AWS Tools for Windows PowerShell
Command Reference

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Synopsis

Calls the Amazon SageMaker Service CreateEndpointConfig API operation.

Syntax

New-SMEndpointConfig
-EndpointConfigName <String>
-DataCaptureConfig_CaptureOption <CaptureOption[]>
-InferenceConfig_ContentTemplate <String>
-CaptureContentTypeHeader_CsvContentType <String[]>
-DataCaptureConfig_DestinationS3Uri <String>
-DataCaptureConfig_EnableCapture <Boolean>
-ClarifyExplainerConfig_EnableExplanation <String>
-EnableNetworkIsolation <Boolean>
-NotificationConfig_ErrorTopic <String>
-ExecutionRoleArn <String>
-InferenceConfig_FeatureHeader <String[]>
-InferenceConfig_FeaturesAttribute <String>
-InferenceConfig_FeatureType <String[]>
-TextConfig_Granularity <ClarifyTextGranularity>
-NotificationConfig_IncludeInferenceResponseIn <String[]>
-DataCaptureConfig_InitialSamplingPercentage <Int32>
-CaptureContentTypeHeader_JsonContentType <String[]>
-OutputConfig_KmsKeyId <String>
-DataCaptureConfig_KmsKeyId <String>
-KmsKeyId <String>
-InferenceConfig_LabelAttribute <String>
-InferenceConfig_LabelHeader <String[]>
-InferenceConfig_LabelIndex <Int32>
-TextConfig_Language <ClarifyTextLanguage>
-ClientConfig_MaxConcurrentInvocationsPerInstance <Int32>
-InferenceConfig_MaxPayloadInMB <Int32>
-InferenceConfig_MaxRecordCount <Int32>
-ShapBaselineConfig_MimeType <String>
-ShapConfig_NumberOfSample <Int32>
-InferenceConfig_ProbabilityAttribute <String>
-InferenceConfig_ProbabilityIndex <Int32>
-ProductionVariant <ProductionVariant[]>
-OutputConfig_S3FailurePath <String>
-OutputConfig_S3OutputPath <String>
-VpcConfig_SecurityGroupId <String[]>
-ShapConfig_Seed <Int32>
-ShadowProductionVariant <ProductionVariant[]>
-ShapBaselineConfig_ShapBaseline <String>
-ShapBaselineConfig_ShapBaselineUri <String>
-VpcConfig_Subnet <String[]>
-NotificationConfig_SuccessTopic <String>
-Tag <Tag[]>
-ShapConfig_UseLogit <Boolean>
-Select <String>
-Force <SwitchParameter>
-ClientConfig <AmazonSageMakerConfig>

Description

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.

Parameters

-CaptureContentTypeHeader_CsvContentType <String[]>
The list of all content type headers that Amazon SageMaker AI will treat as CSV and capture accordingly. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesDataCaptureConfig_CaptureContentTypeHeader_CsvContentTypes
-CaptureContentTypeHeader_JsonContentType <String[]>
The list of all content type headers that SageMaker AI will treat as JSON and capture accordingly. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesDataCaptureConfig_CaptureContentTypeHeader_JsonContentTypes
-ClarifyExplainerConfig_EnableExplanation <String>
A JMESPath boolean expression used to filter which records to explain. Explanations are activated by default. See EnableExplanationsfor additional information.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_EnableExplanations
-ClientConfig <AmazonSageMakerConfig>
Amazon.PowerShell.Cmdlets.SM.AmazonSageMakerClientCmdlet.ClientConfig
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-ClientConfig_MaxConcurrentInvocationsPerInstance <Int32>
The maximum number of concurrent requests sent by the SageMaker client to the model container. If no value is provided, SageMaker chooses an optimal value.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_ClientConfig_MaxConcurrentInvocationsPerInstance
-DataCaptureConfig_CaptureOption <CaptureOption[]>
Specifies data Model Monitor will capture. You can configure whether to collect only input, only output, or both Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesDataCaptureConfig_CaptureOptions
-DataCaptureConfig_DestinationS3Uri <String>
The Amazon S3 location used to capture the data.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-DataCaptureConfig_EnableCapture <Boolean>
Whether data capture should be enabled or disabled (defaults to enabled).
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-DataCaptureConfig_InitialSamplingPercentage <Int32>
The percentage of requests SageMaker AI will capture. A lower value is recommended for Endpoints with high traffic.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-DataCaptureConfig_KmsKeyId <String>
The Amazon Resource Name (ARN) of an Key Management Service key that SageMaker AI uses to encrypt the captured data at rest using Amazon S3 server-side encryption.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
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-EnableNetworkIsolation <Boolean>
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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-EndpointConfigName <String>
The name of the endpoint configuration. You specify this name in a CreateEndpoint request.
Required?True
Position?1
Accept pipeline input?True (ByValue, ByPropertyName)
-ExecutionRoleArn <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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-Force <SwitchParameter>
This parameter overrides confirmation prompts to force the cmdlet to continue its operation. This parameter should always be used with caution.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-InferenceConfig_ContentTemplate <String>
A template string used to format a JSON record into an acceptable model container input. For example, a ContentTemplate string '{"myfeatures":$features}' will format a list of features [1,2,3] into the record string '{"myfeatures":[1,2,3]}'. Required only when the model container input is in JSON Lines format.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_ContentTemplate
-InferenceConfig_FeatureHeader <String[]>
The names of the features. If provided, these are included in the endpoint response payload to help readability of the InvokeEndpoint output. See the Response section under Invoke the endpoint in the Developer Guide for more information. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_FeatureHeaders
-InferenceConfig_FeaturesAttribute <String>
Provides the JMESPath expression to extract the features from a model container input in JSON Lines format. For example, if FeaturesAttribute is the JMESPath expression 'myfeatures', it extracts a list of features [1,2,3] from request data '{"myfeatures":[1,2,3]}'.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_FeaturesAttribute
-InferenceConfig_FeatureType <String[]>
A list of data types of the features (optional). Applicable only to NLP explainability. If provided, FeatureTypes must have at least one 'text' string (for example, ['text']). If FeatureTypes is not provided, the explainer infers the feature types based on the baseline data. The feature types are included in the endpoint response payload. For additional information see the response section under Invoke the endpoint in the Developer Guide for more information. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_FeatureTypes
-InferenceConfig_LabelAttribute <String>
A JMESPath expression used to locate the list of label headers in the model container output.Example: If the model container output of a batch request is '{"labels":["cat","dog","fish"],"probability":[0.6,0.3,0.1]}', then set LabelAttribute to 'labels' to extract the list of label headers ["cat","dog","fish"]
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_LabelAttribute
-InferenceConfig_LabelHeader <String[]>
For multiclass classification problems, the label headers are the names of the classes. Otherwise, the label header is the name of the predicted label. These are used to help readability for the output of the InvokeEndpoint API. See the response section under Invoke the endpoint in the Developer Guide for more information. If there are no label headers in the model container output, provide them manually using this parameter. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_LabelHeaders
-InferenceConfig_LabelIndex <Int32>
A zero-based index used to extract a label header or list of label headers from model container output in CSV format.Example for a multiclass model: If the model container output consists of label headers followed by probabilities: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set LabelIndex to 0 to select the label headers ['cat','dog','fish'].
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_LabelIndex
-InferenceConfig_MaxPayloadInMB <Int32>
The maximum payload size (MB) allowed of a request from the explainer to the model container. Defaults to 6 MB.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_MaxPayloadInMB
-InferenceConfig_MaxRecordCount <Int32>
The maximum number of records in a request that the model container can process when querying the model container for the predictions of a synthetic dataset. A record is a unit of input data that inference can be made on, for example, a single line in CSV data. If MaxRecordCount is 1, the model container expects one record per request. A value of 2 or greater means that the model expects batch requests, which can reduce overhead and speed up the inferencing process. If this parameter is not provided, the explainer will tune the record count per request according to the model container's capacity at runtime.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_MaxRecordCount
-InferenceConfig_ProbabilityAttribute <String>
A JMESPath expression used to extract the probability (or score) from the model container output if the model container is in JSON Lines format.Example: If the model container output of a single request is '{"predicted_label":1,"probability":0.6}', then set ProbabilityAttribute to 'probability'.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_ProbabilityAttribute
-InferenceConfig_ProbabilityIndex <Int32>
A zero-based index used to extract a probability value (score) or list from model container output in CSV format. If this value is not provided, the entire model container output will be treated as a probability value (score) or list.Example for a single class model: If the model container output consists of a string-formatted prediction label followed by its probability: '1,0.6', set ProbabilityIndex to 1 to select the probability value 0.6.Example for a multiclass model: If the model container output consists of a string-formatted prediction label followed by its probability: '"[\'cat\',\'dog\',\'fish\']","[0.1,0.6,0.3]"', set ProbabilityIndex to 1 to select the probability values [0.1,0.6,0.3].
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_InferenceConfig_ProbabilityIndex
-KmsKeyId <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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-NotificationConfig_ErrorTopic <String>
Amazon SNS topic to post a notification to when inference fails. If no topic is provided, no notification is sent on failure.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_NotificationConfig_ErrorTopic
-NotificationConfig_IncludeInferenceResponseIn <String[]>
The Amazon SNS topics where you want the inference response to be included.The inference response is included only if the response size is less than or equal to 128 KB. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_NotificationConfig_IncludeInferenceResponseIn
-NotificationConfig_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.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_NotificationConfig_SuccessTopic
-OutputConfig_KmsKeyId <String>
The Amazon Web Services Key Management Service (Amazon Web Services KMS) key that SageMaker uses to encrypt the asynchronous inference output in Amazon S3.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_KmsKeyId
-OutputConfig_S3FailurePath <String>
The Amazon S3 location to upload failure inference responses to.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_S3FailurePath
-OutputConfig_S3OutputPath <String>
The Amazon S3 location to upload inference responses to.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAsyncInferenceConfig_OutputConfig_S3OutputPath
-ProductionVariant <ProductionVariant[]>
An array of ProductionVariant objects, one for each model that you want to host at this endpoint. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?True
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesProductionVariants
-Select <String>
Use the -Select parameter to control the cmdlet output. The default value is 'EndpointConfigArn'. Specifying -Select '*' will result in the cmdlet returning the whole service response (Amazon.SageMaker.Model.CreateEndpointConfigResponse). Specifying the name of a property of type Amazon.SageMaker.Model.CreateEndpointConfigResponse will result in that property being returned. Specifying -Select '^ParameterName' will result in the cmdlet returning the selected cmdlet parameter value.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-ShadowProductionVariant <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. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesShadowProductionVariants
-ShapBaselineConfig_MimeType <String>
The MIME type of the baseline data. Choose from 'text/csv' or 'application/jsonlines'. Defaults to 'text/csv'.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_ShapBaselineConfig_MimeType
-ShapBaselineConfig_ShapBaseline <String>
The inline SHAP baseline data in string format. ShapBaseline can have one or multiple records to be used as the baseline dataset. The format of the SHAP baseline file should be the same format as the training dataset. For example, if the training dataset is in CSV format and each record contains four features, and all features are numerical, then the format of the baseline data should also share these characteristics. For natural language processing (NLP) of text columns, the baseline value should be the value used to replace the unit of text specified by the Granularity of the TextConfig parameter. The size limit for ShapBasline is 4 KB. Use the ShapBaselineUri parameter if you want to provide more than 4 KB of baseline data.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_ShapBaselineConfig_ShapBaseline
-ShapBaselineConfig_ShapBaselineUri <String>
The uniform resource identifier (URI) of the S3 bucket where the SHAP baseline file is stored. The format of the SHAP baseline file should be the same format as the format of the training dataset. For example, if the training dataset is in CSV format, and each record in the training dataset has four features, and all features are numerical, then the baseline file should also have this same format. Each record should contain only the features. If you are using a virtual private cloud (VPC), the ShapBaselineUri should be accessible to the VPC. For more information about setting up endpoints with Amazon Virtual Private Cloud, see Give SageMaker access to Resources in your Amazon Virtual Private Cloud.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_ShapBaselineConfig_ShapBaselineUri
-ShapConfig_NumberOfSample <Int32>
The number of samples to be used for analysis by the Kernal SHAP algorithm. The number of samples determines the size of the synthetic dataset, which has an impact on latency of explainability requests. For more information, see the Synthetic data of Configure and create an endpoint.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_NumberOfSamples
-ShapConfig_Seed <Int32>
The starting value used to initialize the random number generator in the explainer. Provide a value for this parameter to obtain a deterministic SHAP result.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_Seed
-ShapConfig_UseLogit <Boolean>
A Boolean toggle to indicate if you want to use the logit function (true) or log-odds units (false) for model predictions. Defaults to false.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_UseLogit
-Tag <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. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesTags
-TextConfig_Granularity <ClarifyTextGranularity>
The unit of granularity for the analysis of text features. For example, if the unit is 'token', then each token (like a word in English) of the text is treated as a feature. SHAP values are computed for each unit/feature.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_TextConfig_Granularity
-TextConfig_Language <ClarifyTextLanguage>
Specifies the language of the text features in ISO 639-1 or ISO 639-3 code of a supported language. For a mix of multiple languages, use code 'xx'.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesExplainerConfig_ClarifyExplainerConfig_ShapConfig_TextConfig_Language
-VpcConfig_SecurityGroupId <String[]>
The VPC security group IDs, in the form sg-xxxxxxxx. Specify the security groups for the VPC that is specified in the Subnets field. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesVpcConfig_SecurityGroupIds
-VpcConfig_Subnet <String[]>
The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones. Starting with version 4 of the SDK this property will default to null. If no data for this property is returned from the service the property will also be null. This was changed to improve performance and allow the SDK and caller to distinguish between a property not set or a property being empty to clear out a value. To retain the previous SDK behavior set the AWSConfigs.InitializeCollections static property to true.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesVpcConfig_Subnets

Common Credential and Region Parameters

-AccessKey <String>
The AWS access key for the user account. This can be a temporary access key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAK
-Credential <AWSCredentials>
An AWSCredentials object instance containing access and secret key information, and optionally a token for session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-EndpointUrl <String>
The endpoint to make the call against.Note: This parameter is primarily for internal AWS use and is not required/should not be specified for normal usage. The cmdlets normally determine which endpoint to call based on the region specified to the -Region parameter or set as default in the shell (via Set-DefaultAWSRegion). Only specify this parameter if you must direct the call to a specific custom endpoint.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
-NetworkCredential <PSCredential>
Used with SAML-based authentication when ProfileName references a SAML role profile. Contains the network credentials to be supplied during authentication with the configured identity provider's endpoint. This parameter is not required if the user's default network identity can or should be used during authentication.
Required?False
Position?Named
Accept pipeline input?True (ByValue, ByPropertyName)
-ProfileLocation <String>
Used to specify the name and location of the ini-format credential file (shared with the AWS CLI and other AWS SDKs)If this optional parameter is omitted this cmdlet will search the encrypted credential file used by the AWS SDK for .NET and AWS Toolkit for Visual Studio first. If the profile is not found then the cmdlet will search in the ini-format credential file at the default location: (user's home directory)\.aws\credentials.If this parameter is specified then this cmdlet will only search the ini-format credential file at the location given.As the current folder can vary in a shell or during script execution it is advised that you use specify a fully qualified path instead of a relative path.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesAWSProfilesLocation, ProfilesLocation
-ProfileName <String>
The user-defined name of an AWS credentials or SAML-based role profile containing credential information. The profile is expected to be found in the secure credential file shared with the AWS SDK for .NET and AWS Toolkit for Visual Studio. You can also specify the name of a profile stored in the .ini-format credential file used with the AWS CLI and other AWS SDKs.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesStoredCredentials, AWSProfileName
-Region <Object>
The system name of an AWS region or an AWSRegion instance. This governs the endpoint that will be used when calling service operations. Note that the AWS resources referenced in a call are usually region-specific.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesRegionToCall
-SecretKey <String>
The AWS secret key for the user account. This can be a temporary secret key if the corresponding session token is supplied to the -SessionToken parameter.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesSK, SecretAccessKey
-SessionToken <String>
The session token if the access and secret keys are temporary session-based credentials.
Required?False
Position?Named
Accept pipeline input?True (ByPropertyName)
AliasesST

Outputs

System.String or Amazon.SageMaker.Model.CreateEndpointConfigResponse
This cmdlet returns a System.String object. The service call response (type Amazon.SageMaker.Model.CreateEndpointConfigResponse) can be returned by specifying '-Select *'.
Developer Guide
Service API Reference
AWS Tools for PowerShell User Guide

Supported Version

AWS Tools for PowerShell: 2.x.y.z