification = list(
    ImageUri = "string",
    ContainerEntrypoint = list(
      "string"
    ),
    ContainerArguments = list(
      "string"
    ),
    RecordPreprocessorSourceUri = "string",
    PostAnalyticsProcessorSourceUri = "string",
    Environment = list(
      "string"
    )
  ),
  DataQualityJobInput = 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"
    )
  ),
  DataQualityJobOutputConfig = list(
    MonitoringOutputs = list(
      list(
        S3Output = list(
          S3Uri = "string",
          LocalPath = "string",
          S3UploadMode = "Continuous"|"EndOfJob"
        )
      )
    ),
    KmsKeyId = "string"
  ),
  JobResources = 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"|"ml.g6.xlarge"|"ml.g6.2xlarge"|"ml.g6.4xlarge"|"ml.g6.8xlarge"|"ml.g6.12xlarge"|"ml.g6.16xlarge"|"ml.g6.24xlarge"|"ml.g6.48xlarge"|"ml.g6e.xlarge"|"ml.g6e.2xlarge"|"ml.g6e.4xlarge"|"ml.g6e.8xlarge"|"ml.g6e.12xlarge"|"ml.g6e.16xlarge"|"ml.g6e.24xlarge"|"ml.g6e.48xlarge"|"ml.m6i.large"|"ml.m6i.xlarge"|"ml.m6i.2xlarge"|"ml.m6i.4xlarge"|"ml.m6i.8xlarge"|"ml.m6i.12xlarge"|"ml.m6i.16xlarge"|"ml.m6i.24xlarge"|"ml.m6i.32xlarge"|"ml.c6i.xlarge"|"ml.c6i.2xlarge"|"ml.c6i.4xlarge"|"ml.c6i.8xlarge"|"ml.c6i.12xlarge"|"ml.c6i.16xlarge"|"ml.c6i.24xlarge"|"ml.c6i.32xlarge"|"ml.m7i.large"|"ml.m7i.xlarge"|"ml.m7i.2xlarge"|"ml.m7i.4xlarge"|"ml.m7i.8xlarge"|"ml.m7i.12xlarge"|"ml.m7i.16xlarge"|"ml.m7i.24xlarge"|"ml.m7i.48xlarge"|"ml.c7i.large"|"ml.c7i.xlarge"|"ml.c7i.2xlarge"|"ml.c7i.4xlarge"|"ml.c7i.8xlarge"|"ml.c7i.12xlarge"|"ml.c7i.16xlarge"|"ml.c7i.24xlarge"|"ml.c7i.48xlarge"|"ml.r7i.large"|"ml.r7i.xlarge"|"ml.r7i.2xlarge"|"ml.r7i.4xlarge"|"ml.r7i.8xlarge"|"ml.r7i.12xlarge"|"ml.r7i.16xlarge"|"ml.r7i.24xlarge"|"ml.r7i.48xlarge"|"ml.p5.4xlarge"|"ml.g7e.2xlarge"|"ml.g7e.4xlarge"|"ml.g7e.8xlarge"|"ml.g7e.12xlarge"|"ml.g7e.24xlarge"|"ml.g7e.48xlarge"|"ml.g7.2xlarge"|"ml.g7.4xlarge"|"ml.g7.8xlarge"|"ml.g7.12xlarge"|"ml.g7.24xlarge"|"ml.g7.48xlarge"|"ml.r6i.large"|"ml.r6i.xlarge"|"ml.r6i.2xlarge"|"ml.r6i.4xlarge"|"ml.r6i.8xlarge"|"ml.r6i.12xlarge"|"ml.r6i.16xlarge"|"ml.r6i.24xlarge"|"ml.r6i.32xlarge"|"ml.m8i.large"|"ml.m8i.xlarge"|"ml.m8i.2xlarge"|"ml.m8i.4xlarge"|"ml.m8i.8xlarge"|"ml.m8i.12xlarge"|"ml.m8i.16xlarge"|"ml.m8i.24xlarge"|"ml.m8i.32xlarge"|"ml.m8i.48xlarge"|"ml.m8i.96xlarge"|"ml.c8i.xlarge"|"ml.c8i.2xlarge"|"ml.c8i.4xlarge"|"ml.c8i.8xlarge"|"ml.c8i.12xlarge"|"ml.c8i.16xlarge"|"ml.c8i.24xlarge"|"ml.c8i.32xlarge"|"ml.c8i.48xlarge"|"ml.c8i.96xlarge"|"ml.r8i.large"|"ml.r8i.xlarge"|"ml.r8i.2xlarge"|"ml.r8i.4xlarge"|"ml.r8i.8xlarge"|"ml.r8i.12xlarge"|"ml.r8i.16xlarge"|"ml.r8i.24xlarge"|"ml.r8i.32xlarge"|"ml.r8i.48xlarge"|"ml.r8i.96xlarge"|"ml.m7i-flex.large"|"ml.m7i-flex.xlarge"|"ml.m7i-flex.2xlarge"|"ml.m7i-flex.4xlarge"|"ml.m7i-flex.8xlarge"|"ml.m7i-flex.12xlarge"|"ml.m7i-flex.16xlarge"|"ml.c7i-flex.xlarge"|"ml.c7i-flex.2xlarge"|"ml.c7i-flex.4xlarge"|"ml.c7i-flex.8xlarge"|"ml.c7i-flex.12xlarge"|"ml.c7i-flex.16xlarge"|"ml.m8i-flex.large"|"ml.m8i-flex.xlarge"|"ml.m8i-flex.2xlarge"|"ml.m8i-flex.4xlarge"|"ml.m8i-flex.8xlarge"|"ml.m8i-flex.12xlarge"|"ml.m8i-flex.16xlarge"|"ml.c8i-flex.xlarge"|"ml.c8i-flex.2xlarge"|"ml.c8i-flex.4xlarge"|"ml.c8i-flex.8xlarge"|"ml.c8i-flex.12xlarge"|"ml.c8i-flex.16xlarge"|"ml.r8i-flex.large"|"ml.r8i-flex.xlarge"|"ml.r8i-flex.2xlarge"|"ml.r8i-flex.4xlarge"|"ml.r8i-flex.8xlarge"|"ml.r8i-flex.12xlarge"|"ml.r8i-flex.16xlarge",
      VolumeSizeInGB = 123,
      VolumeKmsKeyId = "string"
    )
  ),
  NetworkConfig = list(
    EnableInterContainerTrafficEncryption = TRUE|FALSE,
    EnableNetworkIsolation = TRUE|FALSE,
    VpcConfig = list(
      SecurityGroupIds = list(
        "string"
      ),
      Subnets = list(
        "string"
      )
    )
  ),
  RoleArn = "string",
  StoppingCondition = list(
    MaxRuntimeInSeconds = 123
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)