Struct CreateEndpointConfigFluentBuilder

pub struct CreateEndpointConfigFluentBuilder { /* private fields */ }

Fluent builder constructing a request to CreateEndpointConfig.

Creates an endpoint configuration that SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want SageMaker to provision. Then you call the CreateEndpoint API.

Use this API if you want to use SageMaker hosting services to deploy models into production.

In the request, you define a ProductionVariant, for each model that you want to deploy. Each ProductionVariant parameter also describes the resources that you want SageMaker to provision. This includes the number and type of ML compute instances to deploy.

If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.

When you call CreateEndpoint, a load call is made to DynamoDB to verify that your endpoint configuration exists. When you read data from a DynamoDB table supporting Eventually Consistent Reads , the response might not reflect the results of a recently completed write operation. The response might include some stale data. If the dependent entities are not yet in DynamoDB, this causes a validation error. If you repeat your read request after a short time, the response should return the latest data. So retry logic is recommended to handle these possible issues. We also recommend that customers call DescribeEndpointConfig before calling CreateEndpoint to minimize the potential impact of a DynamoDB eventually consistent read.

Implementations

impl CreateEndpointConfigFluentBuilder

pub fn as_input(&self) -> &CreateEndpointConfigInputBuilder

Access the CreateEndpointConfig as a reference.

pub async fn send( self, ) -> Result<CreateEndpointConfigOutput, SdkError<CreateEndpointConfigError, HttpResponse>>

Sends the request and returns the response.

If an error occurs, an SdkError will be returned with additional details that can be matched against.

By default, any retryable failures will be retried twice. Retry behavior is configurable with the RetryConfig, which can be set when configuring the client.

pub fn customize( self, ) -> CustomizableOperation<CreateEndpointConfigOutput, CreateEndpointConfigError, Self>

Consumes this builder, creating a customizable operation that can be modified before being sent.

pub fn endpoint_config_name(self, input: impl Into<String>) -> Self

The name of the endpoint configuration. You specify this name in a CreateEndpoint request.

pub fn set_endpoint_config_name(self, input: Option<String>) -> Self

The name of the endpoint configuration. You specify this name in a CreateEndpoint request.

pub fn get_endpoint_config_name(&self) -> &Option<String>

The name of the endpoint configuration. You specify this name in a CreateEndpoint request.

pub fn production_variants(self, input: ProductionVariant) -> Self

Appends an item to ProductionVariants.

To override the contents of this collection use set_production_variants.

An array of ProductionVariant objects, one for each model that you want to host at this endpoint.

pub fn set_production_variants( self, input: Option<Vec<ProductionVariant>>, ) -> Self

An array of ProductionVariant objects, one for each model that you want to host at this endpoint.

pub fn get_production_variants(&self) -> &Option<Vec<ProductionVariant>>

An array of ProductionVariant objects, one for each model that you want to host at this endpoint.

pub fn data_capture_config(self, input: DataCaptureConfig) -> Self

Configuration to control how SageMaker AI captures inference data.

pub fn set_data_capture_config(self, input: Option<DataCaptureConfig>) -> Self

Configuration to control how SageMaker AI captures inference data.

pub fn get_data_capture_config(&self) -> &Option<DataCaptureConfig>

Configuration to control how SageMaker AI captures inference data.

pub fn tags(self, input: Tag) -> Self

Appends an item to Tags.

To override the contents of this collection use set_tags.

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

pub fn set_tags(self, input: Option<Vec<Tag>>) -> Self

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

pub fn get_tags(&self) -> &Option<Vec<Tag>>

An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.

pub fn kms_key_id(self, input: impl Into<String>) -> Self

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

The KmsKeyId can be any of the following formats:

• Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab

• Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab

• Alias name: alias/ExampleAlias

• Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias

The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS

Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.

For a list of instance types that support local instance storage, see Instance Store Volumes.

For more information about local instance storage encryption, see SSD Instance Store Volumes.

pub fn set_kms_key_id(self, input: Option<String>) -> Self

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

The KmsKeyId can be any of the following formats:

• Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab

• Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab

• Alias name: alias/ExampleAlias

• Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias

The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS

Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.

For a list of instance types that support local instance storage, see Instance Store Volumes.

For more information about local instance storage encryption, see SSD Instance Store Volumes.

pub fn get_kms_key_id(&self) -> &Option<String>

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

The KmsKeyId can be any of the following formats:

• Key ID: 1234abcd-12ab-34cd-56ef-1234567890ab

• Key ARN: arn:aws:kms:us-west-2:111122223333:key/1234abcd-12ab-34cd-56ef-1234567890ab

• Alias name: alias/ExampleAlias

• Alias name ARN: arn:aws:kms:us-west-2:111122223333:alias/ExampleAlias

The KMS key policy must grant permission to the IAM role that you specify in your CreateEndpoint, UpdateEndpoint requests. For more information, refer to the Amazon Web Services Key Management Service section Using Key Policies in Amazon Web Services KMS

Certain Nitro-based instances include local storage, dependent on the instance type. Local storage volumes are encrypted using a hardware module on the instance. You can't request a KmsKeyId when using an instance type with local storage. If any of the models that you specify in the ProductionVariants parameter use nitro-based instances with local storage, do not specify a value for the KmsKeyId parameter. If you specify a value for KmsKeyId when using any nitro-based instances with local storage, the call to CreateEndpointConfig fails.

For a list of instance types that support local instance storage, see Instance Store Volumes.

For more information about local instance storage encryption, see SSD Instance Store Volumes.

pub fn async_inference_config(self, input: AsyncInferenceConfig) -> Self

Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.

pub fn set_async_inference_config( self, input: Option<AsyncInferenceConfig>, ) -> Self

Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.

pub fn get_async_inference_config(&self) -> &Option<AsyncInferenceConfig>

Specifies configuration for how an endpoint performs asynchronous inference. This is a required field in order for your Endpoint to be invoked using InvokeEndpointAsync.

pub fn explainer_config(self, input: ExplainerConfig) -> Self

A member of CreateEndpointConfig that enables explainers.

pub fn set_explainer_config(self, input: Option<ExplainerConfig>) -> Self

A member of CreateEndpointConfig that enables explainers.

pub fn get_explainer_config(&self) -> &Option<ExplainerConfig>

A member of CreateEndpointConfig that enables explainers.

pub fn shadow_production_variants(self, input: ProductionVariant) -> Self

Appends an item to ShadowProductionVariants.

To override the contents of this collection use set_shadow_production_variants.

An array of ProductionVariant objects, 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.

pub fn set_shadow_production_variants( self, input: Option<Vec<ProductionVariant>>, ) -> Self

An array of ProductionVariant objects, 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.

pub fn get_shadow_production_variants(&self) -> &Option<Vec<ProductionVariant>>

An array of ProductionVariant objects, 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.

pub fn execution_role_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.

To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.

pub fn set_execution_role_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.

To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.

pub fn get_execution_role_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker AI can assume to perform actions on your behalf. For more information, see SageMaker AI Roles.

To be able to pass this role to Amazon SageMaker AI, the caller of this action must have the iam:PassRole permission.

pub fn vpc_config(self, input: VpcConfig) -> Self

Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.

pub fn set_vpc_config(self, input: Option<VpcConfig>) -> Self

Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.

pub fn get_vpc_config(&self) -> &Option<VpcConfig>

Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC.

pub fn enable_network_isolation(self, input: bool) -> Self

Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.

pub fn set_enable_network_isolation(self, input: Option<bool>) -> Self

Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.

pub fn get_enable_network_isolation(&self) -> &Option<bool>

Sets whether all model containers deployed to the endpoint are isolated. If they are, no inbound or outbound network calls can be made to or from the model containers.

Trait Implementations

impl Clone for CreateEndpointConfigFluentBuilder

fn clone(&self) -> CreateEndpointConfigFluentBuilder

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for CreateEndpointConfigFluentBuilder

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.