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AWS Cloud Control v1.9.0 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-aws-native

aws-native.sagemaker.ModelExplainabilityJobDefinition

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We recommend new projects start with resources from the AWS provider.

AWS Cloud Control v1.9.0 published on Monday, Nov 18, 2024 by Pulumi
pulumi/pulumi-aws-native

    Resource Type definition for AWS::SageMaker::ModelExplainabilityJobDefinition

    Create ModelExplainabilityJobDefinition Resource

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

    Constructor syntax

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

@overload
def ModelExplainabilityJobDefinition(resource_name: str,
                                     opts: Optional[ResourceOptions] = None,
                                     job_resources: Optional[ModelExplainabilityJobDefinitionMonitoringResourcesArgs] = None,
                                     model_explainability_app_specification: Optional[ModelExplainabilityJobDefinitionModelExplainabilityAppSpecificationArgs] = None,
                                     model_explainability_job_input: Optional[ModelExplainabilityJobDefinitionModelExplainabilityJobInputArgs] = None,
                                     model_explainability_job_output_config: Optional[ModelExplainabilityJobDefinitionMonitoringOutputConfigArgs] = None,
                                     role_arn: Optional[str] = None,
                                     endpoint_name: Optional[str] = None,
                                     job_definition_name: Optional[str] = None,
                                     model_explainability_baseline_config: Optional[ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfigArgs] = None,
                                     network_config: Optional[ModelExplainabilityJobDefinitionNetworkConfigArgs] = None,
                                     stopping_condition: Optional[ModelExplainabilityJobDefinitionStoppingConditionArgs] = None,
                                     tags: Optional[Sequence[_root_inputs.CreateOnlyTagArgs]] = None)
    func NewModelExplainabilityJobDefinition(ctx *Context, name string, args ModelExplainabilityJobDefinitionArgs, opts ...ResourceOption) (*ModelExplainabilityJobDefinition, error)
    public ModelExplainabilityJobDefinition(string name, ModelExplainabilityJobDefinitionArgs args, CustomResourceOptions? opts = null)
    public ModelExplainabilityJobDefinition(String name, ModelExplainabilityJobDefinitionArgs args)
public ModelExplainabilityJobDefinition(String name, ModelExplainabilityJobDefinitionArgs args, CustomResourceOptions options)

    type: aws-native:sagemaker:ModelExplainabilityJobDefinition
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 ModelExplainabilityJobDefinitionArgs
    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 ModelExplainabilityJobDefinitionArgs
    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 ModelExplainabilityJobDefinitionArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args ModelExplainabilityJobDefinitionArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args ModelExplainabilityJobDefinitionArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    ModelExplainabilityJobDefinition Resource Properties

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

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The ModelExplainabilityJobDefinition resource accepts the following input properties:

    JobResources Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionMonitoringResources
    Identifies the resources to deploy for a monitoring job.
    ModelExplainabilityAppSpecification Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionModelExplainabilityAppSpecification
    Configures the model explainability job to run a specified Docker container image.
    ModelExplainabilityJobInput Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionModelExplainabilityJobInput
    Inputs for the model explainability job.
    ModelExplainabilityJobOutputConfig Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionMonitoringOutputConfig
    The output configuration for monitoring jobs.
    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
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    ModelExplainabilityBaselineConfig Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfig
    The baseline configuration for a model explainability job.
    NetworkConfig Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionNetworkConfig
    Networking options for a model explainability job.
    StoppingCondition Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionStoppingCondition
    A time limit for how long the monitoring job is allowed to run before stopping.
    Tags List<Pulumi.AwsNative.Inputs.CreateOnlyTag>
    An array of key-value pairs to apply to this resource.
    JobResources ModelExplainabilityJobDefinitionMonitoringResourcesArgs
    Identifies the resources to deploy for a monitoring job.
    ModelExplainabilityAppSpecification ModelExplainabilityJobDefinitionModelExplainabilityAppSpecificationArgs
    Configures the model explainability job to run a specified Docker container image.
    ModelExplainabilityJobInput ModelExplainabilityJobDefinitionModelExplainabilityJobInputArgs
    Inputs for the model explainability job.
    ModelExplainabilityJobOutputConfig ModelExplainabilityJobDefinitionMonitoringOutputConfigArgs
    The output configuration for monitoring jobs.
    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
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    ModelExplainabilityBaselineConfig ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfigArgs
    The baseline configuration for a model explainability job.
    NetworkConfig ModelExplainabilityJobDefinitionNetworkConfigArgs
    Networking options for a model explainability job.
    StoppingCondition ModelExplainabilityJobDefinitionStoppingConditionArgs
    A time limit for how long the monitoring job is allowed to run before stopping.
    Tags CreateOnlyTagArgs
    An array of key-value pairs to apply to this resource.
    jobResources ModelExplainabilityJobDefinitionMonitoringResources
    Identifies the resources to deploy for a monitoring job.
    modelExplainabilityAppSpecification ModelExplainabilityJobDefinitionModelExplainabilityAppSpecification
    Configures the model explainability job to run a specified Docker container image.
    modelExplainabilityJobInput ModelExplainabilityJobDefinitionModelExplainabilityJobInput
    Inputs for the model explainability job.
    modelExplainabilityJobOutputConfig ModelExplainabilityJobDefinitionMonitoringOutputConfig
    The output configuration for monitoring jobs.
    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
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    modelExplainabilityBaselineConfig ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfig
    The baseline configuration for a model explainability job.
    networkConfig ModelExplainabilityJobDefinitionNetworkConfig
    Networking options for a model explainability job.
    stoppingCondition ModelExplainabilityJobDefinitionStoppingCondition
    A time limit for how long the monitoring job is allowed to run before stopping.
    tags List<CreateOnlyTag>
    An array of key-value pairs to apply to this resource.
    jobResources ModelExplainabilityJobDefinitionMonitoringResources
    Identifies the resources to deploy for a monitoring job.
    modelExplainabilityAppSpecification ModelExplainabilityJobDefinitionModelExplainabilityAppSpecification
    Configures the model explainability job to run a specified Docker container image.
    modelExplainabilityJobInput ModelExplainabilityJobDefinitionModelExplainabilityJobInput
    Inputs for the model explainability job.
    modelExplainabilityJobOutputConfig ModelExplainabilityJobDefinitionMonitoringOutputConfig
    The output configuration for monitoring jobs.
    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
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    modelExplainabilityBaselineConfig ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfig
    The baseline configuration for a model explainability job.
    networkConfig ModelExplainabilityJobDefinitionNetworkConfig
    Networking options for a model explainability job.
    stoppingCondition ModelExplainabilityJobDefinitionStoppingCondition
    A time limit for how long the monitoring job is allowed to run before stopping.
    tags CreateOnlyTag[]
    An array of key-value pairs to apply to this resource.
    job_resources ModelExplainabilityJobDefinitionMonitoringResourcesArgs
    Identifies the resources to deploy for a monitoring job.
    model_explainability_app_specification ModelExplainabilityJobDefinitionModelExplainabilityAppSpecificationArgs
    Configures the model explainability job to run a specified Docker container image.
    model_explainability_job_input ModelExplainabilityJobDefinitionModelExplainabilityJobInputArgs
    Inputs for the model explainability job.
    model_explainability_job_output_config ModelExplainabilityJobDefinitionMonitoringOutputConfigArgs
    The output configuration for monitoring jobs.
    role_arn str
    The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume to perform tasks on your behalf.
    endpoint_name str
    job_definition_name str
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    model_explainability_baseline_config ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfigArgs
    The baseline configuration for a model explainability job.
    network_config ModelExplainabilityJobDefinitionNetworkConfigArgs
    Networking options for a model explainability job.
    stopping_condition ModelExplainabilityJobDefinitionStoppingConditionArgs
    A time limit for how long the monitoring job is allowed to run before stopping.
    tags Sequence[CreateOnlyTagArgs]
    An array of key-value pairs to apply to this resource.
    jobResources Property Map
    Identifies the resources to deploy for a monitoring job.
    modelExplainabilityAppSpecification Property Map
    Configures the model explainability job to run a specified Docker container image.
    modelExplainabilityJobInput Property Map
    Inputs for the model explainability job.
    modelExplainabilityJobOutputConfig Property Map
    The output configuration for monitoring jobs.
    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
    The name of the model explainability job definition. The name must be unique within an AWS Region in the AWS account.
    modelExplainabilityBaselineConfig Property Map
    The baseline configuration for a model explainability job.
    networkConfig Property Map
    Networking options for a model explainability job.
    stoppingCondition Property Map
    A time limit for how long the monitoring job is allowed to run before stopping.
    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 ModelExplainabilityJobDefinition 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

    ModelExplainabilityJobDefinitionBatchTransformInput, ModelExplainabilityJobDefinitionBatchTransformInputArgs

    DataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    DatasetFormat Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionDatasetFormat
    The dataset format for your batch transform job.
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    FeaturesAttribute string
    JSONpath to locate features in JSONlines dataset
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    S3DataDistributionType Pulumi.AwsNative.SageMaker.ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode Pulumi.AwsNative.SageMaker.ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode
    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.
    DataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    DatasetFormat ModelExplainabilityJobDefinitionDatasetFormat
    The dataset format for your batch transform job.
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    FeaturesAttribute string
    JSONpath to locate features in JSONlines dataset
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    S3DataDistributionType ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode
    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.
    dataCapturedDestinationS3Uri String
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat ModelExplainabilityJobDefinitionDatasetFormat
    The dataset format for your batch transform job.
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute String
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    s3DataDistributionType ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode
    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.
    dataCapturedDestinationS3Uri string
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat ModelExplainabilityJobDefinitionDatasetFormat
    The dataset format for your batch transform job.
    localPath string
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute string
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute string
    Index or JSONpath to locate probabilities
    s3DataDistributionType ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode
    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.
    data_captured_destination_s3_uri str
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    dataset_format ModelExplainabilityJobDefinitionDatasetFormat
    The dataset format for your batch transform job.
    local_path str
    Path to the filesystem where the endpoint data is available to the container.
    features_attribute str
    JSONpath to locate features in JSONlines dataset
    inference_attribute str
    Index or JSONpath to locate predicted label(s)
    probability_attribute str
    Index or JSONpath to locate probabilities
    s3_data_distribution_type ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3_input_mode ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode
    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.
    dataCapturedDestinationS3Uri String
    A URI that identifies the Amazon S3 storage location where Batch Transform Job captures data.
    datasetFormat Property Map
    The dataset format for your batch transform job.
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute String
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    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.

    ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionType, ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionTypeArgs

    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionTypeFullyReplicated
    FullyReplicated
    ModelExplainabilityJobDefinitionBatchTransformInputS3DataDistributionTypeShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FULLY_REPLICATED
    FullyReplicated
    SHARDED_BY_S3_KEY
    ShardedByS3Key
    "FullyReplicated"
    FullyReplicated
    "ShardedByS3Key"
    ShardedByS3Key

    ModelExplainabilityJobDefinitionBatchTransformInputS3InputMode, ModelExplainabilityJobDefinitionBatchTransformInputS3InputModeArgs

    Pipe
    Pipe
    File
    File
    ModelExplainabilityJobDefinitionBatchTransformInputS3InputModePipe
    Pipe
    ModelExplainabilityJobDefinitionBatchTransformInputS3InputModeFile
    File
    Pipe
    Pipe
    File
    File
    Pipe
    Pipe
    File
    File
    PIPE
    Pipe
    FILE
    File
    "Pipe"
    Pipe
    "File"
    File

    ModelExplainabilityJobDefinitionClusterConfig, ModelExplainabilityJobDefinitionClusterConfigArgs

    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.

    ModelExplainabilityJobDefinitionConstraintsResource, ModelExplainabilityJobDefinitionConstraintsResourceArgs

    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.

    ModelExplainabilityJobDefinitionCsv, ModelExplainabilityJobDefinitionCsvArgs

    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

    ModelExplainabilityJobDefinitionDatasetFormat, ModelExplainabilityJobDefinitionDatasetFormatArgs

    ModelExplainabilityJobDefinitionEndpointInput, ModelExplainabilityJobDefinitionEndpointInputArgs

    EndpointName string
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    FeaturesAttribute string
    JSONpath to locate features in JSONlines dataset
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    S3DataDistributionType Pulumi.AwsNative.SageMaker.ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode Pulumi.AwsNative.SageMaker.ModelExplainabilityJobDefinitionEndpointInputS3InputMode
    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.
    EndpointName string
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    LocalPath string
    Path to the filesystem where the endpoint data is available to the container.
    FeaturesAttribute string
    JSONpath to locate features in JSONlines dataset
    InferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    ProbabilityAttribute string
    Index or JSONpath to locate probabilities
    S3DataDistributionType ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    S3InputMode ModelExplainabilityJobDefinitionEndpointInputS3InputMode
    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.
    endpointName String
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute String
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    s3DataDistributionType ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelExplainabilityJobDefinitionEndpointInputS3InputMode
    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.
    endpointName string
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    localPath string
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute string
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute string
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute string
    Index or JSONpath to locate probabilities
    s3DataDistributionType ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3InputMode ModelExplainabilityJobDefinitionEndpointInputS3InputMode
    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.
    endpoint_name str
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    local_path str
    Path to the filesystem where the endpoint data is available to the container.
    features_attribute str
    JSONpath to locate features in JSONlines dataset
    inference_attribute str
    Index or JSONpath to locate predicted label(s)
    probability_attribute str
    Index or JSONpath to locate probabilities
    s3_data_distribution_type ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType
    Whether input data distributed in Amazon S3 is fully replicated or sharded by an S3 key. Defauts to FullyReplicated
    s3_input_mode ModelExplainabilityJobDefinitionEndpointInputS3InputMode
    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.
    endpointName String
    An endpoint in customer's account which has enabled DataCaptureConfig enabled.
    localPath String
    Path to the filesystem where the endpoint data is available to the container.
    featuresAttribute String
    JSONpath to locate features in JSONlines dataset
    inferenceAttribute String
    Index or JSONpath to locate predicted label(s)
    probabilityAttribute String
    Index or JSONpath to locate probabilities
    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.

    ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionType, ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionTypeArgs

    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionTypeFullyReplicated
    FullyReplicated
    ModelExplainabilityJobDefinitionEndpointInputS3DataDistributionTypeShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FullyReplicated
    FullyReplicated
    ShardedByS3Key
    ShardedByS3Key
    FULLY_REPLICATED
    FullyReplicated
    SHARDED_BY_S3_KEY
    ShardedByS3Key
    "FullyReplicated"
    FullyReplicated
    "ShardedByS3Key"
    ShardedByS3Key

    ModelExplainabilityJobDefinitionEndpointInputS3InputMode, ModelExplainabilityJobDefinitionEndpointInputS3InputModeArgs

    Pipe
    Pipe
    File
    File
    ModelExplainabilityJobDefinitionEndpointInputS3InputModePipe
    Pipe
    ModelExplainabilityJobDefinitionEndpointInputS3InputModeFile
    File
    Pipe
    Pipe
    File
    File
    Pipe
    Pipe
    File
    File
    PIPE
    Pipe
    FILE
    File
    "Pipe"
    Pipe
    "File"
    File

    ModelExplainabilityJobDefinitionJson, ModelExplainabilityJobDefinitionJsonArgs

    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

    ModelExplainabilityJobDefinitionModelExplainabilityAppSpecification, ModelExplainabilityJobDefinitionModelExplainabilityAppSpecificationArgs

    ConfigUri string
    The S3 URI to an analysis configuration file
    ImageUri string
    The container image to be run by the monitoring job.
    Environment object
    Sets the environment variables in the Docker container
    ConfigUri string
    The S3 URI to an analysis configuration file
    ImageUri string
    The container image to be run by the monitoring job.
    Environment interface{}
    Sets the environment variables in the Docker container
    configUri String
    The S3 URI to an analysis configuration file
    imageUri String
    The container image to be run by the monitoring job.
    environment Object
    Sets the environment variables in the Docker container
    configUri string
    The S3 URI to an analysis configuration file
    imageUri string
    The container image to be run by the monitoring job.
    environment any
    Sets the environment variables in the Docker container
    config_uri str
    The S3 URI to an analysis configuration file
    image_uri str
    The container image to be run by the monitoring job.
    environment Any
    Sets the environment variables in the Docker container
    configUri String
    The S3 URI to an analysis configuration file
    imageUri String
    The container image to be run by the monitoring job.
    environment Any
    Sets the environment variables in the Docker container

    ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfig, ModelExplainabilityJobDefinitionModelExplainabilityBaselineConfigArgs

    BaseliningJobName string
    The name of the baseline model explainability job.
    ConstraintsResource Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionConstraintsResource
    The constraints resource for a model explainability job.
    BaseliningJobName string
    The name of the baseline model explainability job.
    ConstraintsResource ModelExplainabilityJobDefinitionConstraintsResource
    The constraints resource for a model explainability job.
    baseliningJobName String
    The name of the baseline model explainability job.
    constraintsResource ModelExplainabilityJobDefinitionConstraintsResource
    The constraints resource for a model explainability job.
    baseliningJobName string
    The name of the baseline model explainability job.
    constraintsResource ModelExplainabilityJobDefinitionConstraintsResource
    The constraints resource for a model explainability job.
    baselining_job_name str
    The name of the baseline model explainability job.
    constraints_resource ModelExplainabilityJobDefinitionConstraintsResource
    The constraints resource for a model explainability job.
    baseliningJobName String
    The name of the baseline model explainability job.
    constraintsResource Property Map
    The constraints resource for a model explainability job.

    ModelExplainabilityJobDefinitionModelExplainabilityJobInput, ModelExplainabilityJobDefinitionModelExplainabilityJobInputArgs

    batchTransformInput Property Map
    Input object for the batch transform job.
    endpointInput Property Map
    Input object for the endpoint

    ModelExplainabilityJobDefinitionMonitoringOutput, ModelExplainabilityJobDefinitionMonitoringOutputArgs

    S3Output Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionS3Output
    The Amazon S3 storage location where the results of a monitoring job are saved.
    S3Output ModelExplainabilityJobDefinitionS3Output
    The Amazon S3 storage location where the results of a monitoring job are saved.
    s3Output ModelExplainabilityJobDefinitionS3Output
    The Amazon S3 storage location where the results of a monitoring job are saved.
    s3Output ModelExplainabilityJobDefinitionS3Output
    The Amazon S3 storage location where the results of a monitoring job are saved.
    s3_output ModelExplainabilityJobDefinitionS3Output
    The Amazon S3 storage location where the results of a monitoring job are saved.
    s3Output Property Map
    The Amazon S3 storage location where the results of a monitoring job are saved.

    ModelExplainabilityJobDefinitionMonitoringOutputConfig, ModelExplainabilityJobDefinitionMonitoringOutputConfigArgs

    MonitoringOutputs List<Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionMonitoringOutput>
    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 []ModelExplainabilityJobDefinitionMonitoringOutput
    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<ModelExplainabilityJobDefinitionMonitoringOutput>
    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 ModelExplainabilityJobDefinitionMonitoringOutput[]
    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[ModelExplainabilityJobDefinitionMonitoringOutput]
    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.

    ModelExplainabilityJobDefinitionMonitoringResources, ModelExplainabilityJobDefinitionMonitoringResourcesArgs

    ClusterConfig Pulumi.AwsNative.SageMaker.Inputs.ModelExplainabilityJobDefinitionClusterConfig
    The configuration for the cluster resources used to run the processing job.
    ClusterConfig ModelExplainabilityJobDefinitionClusterConfig
    The configuration for the cluster resources used to run the processing job.
    clusterConfig ModelExplainabilityJobDefinitionClusterConfig
    The configuration for the cluster resources used to run the processing job.
    clusterConfig ModelExplainabilityJobDefinitionClusterConfig
    The configuration for the cluster resources used to run the processing job.
    cluster_config ModelExplainabilityJobDefinitionClusterConfig
    The configuration for the cluster resources used to run the processing job.
    clusterConfig Property Map
    The configuration for the cluster resources used to run the processing job.

    ModelExplainabilityJobDefinitionNetworkConfig, ModelExplainabilityJobDefinitionNetworkConfigArgs

    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.ModelExplainabilityJobDefinitionVpcConfig
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.
    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 ModelExplainabilityJobDefinitionVpcConfig
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.
    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 ModelExplainabilityJobDefinitionVpcConfig
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.
    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 ModelExplainabilityJobDefinitionVpcConfig
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.
    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 ModelExplainabilityJobDefinitionVpcConfig
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.
    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
    Specifies a VPC that your training jobs and hosted models have access to. Control access to and from your training and model containers by configuring the VPC.

    ModelExplainabilityJobDefinitionS3Output, ModelExplainabilityJobDefinitionS3OutputArgs

    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.ModelExplainabilityJobDefinitionS3OutputS3UploadMode
    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 ModelExplainabilityJobDefinitionS3OutputS3UploadMode
    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 ModelExplainabilityJobDefinitionS3OutputS3UploadMode
    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 ModelExplainabilityJobDefinitionS3OutputS3UploadMode
    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 ModelExplainabilityJobDefinitionS3OutputS3UploadMode
    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.

    ModelExplainabilityJobDefinitionS3OutputS3UploadMode, ModelExplainabilityJobDefinitionS3OutputS3UploadModeArgs

    Continuous
    Continuous
    EndOfJob
    EndOfJob
    ModelExplainabilityJobDefinitionS3OutputS3UploadModeContinuous
    Continuous
    ModelExplainabilityJobDefinitionS3OutputS3UploadModeEndOfJob
    EndOfJob
    Continuous
    Continuous
    EndOfJob
    EndOfJob
    Continuous
    Continuous
    EndOfJob
    EndOfJob
    CONTINUOUS
    Continuous
    END_OF_JOB
    EndOfJob
    "Continuous"
    Continuous
    "EndOfJob"
    EndOfJob

    ModelExplainabilityJobDefinitionStoppingCondition, ModelExplainabilityJobDefinitionStoppingConditionArgs

    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.

    ModelExplainabilityJobDefinitionVpcConfig, ModelExplainabilityJobDefinitionVpcConfigArgs

    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

    We recommend new projects start with resources from the AWS provider.

    AWS Cloud Control v1.9.0 published on Monday, Nov 18, 2024 by Pulumi
    pulumi/pulumi-aws-native