feat(stepfunctions-tasks): support for SageMaker APIs: CreateEndpoint…

…, CreateEndpointConfig, CreateModel, and UpdateEndpoint (#10187)

**Implementation**

Update package `@aws-cdk/aws-stepfunctions-tasks` to include support for SageMaker **CreateEndpoint**, **CreateEndpointConfig**, **CreateModel**, **UpdateEndpoint**    API as per documentation here: https://docs.aws.amazon.com/step-functions/latest/dg/connect-sagemaker.html

Includes support for the following Amazon SageMaker API calls:
* `CreateEndpoint`
* `CreateEndpointConfig`
* `CreateModel`
* `UpdateEndpoint`

Closes #6572

packages/@aws-cdk/aws-stepfunctions-tasks/README.md

@@ -52,6 +52,10 @@ This module is part of the [AWS Cloud Development Kit](https://github.com/aws/aw
 - [SageMaker](#sagemaker)
   - [Create Training Job](#create-training-job)
   - [Create Transform Job](#create-transform-job)
+  - [Create Endpoint](#create-endpoint)
+  - [Create Endpoint Config](#create-endpoint-config)
+  - [Create Model](#create-model)
+  - [Update Endpoint](#update-endpoint)
 - [SNS](#sns)
 - [Step Functions](#step-functions)
   - [Start Execution](#start-execution)
@@ -774,6 +778,59 @@ new sfn.SagemakerTransformTask(this, 'Batch Inference', {
 
 ```
 
+### Create Endpoint
+
+You can call the [`CreateEndpoint`](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpoint.html) API from a `Task` state.
+
+```ts
+new sfn.SageMakerCreateEndpoint(this, 'SagemakerEndpoint', {
+  endpointName: sfn.JsonPath.stringAt('$.EndpointName'),
+  endpointConfigName: sfn.JsonPath.stringAt('$.EndpointConfigName'),
+});
+```
+
+### Create Endpoint Config
+
+You can call the [`CreateEndpointConfig`](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateEndpointConfig.html) API from a `Task` state.
+
+```ts
+new sfn.SageMakerCreateEndpointConfig(this, 'SagemakerEndpointConfig', {
+  endpointConfigName: 'MyEndpointConfig',
+  productionVariants: [{
+  initialInstanceCount: 2,
+  instanceType: ec2.InstanceType.of(ec2.InstanceClass.M5, ec2.InstanceSize.XLARGE),
+     modelName: 'MyModel',
+     variantName: 'awesome-variant',
+   }],
+});
+```
+
+### Create Model
+
+You can call the [`CreateModel`](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html) API from a `Task` state.
+
+```ts
+new sfn.SageMakerCreateModel(this, 'Sagemaker', {
+  modelName: 'MyModel',
+  primaryContainer: new tasks.ContainerDefinition({
+   image: tasks.DockerImage.fromJsonExpression(sfn.JsonPath.stringAt('$.Model.imageName')),
+   mode: tasks.Mode.SINGLE_MODEL,
+   modelS3Location: tasks.S3Location.fromJsonExpression('$.TrainingJob.ModelArtifacts.S3ModelArtifacts'),
+  }),
+});
+```
+
+### Update Endpoint
+
+You can call the [`UpdateEndpoint`](https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_UpdateEndpoint.html) API from a `Task` state.
+
+```ts
+new sfn.SageMakerUpdateEndpoint(this, 'SagemakerEndpoint', {
+    endpointName: sfn.JsonPath.stringAt('$.Endpoint.Name'),
+    endpointConfigName: sfn.JsonPath.stringAt('$.Endpoint.EndpointConfig'),
+  });
+```
+
 ## SNS
 
 Step Functions supports [Amazon SNS](https://docs.aws.amazon.com/step-functions/latest/dg/connect-sns.html) through the service integration pattern.

packages/@aws-cdk/aws-stepfunctions-tasks/lib/index.ts

@@ -14,6 +14,10 @@ export * from './ecs/run-task';
 export * from './sagemaker/base-types';
 export * from './sagemaker/create-training-job';
 export * from './sagemaker/create-transform-job';
+export * from './sagemaker/create-endpoint';
+export * from './sagemaker/create-endpoint-config';
+export * from './sagemaker/create-model';
+export * from './sagemaker/update-endpoint';
 export * from './start-execution';
 export * from './stepfunctions/start-execution';
 export * from './stepfunctions/invoke-activity';

packages/@aws-cdk/aws-stepfunctions-tasks/lib/sagemaker/base-types.ts

@@ -625,6 +625,218 @@ export interface TransformResources {
   readonly volumeEncryptionKey?: kms.IKey;
 }
 
+/**
+ * Properties to define a ContainerDefinition
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ * @experimental
+ */
+export interface ContainerDefinitionOptions {
+  /**
+   * The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored.
+   *
+   * @default - None
+   */
+  readonly image?: DockerImage;
+  /**
+   * The environment variables to set in the Docker container
+   *
+   * @default - No variables
+   */
+  readonly environmentVariables?: sfn.TaskInput;
+  /**
+   * The name or Amazon Resource Name (ARN) of the model package to use to create the model.
+   *
+   * @default - None
+   */
+  readonly modelPackageName?: string;
+  /**
+   * Defines how many models the container hosts
+   *
+   * @default - Mode.SINGLE_MODEL
+   */
+  readonly mode?: Mode;
+  /**
+   * This parameter is ignored for models that contain only a PrimaryContainer.
+   * When a ContainerDefinition is part of an inference pipeline,
+   * the value of the parameter uniquely identifies the container for the purposes of logging and metrics.
+   *
+   * @default - None
+   */
+  readonly containerHostName?: string;
+  /**
+   * The S3 path where the model artifacts, which result from model training, are stored.
+   * This path must point to a single gzip compressed tar archive (.tar.gz suffix).
+   * The S3 path is required for Amazon SageMaker built-in algorithms, but not if you use your own algorithms.
+   *
+   * @default - None
+   */
+  readonly modelS3Location?: S3Location;
+}
+
+/**
+ * Describes the container, as part of model definition.
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ * @experimental
+ */
+export class ContainerDefinition implements IContainerDefinition {
+
+  constructor(private readonly options: ContainerDefinitionOptions) {}
+
+  /**
+   * Called when the ContainerDefinition type configured on Sagemaker Task
+   */
+  public bind(task: ISageMakerTask): ContainerDefinitionConfig {
+    return {
+      parameters: {
+        ContainerHostname: this.options.containerHostName,
+        Image: this.options.image?.bind(task).imageUri,
+        Mode: this.options.mode,
+        ModelDataUrl: this.options.modelS3Location?.bind(task, { forReading: true }).uri,
+        ModelPackageName: this.options.modelPackageName,
+        Environment: this.options.environmentVariables?.value,
+      },
+    };
+  }
+}
+
+/**
+ * Configuration of the container used to host the model
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ContainerDefinition.html
+ * @experimental
+ */
+export interface IContainerDefinition {
+  /**
+   * Called when the ContainerDefinition is used by a SageMaker task.
+   */
+  bind(task: ISageMakerTask): ContainerDefinitionConfig;
+}
+
+/**
+ * Configuration options for the ContainerDefinition
+ */
+export interface ContainerDefinitionConfig {
+  /**
+   * Additional parameters to pass to the base task
+   *
+   * @default - No additional parameters passed
+   */
+  readonly parameters?: { [key: string]: any };
+}
+
+/**
+ * Specifies how many models the container hosts
+ *
+ * @experimental
+ */
+export enum Mode {
+  /**
+   * Container hosts a single model
+   */
+  SINGLE_MODEL = 'SingleModel',
+  /**
+   * Container hosts multiple models
+   *
+   * @see https://docs.aws.amazon.com/sagemaker/latest/dg/multi-model-endpoints.html
+   */
+  MULTI_MODEL = 'MultiModel',
+}
+
+/**
+ * Identifies a model that you want to host and the resources to deploy for hosting it.
+ *
+ * @see  https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ProductionVariant.html
+ * @experimental
+ */
+export interface ProductionVariant {
+  /**
+   * The size of the Elastic Inference (EI) instance to use for the production variant.
+   *
+   * @default - None
+   */
+  readonly acceleratorType?: AcceleratorType;
+  /**
+   * Number of instances to launch initially.
+   *
+   * @default - 1
+   */
+  readonly initialInstanceCount?: number;
+  /**
+   * Determines initial traffic distribution among all of the models that you specify in the endpoint configuration.
+   *
+   * @default - 1.0
+   */
+  readonly initialVariantWeight?: number;
+  /**
+   * The ML compute instance type
+   */
+  readonly instanceType: ec2.InstanceType;
+  /**
+   * The name of the production variant.
+   */
+  readonly variantName: string;
+  /**
+   * The name of the model that you want to host. This is the name that you specified when creating the model.
+   */
+  readonly modelName: string;
+}
+
+/**
+ * The generation of Elastic Inference (EI) instance
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
+ * @experimental
+ */
+export class AcceleratorClass {
+  /**
+   * Elastic Inference accelerator 1st generation
+   */
+  public static readonly EIA1 = AcceleratorClass.of('eia1');
+  /**
+   * Elastic Inference accelerator 2nd generation
+   */
+  public static readonly EIA2 = AcceleratorClass.of('eia2');
+  /**
+   * Custom AcceleratorType
+   * @param version - Elastic Inference accelerator generation
+  */
+  public static of(version: string) { return new AcceleratorClass(version); }
+  /**
+   * @param version - Elastic Inference accelerator generation
+   */
+  private constructor(public readonly version: string) { }
+}
+
+/**
+ * The size of the Elastic Inference (EI) instance to use for the production variant.
+ * EI instances provide on-demand GPU computing for inference
+ *
+ * @see https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html
+ * @experimental
+ */
+export class AcceleratorType {
+  /**
+   * AcceleratorType
+   *
+   * This class takes a combination of a class and size.
+   */
+  public static of(acceleratorClass: AcceleratorClass, instanceSize: ec2.InstanceSize) {
+    return new AcceleratorType(`ml.${acceleratorClass}.${instanceSize}`);
+  }
+
+  constructor(private readonly instanceTypeIdentifier: string) {
+  }
+
+  /**
+   * Return the accelerator type as a dotted string
+   */
+  public toString(): string {
+    return this.instanceTypeIdentifier;
+  }
+}
+
 /**
  * Specifies the number of records to include in a mini-batch for an HTTP inference request.
  *