1. Packages
  2. AWS Classic
  3. API Docs
  4. sagemaker
  5. EndpointConfiguration

Try AWS Native preview for resources not in the classic version.

AWS Classic v6.2.1 published on Friday, Sep 22, 2023 by Pulumi

aws.sagemaker.EndpointConfiguration

Explore with Pulumi AI

aws logo

Try AWS Native preview for resources not in the classic version.

AWS Classic v6.2.1 published on Friday, Sep 22, 2023 by Pulumi

    Provides a SageMaker endpoint configuration resource.

    Example Usage

    Basic usage

    using System.Collections.Generic;
    using System.Linq;
    using Pulumi;
    using Aws = Pulumi.Aws;
    
    return await Deployment.RunAsync(() => 
    {
        var ec = new Aws.Sagemaker.EndpointConfiguration("ec", new()
        {
            ProductionVariants = new[]
            {
                new Aws.Sagemaker.Inputs.EndpointConfigurationProductionVariantArgs
                {
                    VariantName = "variant-1",
                    ModelName = aws_sagemaker_model.M.Name,
                    InitialInstanceCount = 1,
                    InstanceType = "ml.t2.medium",
                },
            },
            Tags = 
            {
                { "Name", "foo" },
            },
        });
    
    });
    
    package main
    
    import (
    	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		_, err := sagemaker.NewEndpointConfiguration(ctx, "ec", &sagemaker.EndpointConfigurationArgs{
    			ProductionVariants: sagemaker.EndpointConfigurationProductionVariantArray{
    				&sagemaker.EndpointConfigurationProductionVariantArgs{
    					VariantName:          pulumi.String("variant-1"),
    					ModelName:            pulumi.Any(aws_sagemaker_model.M.Name),
    					InitialInstanceCount: pulumi.Int(1),
    					InstanceType:         pulumi.String("ml.t2.medium"),
    				},
    			},
    			Tags: pulumi.StringMap{
    				"Name": pulumi.String("foo"),
    			},
    		})
    		if err != nil {
    			return err
    		}
    		return nil
    	})
    }
    
    package generated_program;
    
    import com.pulumi.Context;
    import com.pulumi.Pulumi;
    import com.pulumi.core.Output;
    import com.pulumi.aws.sagemaker.EndpointConfiguration;
    import com.pulumi.aws.sagemaker.EndpointConfigurationArgs;
    import com.pulumi.aws.sagemaker.inputs.EndpointConfigurationProductionVariantArgs;
    import java.util.List;
    import java.util.ArrayList;
    import java.util.Map;
    import java.io.File;
    import java.nio.file.Files;
    import java.nio.file.Paths;
    
    public class App {
        public static void main(String[] args) {
            Pulumi.run(App::stack);
        }
    
        public static void stack(Context ctx) {
            var ec = new EndpointConfiguration("ec", EndpointConfigurationArgs.builder()        
                .productionVariants(EndpointConfigurationProductionVariantArgs.builder()
                    .variantName("variant-1")
                    .modelName(aws_sagemaker_model.m().name())
                    .initialInstanceCount(1)
                    .instanceType("ml.t2.medium")
                    .build())
                .tags(Map.of("Name", "foo"))
                .build());
    
        }
    }
    
    import pulumi
    import pulumi_aws as aws
    
    ec = aws.sagemaker.EndpointConfiguration("ec",
        production_variants=[aws.sagemaker.EndpointConfigurationProductionVariantArgs(
            variant_name="variant-1",
            model_name=aws_sagemaker_model["m"]["name"],
            initial_instance_count=1,
            instance_type="ml.t2.medium",
        )],
        tags={
            "Name": "foo",
        })
    
    import * as pulumi from "@pulumi/pulumi";
    import * as aws from "@pulumi/aws";
    
    const ec = new aws.sagemaker.EndpointConfiguration("ec", {
        productionVariants: [{
            variantName: "variant-1",
            modelName: aws_sagemaker_model.m.name,
            initialInstanceCount: 1,
            instanceType: "ml.t2.medium",
        }],
        tags: {
            Name: "foo",
        },
    });
    
    resources:
      ec:
        type: aws:sagemaker:EndpointConfiguration
        properties:
          productionVariants:
            - variantName: variant-1
              modelName: ${aws_sagemaker_model.m.name}
              initialInstanceCount: 1
              instanceType: ml.t2.medium
          tags:
            Name: foo
    

    Create EndpointConfiguration Resource

    new EndpointConfiguration(name: string, args: EndpointConfigurationArgs, opts?: CustomResourceOptions);
    @overload
    def EndpointConfiguration(resource_name: str,
                              opts: Optional[ResourceOptions] = None,
                              async_inference_config: Optional[EndpointConfigurationAsyncInferenceConfigArgs] = None,
                              data_capture_config: Optional[EndpointConfigurationDataCaptureConfigArgs] = None,
                              kms_key_arn: Optional[str] = None,
                              name: Optional[str] = None,
                              name_prefix: Optional[str] = None,
                              production_variants: Optional[Sequence[EndpointConfigurationProductionVariantArgs]] = None,
                              shadow_production_variants: Optional[Sequence[EndpointConfigurationShadowProductionVariantArgs]] = None,
                              tags: Optional[Mapping[str, str]] = None)
    @overload
    def EndpointConfiguration(resource_name: str,
                              args: EndpointConfigurationArgs,
                              opts: Optional[ResourceOptions] = None)
    func NewEndpointConfiguration(ctx *Context, name string, args EndpointConfigurationArgs, opts ...ResourceOption) (*EndpointConfiguration, error)
    public EndpointConfiguration(string name, EndpointConfigurationArgs args, CustomResourceOptions? opts = null)
    public EndpointConfiguration(String name, EndpointConfigurationArgs args)
    public EndpointConfiguration(String name, EndpointConfigurationArgs args, CustomResourceOptions options)
    
    type: aws:sagemaker:EndpointConfiguration
    properties: # The arguments to resource properties.
    options: # Bag of options to control resource's behavior.
    
    
    name string
    The unique name of the resource.
    args EndpointConfigurationArgs
    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 EndpointConfigurationArgs
    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 EndpointConfigurationArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args EndpointConfigurationArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args EndpointConfigurationArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    EndpointConfiguration 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 EndpointConfiguration resource accepts the following input properties:

    ProductionVariants List<Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationProductionVariant>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    AsyncInferenceConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    DataCaptureConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    KmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    Name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    NamePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    ShadowProductionVariants List<Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationShadowProductionVariant>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    Tags Dictionary<string, string>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    ProductionVariants []EndpointConfigurationProductionVariantArgs

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    AsyncInferenceConfig EndpointConfigurationAsyncInferenceConfigArgs

    Specifies configuration for how an endpoint performs asynchronous inference.

    DataCaptureConfig EndpointConfigurationDataCaptureConfigArgs

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    KmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    Name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    NamePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    ShadowProductionVariants []EndpointConfigurationShadowProductionVariantArgs

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    Tags map[string]string

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    productionVariants List<EndpointConfigurationProductionVariant>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    asyncInferenceConfig EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name String

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix String

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    shadowProductionVariants List<EndpointConfigurationShadowProductionVariant>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Map<String,String>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    productionVariants EndpointConfigurationProductionVariant[]

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    asyncInferenceConfig EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    shadowProductionVariants EndpointConfigurationShadowProductionVariant[]

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags {[key: string]: string}

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    production_variants Sequence[EndpointConfigurationProductionVariantArgs]

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    async_inference_config EndpointConfigurationAsyncInferenceConfigArgs

    Specifies configuration for how an endpoint performs asynchronous inference.

    data_capture_config EndpointConfigurationDataCaptureConfigArgs

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kms_key_arn str

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name str

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    name_prefix str

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    shadow_production_variants Sequence[EndpointConfigurationShadowProductionVariantArgs]

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Mapping[str, str]

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    productionVariants List<Property Map>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    asyncInferenceConfig Property Map

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig Property Map

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name String

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix String

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    shadowProductionVariants List<Property Map>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Map<String>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    Outputs

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

    Arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    Id string

    The provider-assigned unique ID for this managed resource.

    TagsAll Dictionary<string, string>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    Arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    Id string

    The provider-assigned unique ID for this managed resource.

    TagsAll map[string]string

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn String

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    id String

    The provider-assigned unique ID for this managed resource.

    tagsAll Map<String,String>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    id string

    The provider-assigned unique ID for this managed resource.

    tagsAll {[key: string]: string}

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn str

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    id str

    The provider-assigned unique ID for this managed resource.

    tags_all Mapping[str, str]

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn String

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    id String

    The provider-assigned unique ID for this managed resource.

    tagsAll Map<String>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    Look up Existing EndpointConfiguration Resource

    Get an existing EndpointConfiguration resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: EndpointConfigurationState, opts?: CustomResourceOptions): EndpointConfiguration
    @staticmethod
    def get(resource_name: str,
            id: str,
            opts: Optional[ResourceOptions] = None,
            arn: Optional[str] = None,
            async_inference_config: Optional[EndpointConfigurationAsyncInferenceConfigArgs] = None,
            data_capture_config: Optional[EndpointConfigurationDataCaptureConfigArgs] = None,
            kms_key_arn: Optional[str] = None,
            name: Optional[str] = None,
            name_prefix: Optional[str] = None,
            production_variants: Optional[Sequence[EndpointConfigurationProductionVariantArgs]] = None,
            shadow_production_variants: Optional[Sequence[EndpointConfigurationShadowProductionVariantArgs]] = None,
            tags: Optional[Mapping[str, str]] = None,
            tags_all: Optional[Mapping[str, str]] = None) -> EndpointConfiguration
    func GetEndpointConfiguration(ctx *Context, name string, id IDInput, state *EndpointConfigurationState, opts ...ResourceOption) (*EndpointConfiguration, error)
    public static EndpointConfiguration Get(string name, Input<string> id, EndpointConfigurationState? state, CustomResourceOptions? opts = null)
    public static EndpointConfiguration get(String name, Output<String> id, EndpointConfigurationState state, CustomResourceOptions options)
    Resource lookup is not supported in YAML
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    Arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    AsyncInferenceConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    DataCaptureConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    KmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    Name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    NamePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    ProductionVariants List<Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationProductionVariant>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    ShadowProductionVariants List<Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationShadowProductionVariant>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    Tags Dictionary<string, string>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    TagsAll Dictionary<string, string>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    Arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    AsyncInferenceConfig EndpointConfigurationAsyncInferenceConfigArgs

    Specifies configuration for how an endpoint performs asynchronous inference.

    DataCaptureConfig EndpointConfigurationDataCaptureConfigArgs

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    KmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    Name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    NamePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    ProductionVariants []EndpointConfigurationProductionVariantArgs

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    ShadowProductionVariants []EndpointConfigurationShadowProductionVariantArgs

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    Tags map[string]string

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    TagsAll map[string]string

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn String

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    asyncInferenceConfig EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name String

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix String

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    productionVariants List<EndpointConfigurationProductionVariant>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    shadowProductionVariants List<EndpointConfigurationShadowProductionVariant>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Map<String,String>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    tagsAll Map<String,String>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn string

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    asyncInferenceConfig EndpointConfigurationAsyncInferenceConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig EndpointConfigurationDataCaptureConfig

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name string

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix string

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    productionVariants EndpointConfigurationProductionVariant[]

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    shadowProductionVariants EndpointConfigurationShadowProductionVariant[]

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags {[key: string]: string}

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    tagsAll {[key: string]: string}

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn str

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    async_inference_config EndpointConfigurationAsyncInferenceConfigArgs

    Specifies configuration for how an endpoint performs asynchronous inference.

    data_capture_config EndpointConfigurationDataCaptureConfigArgs

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kms_key_arn str

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name str

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    name_prefix str

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    production_variants Sequence[EndpointConfigurationProductionVariantArgs]

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    shadow_production_variants Sequence[EndpointConfigurationShadowProductionVariantArgs]

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Mapping[str, str]

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    tags_all Mapping[str, str]

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    arn String

    The Amazon Resource Name (ARN) assigned by AWS to this endpoint configuration.

    asyncInferenceConfig Property Map

    Specifies configuration for how an endpoint performs asynchronous inference.

    dataCaptureConfig Property Map

    Specifies the parameters to capture input/output of SageMaker models endpoints. Fields are documented below.

    kmsKeyArn String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt data on the storage volume attached to the ML compute instance that hosts the endpoint.

    name String

    The name of the endpoint configuration. If omitted, this provider will assign a random, unique name. Conflicts with name_prefix.

    namePrefix String

    Creates a unique endpoint configuration name beginning with the specified prefix. Conflicts with name.

    productionVariants List<Property Map>

    An list of ProductionVariant objects, one for each model that you want to host at this endpoint. Fields are documented below.

    shadowProductionVariants List<Property Map>

    Array of ProductionVariant objects. There is one for each model that you want to host at this endpoint in shadow mode with production traffic replicated from the model specified on ProductionVariants.If you use this field, you can only specify one variant for ProductionVariants and one variant for ShadowProductionVariants. Fields are documented below.

    tags Map<String>

    A mapping of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.

    tagsAll Map<String>

    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated:

    Please use tags instead.

    Supporting Types

    EndpointConfigurationAsyncInferenceConfig, EndpointConfigurationAsyncInferenceConfigArgs

    OutputConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationAsyncInferenceConfigOutputConfig

    Specifies the configuration for asynchronous inference invocation outputs.

    ClientConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationAsyncInferenceConfigClientConfig

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    OutputConfig EndpointConfigurationAsyncInferenceConfigOutputConfig

    Specifies the configuration for asynchronous inference invocation outputs.

    ClientConfig EndpointConfigurationAsyncInferenceConfigClientConfig

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    outputConfig EndpointConfigurationAsyncInferenceConfigOutputConfig

    Specifies the configuration for asynchronous inference invocation outputs.

    clientConfig EndpointConfigurationAsyncInferenceConfigClientConfig

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    outputConfig EndpointConfigurationAsyncInferenceConfigOutputConfig

    Specifies the configuration for asynchronous inference invocation outputs.

    clientConfig EndpointConfigurationAsyncInferenceConfigClientConfig

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    output_config EndpointConfigurationAsyncInferenceConfigOutputConfig

    Specifies the configuration for asynchronous inference invocation outputs.

    client_config EndpointConfigurationAsyncInferenceConfigClientConfig

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    outputConfig Property Map

    Specifies the configuration for asynchronous inference invocation outputs.

    clientConfig Property Map

    Configures the behavior of the client used by Amazon SageMaker to interact with the model container during asynchronous inference.

    EndpointConfigurationAsyncInferenceConfigClientConfig, EndpointConfigurationAsyncInferenceConfigClientConfigArgs

    MaxConcurrentInvocationsPerInstance int

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    MaxConcurrentInvocationsPerInstance int

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    maxConcurrentInvocationsPerInstance Integer

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    maxConcurrentInvocationsPerInstance number

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    max_concurrent_invocations_per_instance int

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    maxConcurrentInvocationsPerInstance Number

    The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, Amazon SageMaker will choose an optimal value for you.

    EndpointConfigurationAsyncInferenceConfigOutputConfig, EndpointConfigurationAsyncInferenceConfigOutputConfigArgs

    S3OutputPath string

    The Amazon S3 location to upload inference responses to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    NotificationConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig

    Specifies the configuration for notifications of inference results for asynchronous inference.

    S3FailurePath string

    The Amazon S3 location to upload failure inference responses to.

    S3OutputPath string

    The Amazon S3 location to upload inference responses to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    NotificationConfig EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig

    Specifies the configuration for notifications of inference results for asynchronous inference.

    S3FailurePath string

    The Amazon S3 location to upload failure inference responses to.

    s3OutputPath String

    The Amazon S3 location to upload inference responses to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    notificationConfig EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig

    Specifies the configuration for notifications of inference results for asynchronous inference.

    s3FailurePath String

    The Amazon S3 location to upload failure inference responses to.

    s3OutputPath string

    The Amazon S3 location to upload inference responses to.

    kmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    notificationConfig EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig

    Specifies the configuration for notifications of inference results for asynchronous inference.

    s3FailurePath string

    The Amazon S3 location to upload failure inference responses to.

    s3_output_path str

    The Amazon S3 location to upload inference responses to.

    kms_key_id str

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    notification_config EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig

    Specifies the configuration for notifications of inference results for asynchronous inference.

    s3_failure_path str

    The Amazon S3 location to upload failure inference responses to.

    s3OutputPath String

    The Amazon S3 location to upload inference responses to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that Amazon SageMaker uses to encrypt the asynchronous inference output in Amazon S3.

    notificationConfig Property Map

    Specifies the configuration for notifications of inference results for asynchronous inference.

    s3FailurePath String

    The Amazon S3 location to upload failure inference responses to.

    EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfig, EndpointConfigurationAsyncInferenceConfigOutputConfigNotificationConfigArgs

    ErrorTopic string

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    IncludeInferenceResponseIns List<string>

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    SuccessTopic string

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    ErrorTopic string

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    IncludeInferenceResponseIns []string

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    SuccessTopic string

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    errorTopic String

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    includeInferenceResponseIns List<String>

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    successTopic String

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    errorTopic string

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    includeInferenceResponseIns string[]

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    successTopic string

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    error_topic str

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    include_inference_response_ins Sequence[str]

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    success_topic str

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    errorTopic String

    Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.

    includeInferenceResponseIns List<String>

    The Amazon SNS topics where you want the inference response to be included. Valid values are SUCCESS_NOTIFICATION_TOPIC and ERROR_NOTIFICATION_TOPIC.

    successTopic String

    Amazon SNS topic to post a notification to when inference completes successfully. If no topic is provided, no notification is sent on success.

    EndpointConfigurationDataCaptureConfig, EndpointConfigurationDataCaptureConfigArgs

    CaptureOptions List<Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationDataCaptureConfigCaptureOption>

    Specifies what data to capture. Fields are documented below.

    DestinationS3Uri string

    The URL for S3 location where the captured data is stored.

    InitialSamplingPercentage int

    Portion of data to capture. Should be between 0 and 100.

    CaptureContentTypeHeader Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader

    The content type headers to capture. Fields are documented below.

    EnableCapture bool

    Flag to enable data capture. Defaults to false.

    KmsKeyId string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    CaptureOptions []EndpointConfigurationDataCaptureConfigCaptureOption

    Specifies what data to capture. Fields are documented below.

    DestinationS3Uri string

    The URL for S3 location where the captured data is stored.

    InitialSamplingPercentage int

    Portion of data to capture. Should be between 0 and 100.

    CaptureContentTypeHeader EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader

    The content type headers to capture. Fields are documented below.

    EnableCapture bool

    Flag to enable data capture. Defaults to false.

    KmsKeyId string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    captureOptions List<EndpointConfigurationDataCaptureConfigCaptureOption>

    Specifies what data to capture. Fields are documented below.

    destinationS3Uri String

    The URL for S3 location where the captured data is stored.

    initialSamplingPercentage Integer

    Portion of data to capture. Should be between 0 and 100.

    captureContentTypeHeader EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader

    The content type headers to capture. Fields are documented below.

    enableCapture Boolean

    Flag to enable data capture. Defaults to false.

    kmsKeyId String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    captureOptions EndpointConfigurationDataCaptureConfigCaptureOption[]

    Specifies what data to capture. Fields are documented below.

    destinationS3Uri string

    The URL for S3 location where the captured data is stored.

    initialSamplingPercentage number

    Portion of data to capture. Should be between 0 and 100.

    captureContentTypeHeader EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader

    The content type headers to capture. Fields are documented below.

    enableCapture boolean

    Flag to enable data capture. Defaults to false.

    kmsKeyId string

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    capture_options Sequence[EndpointConfigurationDataCaptureConfigCaptureOption]

    Specifies what data to capture. Fields are documented below.

    destination_s3_uri str

    The URL for S3 location where the captured data is stored.

    initial_sampling_percentage int

    Portion of data to capture. Should be between 0 and 100.

    capture_content_type_header EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader

    The content type headers to capture. Fields are documented below.

    enable_capture bool

    Flag to enable data capture. Defaults to false.

    kms_key_id str

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    captureOptions List<Property Map>

    Specifies what data to capture. Fields are documented below.

    destinationS3Uri String

    The URL for S3 location where the captured data is stored.

    initialSamplingPercentage Number

    Portion of data to capture. Should be between 0 and 100.

    captureContentTypeHeader Property Map

    The content type headers to capture. Fields are documented below.

    enableCapture Boolean

    Flag to enable data capture. Defaults to false.

    kmsKeyId String

    Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon SageMaker uses to encrypt the captured data on Amazon S3.

    EndpointConfigurationDataCaptureConfigCaptureContentTypeHeader, EndpointConfigurationDataCaptureConfigCaptureContentTypeHeaderArgs

    CsvContentTypes List<string>

    The CSV content type headers to capture.

    JsonContentTypes List<string>

    The JSON content type headers to capture.

    CsvContentTypes []string

    The CSV content type headers to capture.

    JsonContentTypes []string

    The JSON content type headers to capture.

    csvContentTypes List<String>

    The CSV content type headers to capture.

    jsonContentTypes List<String>

    The JSON content type headers to capture.

    csvContentTypes string[]

    The CSV content type headers to capture.

    jsonContentTypes string[]

    The JSON content type headers to capture.

    csv_content_types Sequence[str]

    The CSV content type headers to capture.

    json_content_types Sequence[str]

    The JSON content type headers to capture.

    csvContentTypes List<String>

    The CSV content type headers to capture.

    jsonContentTypes List<String>

    The JSON content type headers to capture.

    EndpointConfigurationDataCaptureConfigCaptureOption, EndpointConfigurationDataCaptureConfigCaptureOptionArgs

    CaptureMode string

    Specifies the data to be captured. Should be one of Input or Output.

    CaptureMode string

    Specifies the data to be captured. Should be one of Input or Output.

    captureMode String

    Specifies the data to be captured. Should be one of Input or Output.

    captureMode string

    Specifies the data to be captured. Should be one of Input or Output.

    capture_mode str

    Specifies the data to be captured. Should be one of Input or Output.

    captureMode String

    Specifies the data to be captured. Should be one of Input or Output.

    EndpointConfigurationProductionVariant, EndpointConfigurationProductionVariantArgs

    ModelName string

    The name of the model to use.

    AcceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    ContainerStartupHealthCheckTimeoutInSeconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    CoreDumpConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    EnableSsmAccess bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    InitialInstanceCount int

    Initial number of instances used for auto-scaling.

    InitialVariantWeight double

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    InstanceType string

    The type of instance to start.

    ModelDataDownloadTimeoutInSeconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    ServerlessConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    VariantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    VolumeSizeInGb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    ModelName string

    The name of the model to use.

    AcceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    ContainerStartupHealthCheckTimeoutInSeconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    CoreDumpConfig EndpointConfigurationProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    EnableSsmAccess bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    InitialInstanceCount int

    Initial number of instances used for auto-scaling.

    InitialVariantWeight float64

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    InstanceType string

    The type of instance to start.

    ModelDataDownloadTimeoutInSeconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    ServerlessConfig EndpointConfigurationProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    VariantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    VolumeSizeInGb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName String

    The name of the model to use.

    acceleratorType String

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds Integer

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig EndpointConfigurationProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess Boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount Integer

    Initial number of instances used for auto-scaling.

    initialVariantWeight Double

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType String

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds Integer

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig EndpointConfigurationProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName String

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb Integer

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName string

    The name of the model to use.

    acceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds number

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig EndpointConfigurationProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount number

    Initial number of instances used for auto-scaling.

    initialVariantWeight number

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType string

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds number

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig EndpointConfigurationProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb number

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    model_name str

    The name of the model to use.

    accelerator_type str

    The size of the Elastic Inference (EI) instance to use for the production variant.

    container_startup_health_check_timeout_in_seconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    core_dump_config EndpointConfigurationProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enable_ssm_access bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initial_instance_count int

    Initial number of instances used for auto-scaling.

    initial_variant_weight float

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instance_type str

    The type of instance to start.

    model_data_download_timeout_in_seconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverless_config EndpointConfigurationProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variant_name str

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volume_size_in_gb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName String

    The name of the model to use.

    acceleratorType String

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds Number

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig Property Map

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess Boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount Number

    Initial number of instances used for auto-scaling.

    initialVariantWeight Number

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType String

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds Number

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig Property Map

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName String

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb Number

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    EndpointConfigurationProductionVariantCoreDumpConfig, EndpointConfigurationProductionVariantCoreDumpConfigArgs

    DestinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    DestinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri String

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destination_s3_uri str

    The Amazon S3 bucket to send the core dump to.

    kms_key_id str

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri String

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    EndpointConfigurationProductionVariantServerlessConfig, EndpointConfigurationProductionVariantServerlessConfigArgs

    MaxConcurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    MemorySizeInMb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    ProvisionedConcurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    MaxConcurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    MemorySizeInMb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    ProvisionedConcurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency Integer

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb Integer

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency Integer

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency number

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb number

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency number

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    max_concurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memory_size_in_mb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisioned_concurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency Number

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb Number

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency Number

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    EndpointConfigurationShadowProductionVariant, EndpointConfigurationShadowProductionVariantArgs

    ModelName string

    The name of the model to use.

    AcceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    ContainerStartupHealthCheckTimeoutInSeconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    CoreDumpConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationShadowProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    EnableSsmAccess bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    InitialInstanceCount int

    Initial number of instances used for auto-scaling.

    InitialVariantWeight double

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    InstanceType string

    The type of instance to start.

    ModelDataDownloadTimeoutInSeconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    ServerlessConfig Pulumi.Aws.Sagemaker.Inputs.EndpointConfigurationShadowProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    VariantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    VolumeSizeInGb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    ModelName string

    The name of the model to use.

    AcceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    ContainerStartupHealthCheckTimeoutInSeconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    CoreDumpConfig EndpointConfigurationShadowProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    EnableSsmAccess bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    InitialInstanceCount int

    Initial number of instances used for auto-scaling.

    InitialVariantWeight float64

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    InstanceType string

    The type of instance to start.

    ModelDataDownloadTimeoutInSeconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    ServerlessConfig EndpointConfigurationShadowProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    VariantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    VolumeSizeInGb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName String

    The name of the model to use.

    acceleratorType String

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds Integer

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig EndpointConfigurationShadowProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess Boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount Integer

    Initial number of instances used for auto-scaling.

    initialVariantWeight Double

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType String

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds Integer

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig EndpointConfigurationShadowProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName String

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb Integer

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName string

    The name of the model to use.

    acceleratorType string

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds number

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig EndpointConfigurationShadowProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount number

    Initial number of instances used for auto-scaling.

    initialVariantWeight number

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType string

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds number

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig EndpointConfigurationShadowProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName string

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb number

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    model_name str

    The name of the model to use.

    accelerator_type str

    The size of the Elastic Inference (EI) instance to use for the production variant.

    container_startup_health_check_timeout_in_seconds int

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    core_dump_config EndpointConfigurationShadowProductionVariantCoreDumpConfig

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enable_ssm_access bool

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initial_instance_count int

    Initial number of instances used for auto-scaling.

    initial_variant_weight float

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instance_type str

    The type of instance to start.

    model_data_download_timeout_in_seconds int

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverless_config EndpointConfigurationShadowProductionVariantServerlessConfig

    Specifies configuration for how an endpoint performs asynchronous inference.

    variant_name str

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volume_size_in_gb int

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    modelName String

    The name of the model to use.

    acceleratorType String

    The size of the Elastic Inference (EI) instance to use for the production variant.

    containerStartupHealthCheckTimeoutInSeconds Number

    The timeout value, in seconds, for your inference container to pass health check by SageMaker Hosting. For more information about health check, see How Your Container Should Respond to Health Check (Ping) Requests. Valid values between 60 and 3600.

    coreDumpConfig Property Map

    Specifies configuration for a core dump from the model container when the process crashes. Fields are documented below.

    enableSsmAccess Boolean

    You can use this parameter to turn on native Amazon Web Services Systems Manager (SSM) access for a production variant behind an endpoint. By default, SSM access is disabled for all production variants behind an endpoints.

    initialInstanceCount Number

    Initial number of instances used for auto-scaling.

    initialVariantWeight Number

    Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. If unspecified, it defaults to 1.0.

    instanceType String

    The type of instance to start.

    modelDataDownloadTimeoutInSeconds Number

    The timeout value, in seconds, to download and extract the model that you want to host from Amazon S3 to the individual inference instance associated with this production variant. Valid values between 60 and 3600.

    serverlessConfig Property Map

    Specifies configuration for how an endpoint performs asynchronous inference.

    variantName String

    The name of the variant. If omitted, this provider will assign a random, unique name.

    volumeSizeInGb Number

    The size, in GB, of the ML storage volume attached to individual inference instance associated with the production variant. Valid values between 1 and 512.

    EndpointConfigurationShadowProductionVariantCoreDumpConfig, EndpointConfigurationShadowProductionVariantCoreDumpConfigArgs

    DestinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    DestinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    KmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri String

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri string

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId string

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destination_s3_uri str

    The Amazon S3 bucket to send the core dump to.

    kms_key_id str

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    destinationS3Uri String

    The Amazon S3 bucket to send the core dump to.

    kmsKeyId String

    The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the core dump data at rest using Amazon S3 server-side encryption.

    EndpointConfigurationShadowProductionVariantServerlessConfig, EndpointConfigurationShadowProductionVariantServerlessConfigArgs

    MaxConcurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    MemorySizeInMb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    ProvisionedConcurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    MaxConcurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    MemorySizeInMb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    ProvisionedConcurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency Integer

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb Integer

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency Integer

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency number

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb number

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency number

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    max_concurrency int

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memory_size_in_mb int

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisioned_concurrency int

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    maxConcurrency Number

    The maximum number of concurrent invocations your serverless endpoint can process. Valid values are between 1 and 200.

    memorySizeInMb Number

    The memory size of your serverless endpoint. Valid values are in 1 GB increments: 1024 MB, 2048 MB, 3072 MB, 4096 MB, 5120 MB, or 6144 MB.

    provisionedConcurrency Number

    The amount of provisioned concurrency to allocate for the serverless endpoint. Should be less than or equal to max_concurrency. Valid values are between 1 and 200.

    Import

    Using pulumi import, import endpoint configurations using the name. For example:

     $ pulumi import aws:sagemaker/endpointConfiguration:EndpointConfiguration test_endpoint_config endpoint-config-foo
    

    Package Details

    Repository
    AWS Classic pulumi/pulumi-aws
    License
    Apache-2.0
    Notes

    This Pulumi package is based on the aws Terraform Provider.

    aws logo

    Try AWS Native preview for resources not in the classic version.

    AWS Classic v6.2.1 published on Friday, Sep 22, 2023 by Pulumi