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AWS Native v0.102.0 published on Tuesday, Apr 16, 2024 by Pulumi
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aws-native.sagemaker.ModelQualityJobDefinition

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AWS Native is in preview. AWS Classic is fully supported.

AWS Native v0.102.0 published on Tuesday, Apr 16, 2024 by Pulumi
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    Resource Type definition for AWS::SageMaker::ModelQualityJobDefinition

    Create ModelQualityJobDefinition Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new ModelQualityJobDefinition(name: string, args: ModelQualityJobDefinitionArgs, opts?: CustomResourceOptions);
    @overload
def ModelQualityJobDefinition(resource_name: str,
                              args: ModelQualityJobDefinitionArgs,
                              opts: Optional[ResourceOptions] = None)

@overload
def ModelQualityJobDefinition(resource_name: str,
                              opts: Optional[ResourceOptions] = None,
                              job_resources: Optional[ModelQualityJobDefinitionMonitoringResourcesArgs] = None,
                              model_quality_app_specification: Optional[ModelQualityJobDefinitionModelQualityAppSpecificationArgs] = None,
                              model_quality_job_input: Optional[ModelQualityJobDefinitionModelQualityJobInputArgs] = None,
                              model_quality_job_output_config: Optional[ModelQualityJobDefinitionMonitoringOutputConfigArgs] = None,
                              role_arn: Optional[str] = None,
                              endpoint_name: Optional[str] = None,
                              job_definition_name: Optional[str] = None,
                              model_quality_baseline_config: Optional[ModelQualityJobDefinitionModelQualityBaselineConfigArgs] = None,
                              network_config: Optional[ModelQualityJobDefinitionNetworkConfigArgs] = None,
                              stopping_condition: Optional[ModelQualityJobDefinitionStoppingConditionArgs] = None,
                              tags: Optional[Sequence[_root_inputs.CreateOnlyTagArgs]] = None)
    func NewModelQualityJobDefinition(ctx *Context, name string, args ModelQualityJobDefinitionArgs, opts ...ResourceOption) (*ModelQualityJobDefinition, error)
    public ModelQualityJobDefinition(string name, ModelQualityJobDefinitionArgs args, CustomResourceOptions? opts = null)
    public ModelQualityJobDefinition(String name, ModelQualityJobDefinitionArgs args)
public ModelQualityJobDefinition(String name, ModelQualityJobDefinitionArgs args, CustomResourceOptions options)

    type: aws-native:sagemaker:ModelQualityJobDefinition
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args ModelQualityJobDefinitionArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args ModelQualityJobDefinitionArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args ModelQualityJobDefinitionArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelQualityJobDefinitionArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelQualityJobDefinitionArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Example

    The following reference example uses placeholder values for all input properties.

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    const modelQualityJobDefinitionResource = new aws_native.sagemaker.ModelQualityJobDefinition("modelQualityJobDefinitionResource", {
    jobResources: {
        clusterConfig: {
            instanceCount: 0,
            instanceType: "string",
            volumeSizeInGb: 0,
            volumeKmsKeyId: "string",
        },
    },
    modelQualityAppSpecification: {
        imageUri: "string",
        problemType: aws_native.sagemaker.ModelQualityJobDefinitionProblemType.BinaryClassification,
        containerArguments: ["string"],
        containerEntrypoint: ["string"],
        environment: "any",
        postAnalyticsProcessorSourceUri: "string",
        recordPreprocessorSourceUri: "string",
    },
    modelQualityJobInput: {
        groundTruthS3Input: {
            s3Uri: "string",
        },
        batchTransformInput: {
            dataCapturedDestinationS3Uri: "string",
            datasetFormat: {
                csv: {
                    header: false,
                },
                json: {
                    line: false,
                },
                parquet: false,
            },
            localPath: "string",
            endTimeOffset: "string",
            inferenceAttribute: "string",
            probabilityAttribute: "string",
            probabilityThresholdAttribute: 0,
            s3DataDistributionType: aws_native.sagemaker.ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType.FullyReplicated,
            s3InputMode: aws_native.sagemaker.ModelQualityJobDefinitionBatchTransformInputS3InputMode.Pipe,
            startTimeOffset: "string",
        },
        endpointInput: {
            endpointName: "string",
            localPath: "string",
            endTimeOffset: "string",
            inferenceAttribute: "string",
            probabilityAttribute: "string",
            probabilityThresholdAttribute: 0,
            s3DataDistributionType: aws_native.sagemaker.ModelQualityJobDefinitionEndpointInputS3DataDistributionType.FullyReplicated,
            s3InputMode: aws_native.sagemaker.ModelQualityJobDefinitionEndpointInputS3InputMode.Pipe,
            startTimeOffset: "string",
        },
    },
    modelQualityJobOutputConfig: {
        monitoringOutputs: [{
            s3Output: {
                localPath: "string",
                s3Uri: "string",
                s3UploadMode: aws_native.sagemaker.ModelQualityJobDefinitionS3OutputS3UploadMode.Continuous,
            },
        }],
        kmsKeyId: "string",
    },
    roleArn: "string",
    endpointName: "string",
    jobDefinitionName: "string",
    modelQualityBaselineConfig: {
        baseliningJobName: "string",
        constraintsResource: {
            s3Uri: "string",
        },
    },
    networkConfig: {
        enableInterContainerTrafficEncryption: false,
        enableNetworkIsolation: false,
        vpcConfig: {
            securityGroupIds: ["string"],
            subnets: ["string"],
        },
    },
    stoppingCondition: {
        maxRuntimeInSeconds: 0,
    },
    tags: [{
        key: "string",
        value: "string",
    }],
});

    Coming soon!

    ModelQualityJobDefinition Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    The ModelQualityJobDefinition resource accepts the following input properties:

    JobResources Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionMonitoringResources
    ModelQualityAppSpecification Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionModelQualityAppSpecification
    ModelQualityJobInput Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionModelQualityJobInput
    ModelQualityJobOutputConfig Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionMonitoringOutputConfig
    RoleArn string
    The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
    EndpointName string
    JobDefinitionName string
    ModelQualityBaselineConfig Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionModelQualityBaselineConfig
    NetworkConfig Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionNetworkConfig
    StoppingCondition Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionStoppingCondition
    Tags List<Pulumi.AwsNative.Inputs.CreateOnlyTag>
    An array of key-value pairs to apply to this resource.
    jobResources Property Map
    modelQualityAppSpecification Property Map
    modelQualityJobInput Property Map
    modelQualityJobOutputConfig Property Map
    roleArn String
    The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
    endpointName String
    jobDefinitionName String
    modelQualityBaselineConfig Property Map
    networkConfig Property Map
    stoppingCondition Property Map
    tags List<Property Map>
    An array of key-value pairs to apply to this resource.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the ModelQualityJobDefinition resource produces the following output properties:

    CreationTime string
    The time at which the job definition was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    JobDefinitionArn string
    The Amazon Resource Name (ARN) of job definition.
    CreationTime string
    The time at which the job definition was created.
    Id string
    The provider-assigned unique ID for this managed resource.
    JobDefinitionArn string
    The Amazon Resource Name (ARN) of job definition.
    creationTime String
    The time at which the job definition was created.
    id String
    The provider-assigned unique ID for this managed resource.
    jobDefinitionArn String
    The Amazon Resource Name (ARN) of job definition.
    creationTime string
    The time at which the job definition was created.
    id string
    The provider-assigned unique ID for this managed resource.
    jobDefinitionArn string
    The Amazon Resource Name (ARN) of job definition.
    creation_time str
    The time at which the job definition was created.
    id str
    The provider-assigned unique ID for this managed resource.
    job_definition_arn str
    The Amazon Resource Name (ARN) of job definition.
    creationTime String
    The time at which the job definition was created.
    id String
    The provider-assigned unique ID for this managed resource.
    jobDefinitionArn String
    The Amazon Resource Name (ARN) of job definition.

    Supporting Types

    CreateOnlyTag, CreateOnlyTagArgs

    Key string
    The key name of the tag
    Value string
    The value of the tag
    Key string
    The key name of the tag
    Value string
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag
    key string
    The key name of the tag
    value string
    The value of the tag
    key str
    The key name of the tag
    value str
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag

    ModelQualityJobDefinitionBatchTransformInput, ModelQualityJobDefinitionBatchTransformInputArgs

    DataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    DatasetFormat Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionDatasetFormat
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    EndTimeOffset string
    Monitoring end time offset, e.g. PT0H
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    ProbabilityThresholdAttribute double
    S3DataDistributionType Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionBatchTransformInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    StartTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    DataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    DatasetFormat ModelQualityJobDefinitionDatasetFormat
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    EndTimeOffset string
    Monitoring end time offset, e.g. PT0H
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    ProbabilityThresholdAttribute float64
    S3DataDistributionType ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode ModelQualityJobDefinitionBatchTransformInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    StartTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    dataCapturedDestinationS3Uri String
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat ModelQualityJobDefinitionDatasetFormat
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset String
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute Double
    s3DataDistributionType ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelQualityJobDefinitionBatchTransformInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset String
    Monitoring start time offset, e.g. -PT1H
    dataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat ModelQualityJobDefinitionDatasetFormat
    localPath string
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset string
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute string
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute number
    s3DataDistributionType ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelQualityJobDefinitionBatchTransformInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    data_captured_destination_s3_uri str
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    dataset_format ModelQualityJobDefinitionDatasetFormat
    local_path str
    Path to the filesystem where the endpoint data is available to the container.
    end_time_offset str
    Monitoring end time offset, e.g. PT0H
    inference_attribute str
    Index or JSONpath to locate predicted label(s)
    probability_attribute str
    Index or JSONpath to locate probabilities
    probability_threshold_attribute float
    s3_data_distribution_type ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3_input_mode ModelQualityJobDefinitionBatchTransformInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    start_time_offset str
    Monitoring start time offset, e.g. -PT1H
    dataCapturedDestinationS3Uri String
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat Property Map
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset String
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute Number
    s3DataDistributionType "FullyReplicated" | "ShardedByS3Key"
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode "Pipe" | "File"
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset String
    Monitoring start time offset, e.g. -PT1H

    ModelQualityJobDefinitionBatchTransformInputS3DataDistributionType, ModelQualityJobDefinitionBatchTransformInputS3DataDistributionTypeArgs

    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    ModelQualityJobDefinitionBatchTransformInputS3DataDistributionTypeFullyReplicated
    FullyReplicated
    ModelQualityJobDefinitionBatchTransformInputS3DataDistributionTypeShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FULLY_REPLICATED
    FullyReplicated
    SHARDED_BY_S3_KEY
    ShardedByS3Key
    "FullyReplicated"
    FullyReplicated
    "ShardedByS3Key"
    ShardedByS3Key

    ModelQualityJobDefinitionBatchTransformInputS3InputMode, ModelQualityJobDefinitionBatchTransformInputS3InputModeArgs

    Pipe
    Pipe
    File
    File
    ModelQualityJobDefinitionBatchTransformInputS3InputModePipe
    Pipe
    ModelQualityJobDefinitionBatchTransformInputS3InputModeFile
    File
    Pipe
    Pipe
    File
    File
    Pipe
    Pipe
    File
    File
    PIPE
    Pipe
    FILE
    File
    "Pipe"
    Pipe
    "File"
    File

    ModelQualityJobDefinitionClusterConfig, ModelQualityJobDefinitionClusterConfigArgs

    InstanceCount int
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    InstanceType string
    The ML compute instance type for the processing job.
    VolumeSizeInGb int
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    VolumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
    InstanceCount int
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    InstanceType string
    The ML compute instance type for the processing job.
    VolumeSizeInGb int
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    VolumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
    instanceCount Integer
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    instanceType String
    The ML compute instance type for the processing job.
    volumeSizeInGb Integer
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    volumeKmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
    instanceCount number
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    instanceType string
    The ML compute instance type for the processing job.
    volumeSizeInGb number
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    volumeKmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
    instance_count int
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    instance_type str
    The ML compute instance type for the processing job.
    volume_size_in_gb int
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    volume_kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.
    instanceCount Number
    The number of ML compute instances to use in the model monitoring job. For distributed processing jobs, specify a value greater than 1. The default value is 1.
    instanceType String
    The ML compute instance type for the processing job.
    volumeSizeInGb Number
    The size of the ML storage volume, in gigabytes, that you want to provision. You must specify sufficient ML storage for your scenario.
    volumeKmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance(s) that run the model monitoring job.

    ModelQualityJobDefinitionConstraintsResource, ModelQualityJobDefinitionConstraintsResourceArgs

    S3Uri string
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
    S3Uri string
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
    s3Uri String
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
    s3Uri string
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
    s3_uri str
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.
    s3Uri String
    The Amazon S3 URI for baseline constraint file in Amazon S3 that the current monitoring job should validated against.

    ModelQualityJobDefinitionCsv, ModelQualityJobDefinitionCsvArgs

    Header bool
    A boolean flag indicating if given CSV has header
    Header bool
    A boolean flag indicating if given CSV has header
    header Boolean
    A boolean flag indicating if given CSV has header
    header boolean
    A boolean flag indicating if given CSV has header
    header bool
    A boolean flag indicating if given CSV has header
    header Boolean
    A boolean flag indicating if given CSV has header

    ModelQualityJobDefinitionDatasetFormat, ModelQualityJobDefinitionDatasetFormatArgs

    ModelQualityJobDefinitionEndpointInput, ModelQualityJobDefinitionEndpointInputArgs

    EndpointName string
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    EndTimeOffset string
    Monitoring end time offset, e.g. PT0H
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    ProbabilityThresholdAttribute double
    S3DataDistributionType Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionEndpointInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    StartTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    EndpointName string
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    EndTimeOffset string
    Monitoring end time offset, e.g. PT0H
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    ProbabilityThresholdAttribute float64
    S3DataDistributionType ModelQualityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode ModelQualityJobDefinitionEndpointInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    StartTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    endpointName String
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset String
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute Double
    s3DataDistributionType ModelQualityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelQualityJobDefinitionEndpointInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset String
    Monitoring start time offset, e.g. -PT1H
    endpointName string
    localPath string
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset string
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute string
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute number
    s3DataDistributionType ModelQualityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelQualityJobDefinitionEndpointInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset string
    Monitoring start time offset, e.g. -PT1H
    endpoint_name str
    local_path str
    Path to the filesystem where the endpoint data is available to the container.
    end_time_offset str
    Monitoring end time offset, e.g. PT0H
    inference_attribute str
    Index or JSONpath to locate predicted label(s)
    probability_attribute str
    Index or JSONpath to locate probabilities
    probability_threshold_attribute float
    s3_data_distribution_type ModelQualityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3_input_mode ModelQualityJobDefinitionEndpointInputS3InputMode
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    start_time_offset str
    Monitoring start time offset, e.g. -PT1H
    endpointName String
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    endTimeOffset String
    Monitoring end time offset, e.g. PT0H
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    probabilityThresholdAttribute Number
    s3DataDistributionType "FullyReplicated" | "ShardedByS3Key"
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode "Pipe" | "File"
    Whether the Pipe or File is used as the input mode for transfering data for the monitoring job. Pipe mode is recommended for large datasets. File mode is useful for small files that fit in memory. Defaults to File.
    startTimeOffset String
    Monitoring start time offset, e.g. -PT1H

    ModelQualityJobDefinitionEndpointInputS3DataDistributionType, ModelQualityJobDefinitionEndpointInputS3DataDistributionTypeArgs

    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    ModelQualityJobDefinitionEndpointInputS3DataDistributionTypeFullyReplicated
    FullyReplicated
    ModelQualityJobDefinitionEndpointInputS3DataDistributionTypeShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FULLY_REPLICATED
    FullyReplicated
    SHARDED_BY_S3_KEY
    ShardedByS3Key
    "FullyReplicated"
    FullyReplicated
    "ShardedByS3Key"
    ShardedByS3Key

    ModelQualityJobDefinitionEndpointInputS3InputMode, ModelQualityJobDefinitionEndpointInputS3InputModeArgs

    Pipe
    Pipe
    File
    File
    ModelQualityJobDefinitionEndpointInputS3InputModePipe
    Pipe
    ModelQualityJobDefinitionEndpointInputS3InputModeFile
    File
    Pipe
    Pipe
    File
    File
    Pipe
    Pipe
    File
    File
    PIPE
    Pipe
    FILE
    File
    "Pipe"
    Pipe
    "File"
    File

    ModelQualityJobDefinitionJson, ModelQualityJobDefinitionJsonArgs

    Line bool
    A boolean flag indicating if it is JSON line format
    Line bool
    A boolean flag indicating if it is JSON line format
    line Boolean
    A boolean flag indicating if it is JSON line format
    line boolean
    A boolean flag indicating if it is JSON line format
    line bool
    A boolean flag indicating if it is JSON line format
    line Boolean
    A boolean flag indicating if it is JSON line format

    ModelQualityJobDefinitionModelQualityAppSpecification, ModelQualityJobDefinitionModelQualityAppSpecificationArgs

    ImageUri string
    The container image to be run by the monitoring job.
    ProblemType Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionProblemType
    ContainerArguments List<string>
    An array of arguments for the container used to run the monitoring job.
    ContainerEntrypoint List<string>
    Specifies the entrypoint for a container used to run the monitoring job.
    Environment object
    Sets the environment variables in the Docker container
    PostAnalyticsProcessorSourceUri string
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    RecordPreprocessorSourceUri string
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
    ImageUri string
    The container image to be run by the monitoring job.
    ProblemType ModelQualityJobDefinitionProblemType
    ContainerArguments []string
    An array of arguments for the container used to run the monitoring job.
    ContainerEntrypoint []string
    Specifies the entrypoint for a container used to run the monitoring job.
    Environment interface{}
    Sets the environment variables in the Docker container
    PostAnalyticsProcessorSourceUri string
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    RecordPreprocessorSourceUri string
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
    imageUri String
    The container image to be run by the monitoring job.
    problemType ModelQualityJobDefinitionProblemType
    containerArguments List<String>
    An array of arguments for the container used to run the monitoring job.
    containerEntrypoint List<String>
    Specifies the entrypoint for a container used to run the monitoring job.
    environment Object
    Sets the environment variables in the Docker container
    postAnalyticsProcessorSourceUri String
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    recordPreprocessorSourceUri String
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
    imageUri string
    The container image to be run by the monitoring job.
    problemType ModelQualityJobDefinitionProblemType
    containerArguments string[]
    An array of arguments for the container used to run the monitoring job.
    containerEntrypoint string[]
    Specifies the entrypoint for a container used to run the monitoring job.
    environment any
    Sets the environment variables in the Docker container
    postAnalyticsProcessorSourceUri string
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    recordPreprocessorSourceUri string
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
    image_uri str
    The container image to be run by the monitoring job.
    problem_type ModelQualityJobDefinitionProblemType
    container_arguments Sequence[str]
    An array of arguments for the container used to run the monitoring job.
    container_entrypoint Sequence[str]
    Specifies the entrypoint for a container used to run the monitoring job.
    environment Any
    Sets the environment variables in the Docker container
    post_analytics_processor_source_uri str
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    record_preprocessor_source_uri str
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers
    imageUri String
    The container image to be run by the monitoring job.
    problemType "BinaryClassification" | "MulticlassClassification" | "Regression"
    containerArguments List<String>
    An array of arguments for the container used to run the monitoring job.
    containerEntrypoint List<String>
    Specifies the entrypoint for a container used to run the monitoring job.
    environment Any
    Sets the environment variables in the Docker container
    postAnalyticsProcessorSourceUri String
    An Amazon S3 URI to a script that is called after analysis has been performed. Applicable only for the built-in (first party) containers.
    recordPreprocessorSourceUri String
    An Amazon S3 URI to a script that is called per row prior to running analysis. It can base64 decode the payload and convert it into a flatted json so that the built-in container can use the converted data. Applicable only for the built-in (first party) containers

    ModelQualityJobDefinitionModelQualityBaselineConfig, ModelQualityJobDefinitionModelQualityBaselineConfigArgs

    ModelQualityJobDefinitionModelQualityJobInput, ModelQualityJobDefinitionModelQualityJobInputArgs

    ModelQualityJobDefinitionMonitoringGroundTruthS3Input, ModelQualityJobDefinitionMonitoringGroundTruthS3InputArgs

    S3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    S3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3Uri String
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3_uri str
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3Uri String
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.

    ModelQualityJobDefinitionMonitoringOutput, ModelQualityJobDefinitionMonitoringOutputArgs

    ModelQualityJobDefinitionMonitoringOutputConfig, ModelQualityJobDefinitionMonitoringOutputConfigArgs

    MonitoringOutputs List<Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionMonitoringOutput>
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    MonitoringOutputs []ModelQualityJobDefinitionMonitoringOutput
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    monitoringOutputs List<ModelQualityJobDefinitionMonitoringOutput>
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    monitoringOutputs ModelQualityJobDefinitionMonitoringOutput[]
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    kmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    monitoring_outputs Sequence[ModelQualityJobDefinitionMonitoringOutput]
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    monitoringOutputs List<Property Map>
    Monitoring outputs for monitoring jobs. This is where the output of the periodic monitoring jobs is uploaded.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.

    ModelQualityJobDefinitionMonitoringResources, ModelQualityJobDefinitionMonitoringResourcesArgs

    ModelQualityJobDefinitionNetworkConfig, ModelQualityJobDefinitionNetworkConfigArgs

    EnableInterContainerTrafficEncryption bool
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    EnableNetworkIsolation bool
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    VpcConfig Pulumi.AwsNative.SageMaker.Inputs.ModelQualityJobDefinitionVpcConfig
    EnableInterContainerTrafficEncryption bool
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    EnableNetworkIsolation bool
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    VpcConfig ModelQualityJobDefinitionVpcConfig
    enableInterContainerTrafficEncryption Boolean
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    enableNetworkIsolation Boolean
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    vpcConfig ModelQualityJobDefinitionVpcConfig
    enableInterContainerTrafficEncryption boolean
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    enableNetworkIsolation boolean
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    vpcConfig ModelQualityJobDefinitionVpcConfig
    enable_inter_container_traffic_encryption bool
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    enable_network_isolation bool
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    vpc_config ModelQualityJobDefinitionVpcConfig
    enableInterContainerTrafficEncryption Boolean
    Whether to encrypt all communications between distributed processing jobs. Choose True to encrypt communications. Encryption provides greater security for distributed processing jobs, but the processing might take longer.
    enableNetworkIsolation Boolean
    Whether to allow inbound and outbound network calls to and from the containers used for the processing job.
    vpcConfig Property Map

    ModelQualityJobDefinitionProblemType, ModelQualityJobDefinitionProblemTypeArgs

    BinaryClassification
    BinaryClassification
    MulticlassClassification
    MulticlassClassification
    Regression
    Regression
    ModelQualityJobDefinitionProblemTypeBinaryClassification
    BinaryClassification
    ModelQualityJobDefinitionProblemTypeMulticlassClassification
    MulticlassClassification
    ModelQualityJobDefinitionProblemTypeRegression
    Regression
    BinaryClassification
    BinaryClassification
    MulticlassClassification
    MulticlassClassification
    Regression
    Regression
    BinaryClassification
    BinaryClassification
    MulticlassClassification
    MulticlassClassification
    Regression
    Regression
    BINARY_CLASSIFICATION
    BinaryClassification
    MULTICLASS_CLASSIFICATION
    MulticlassClassification
    REGRESSION
    Regression
    "BinaryClassification"
    BinaryClassification
    "MulticlassClassification"
    MulticlassClassification
    "Regression"
    Regression

    ModelQualityJobDefinitionS3Output, ModelQualityJobDefinitionS3OutputArgs

    LocalPath string
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    S3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    S3UploadMode Pulumi.AwsNative.SageMaker.ModelQualityJobDefinitionS3OutputS3UploadMode
    Whether to upload the results of the monitoring job continuously or after the job completes.
    LocalPath string
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    S3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    S3UploadMode ModelQualityJobDefinitionS3OutputS3UploadMode
    Whether to upload the results of the monitoring job continuously or after the job completes.
    localPath String
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    s3Uri String
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3UploadMode ModelQualityJobDefinitionS3OutputS3UploadMode
    Whether to upload the results of the monitoring job continuously or after the job completes.
    localPath string
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    s3Uri string
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3UploadMode ModelQualityJobDefinitionS3OutputS3UploadMode
    Whether to upload the results of the monitoring job continuously or after the job completes.
    local_path str
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    s3_uri str
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3_upload_mode ModelQualityJobDefinitionS3OutputS3UploadMode
    Whether to upload the results of the monitoring job continuously or after the job completes.
    localPath String
    The local path to the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job. LocalPath is an absolute path for the output data.
    s3Uri String
    A URI that identifies the Amazon S3 storage location where Amazon SageMaker saves the results of a monitoring job.
    s3UploadMode "Continuous" | "EndOfJob"
    Whether to upload the results of the monitoring job continuously or after the job completes.

    ModelQualityJobDefinitionS3OutputS3UploadMode, ModelQualityJobDefinitionS3OutputS3UploadModeArgs

    Continuous
    Continuous
    EndOfJob
    EndOfJob
    ModelQualityJobDefinitionS3OutputS3UploadModeContinuous
    Continuous
    ModelQualityJobDefinitionS3OutputS3UploadModeEndOfJob
    EndOfJob
    Continuous
    Continuous
    EndOfJob
    EndOfJob
    Continuous
    Continuous
    EndOfJob
    EndOfJob
    CONTINUOUS
    Continuous
    END_OF_JOB
    EndOfJob
    "Continuous"
    Continuous
    "EndOfJob"
    EndOfJob

    ModelQualityJobDefinitionStoppingCondition, ModelQualityJobDefinitionStoppingConditionArgs

    MaxRuntimeInSeconds int
    The maximum runtime allowed in seconds.
    MaxRuntimeInSeconds int
    The maximum runtime allowed in seconds.
    maxRuntimeInSeconds Integer
    The maximum runtime allowed in seconds.
    maxRuntimeInSeconds number
    The maximum runtime allowed in seconds.
    max_runtime_in_seconds int
    The maximum runtime allowed in seconds.
    maxRuntimeInSeconds Number
    The maximum runtime allowed in seconds.

    ModelQualityJobDefinitionVpcConfig, ModelQualityJobDefinitionVpcConfigArgs

    SecurityGroupIds List<string>
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    Subnets List<string>
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
    SecurityGroupIds []string
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    Subnets []string
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
    securityGroupIds List<String>
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    subnets List<String>
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
    securityGroupIds string[]
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    subnets string[]
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
    security_group_ids Sequence[str]
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    subnets Sequence[str]
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.
    securityGroupIds List<String>
    The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field.
    subnets List<String>
    The ID of the subnets in the VPC to which you want to connect to your monitoring jobs.

    Package Details

    Repository
    AWS Native pulumi/pulumi-aws-native
    License
    Apache-2.0
    aws-native logo

    AWS Native is in preview. AWS Classic is fully supported.

    AWS Native v0.102.0 published on Tuesday, Apr 16, 2024 by Pulumi
    pulumi/pulumi-aws-native