[ aws . sagemaker ]

create-user-profile

Description

Creates a user profile. A user profile represents a single user within a domain, and is the main way to reference a “person” for the purposes of sharing, reporting, and other user-oriented features. This entity is created when a user onboards to Amazon SageMaker Studio. If an administrator invites a person by email or imports them from SSO, a user profile is automatically created. A user profile is the primary holder of settings for an individual user and has a reference to the user’s private Amazon Elastic File System (EFS) home directory.

See also: AWS API Documentation

See ‘aws help’ for descriptions of global parameters.

Synopsis

  create-user-profile
--domain-id <value>
--user-profile-name <value>
[--single-sign-on-user-identifier <value>]
[--single-sign-on-user-value <value>]
[--tags <value>]
[--user-settings <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options

--domain-id (string)

The ID of the associated Domain.

--user-profile-name (string)

A name for the UserProfile. This value is not case sensitive.

--single-sign-on-user-identifier (string)

A specifier for the type of value specified in SingleSignOnUserValue. Currently, the only supported value is “UserName”. If the Domain’s AuthMode is SSO, this field is required. If the Domain’s AuthMode is not SSO, this field cannot be specified.

--single-sign-on-user-value (string)

The username of the associated Amazon Web Services Single Sign-On User for this UserProfile. If the Domain’s AuthMode is SSO, this field is required, and must match a valid username of a user in your directory. If the Domain’s AuthMode is not SSO, this field cannot be specified.

--tags (list)

Each tag consists of a key and an optional value. Tag keys must be unique per resource.

Tags that you specify for the User Profile are also added to all Apps that the User Profile launches.

(structure)

A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags .

For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources . For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy .

Key -> (string)

The tag key. Tag keys must be unique per resource.

Value -> (string)

The tag value.

Shorthand Syntax:

Key=string,Value=string ...

JSON Syntax:

[
  {
    "Key": "string",
    "Value": "string"
  }
  ...
]

--user-settings (structure)

A collection of settings.

ExecutionRole -> (string)

The execution role for the user.

SecurityGroups -> (list)

The security groups for the Amazon Virtual Private Cloud (VPC) that Studio uses for communication.

Optional when the CreateDomain.AppNetworkAccessType parameter is set to PublicInternetOnly .

Required when the CreateDomain.AppNetworkAccessType parameter is set to VpcOnly .

Amazon SageMaker adds a security group to allow NFS traffic from SageMaker Studio. Therefore, the number of security groups that you can specify is one less than the maximum number shown.

(string)

SharingSettings -> (structure)

Specifies options for sharing SageMaker Studio notebooks.

NotebookOutputOption -> (string)

Whether to include the notebook cell output when sharing the notebook. The default is Disabled .

S3OutputPath -> (string)

When NotebookOutputOption is Allowed , the Amazon S3 bucket used to store the shared notebook snapshots.

S3KmsKeyId -> (string)

When NotebookOutputOption is Allowed , the Amazon Web Services Key Management Service (KMS) encryption key ID used to encrypt the notebook cell output in the Amazon S3 bucket.

JupyterServerAppSettings -> (structure)

The Jupyter server’s app settings.

DefaultResourceSpec -> (structure)

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the JupyterServer app.

SageMakerImageArn -> (string)

The ARN of the SageMaker image that the image version belongs to.

SageMakerImageVersionArn -> (string)

The ARN of the image version created on the instance.

InstanceType -> (string)

The instance type that the image version runs on.

LifecycleConfigArn -> (string)

The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.

LifecycleConfigArns -> (list)

The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the JupyterServerApp.

(string)

KernelGatewayAppSettings -> (structure)

The kernel gateway app settings.

DefaultResourceSpec -> (structure)

The default instance type and the Amazon Resource Name (ARN) of the default SageMaker image used by the KernelGateway app.

SageMakerImageArn -> (string)

The ARN of the SageMaker image that the image version belongs to.

SageMakerImageVersionArn -> (string)

The ARN of the image version created on the instance.

InstanceType -> (string)

The instance type that the image version runs on.

LifecycleConfigArn -> (string)

The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.

CustomImages -> (list)

A list of custom SageMaker images that are configured to run as a KernelGateway app.

(structure)

A custom SageMaker image. For more information, see Bring your own SageMaker image .

ImageName -> (string)

The name of the CustomImage. Must be unique to your account.

ImageVersionNumber -> (integer)

The version number of the CustomImage.

AppImageConfigName -> (string)

The name of the AppImageConfig.

LifecycleConfigArns -> (list)

The Amazon Resource Name (ARN) of the Lifecycle Configurations attached to the the user profile or domain.

(string)

TensorBoardAppSettings -> (structure)

The TensorBoard app settings.

DefaultResourceSpec -> (structure)

The default instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.

SageMakerImageArn -> (string)

The ARN of the SageMaker image that the image version belongs to.

SageMakerImageVersionArn -> (string)

The ARN of the image version created on the instance.

InstanceType -> (string)

The instance type that the image version runs on.

LifecycleConfigArn -> (string)

The Amazon Resource Name (ARN) of the Lifecycle Configuration attached to the Resource.

RStudioServerProAppSettings -> (structure)

A collection of settings that configure user interaction with the RStudioServerPro app.

AccessStatus -> (string)

Indicates whether the current user has access to the RStudioServerPro app.

UserGroup -> (string)

The level of permissions that the user has within the RStudioServerPro app. This value defaults to User. The Admin value allows the user access to the RStudio Administrative Dashboard.

RSessionAppSettings -> (structure)

A collection of settings that configure the RSessionGateway app.

JSON Syntax:

{
  "ExecutionRole": "string",
  "SecurityGroups": ["string", ...],
  "SharingSettings": {
    "NotebookOutputOption": "Allowed"|"Disabled",
    "S3OutputPath": "string",
    "S3KmsKeyId": "string"
  },
  "JupyterServerAppSettings": {
    "DefaultResourceSpec": {
      "SageMakerImageArn": "string",
      "SageMakerImageVersionArn": "string",
      "InstanceType": "system"|"ml.t3.micro"|"ml.t3.small"|"ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.8xlarge"|"ml.m5.12xlarge"|"ml.m5.16xlarge"|"ml.m5.24xlarge"|"ml.m5d.large"|"ml.m5d.xlarge"|"ml.m5d.2xlarge"|"ml.m5d.4xlarge"|"ml.m5d.8xlarge"|"ml.m5d.12xlarge"|"ml.m5d.16xlarge"|"ml.m5d.24xlarge"|"ml.c5.large"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.12xlarge"|"ml.c5.18xlarge"|"ml.c5.24xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge",
      "LifecycleConfigArn": "string"
    },
    "LifecycleConfigArns": ["string", ...]
  },
  "KernelGatewayAppSettings": {
    "DefaultResourceSpec": {
      "SageMakerImageArn": "string",
      "SageMakerImageVersionArn": "string",
      "InstanceType": "system"|"ml.t3.micro"|"ml.t3.small"|"ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.8xlarge"|"ml.m5.12xlarge"|"ml.m5.16xlarge"|"ml.m5.24xlarge"|"ml.m5d.large"|"ml.m5d.xlarge"|"ml.m5d.2xlarge"|"ml.m5d.4xlarge"|"ml.m5d.8xlarge"|"ml.m5d.12xlarge"|"ml.m5d.16xlarge"|"ml.m5d.24xlarge"|"ml.c5.large"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.12xlarge"|"ml.c5.18xlarge"|"ml.c5.24xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge",
      "LifecycleConfigArn": "string"
    },
    "CustomImages": [
      {
        "ImageName": "string",
        "ImageVersionNumber": integer,
        "AppImageConfigName": "string"
      }
      ...
    ],
    "LifecycleConfigArns": ["string", ...]
  },
  "TensorBoardAppSettings": {
    "DefaultResourceSpec": {
      "SageMakerImageArn": "string",
      "SageMakerImageVersionArn": "string",
      "InstanceType": "system"|"ml.t3.micro"|"ml.t3.small"|"ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.8xlarge"|"ml.m5.12xlarge"|"ml.m5.16xlarge"|"ml.m5.24xlarge"|"ml.m5d.large"|"ml.m5d.xlarge"|"ml.m5d.2xlarge"|"ml.m5d.4xlarge"|"ml.m5d.8xlarge"|"ml.m5d.12xlarge"|"ml.m5d.16xlarge"|"ml.m5d.24xlarge"|"ml.c5.large"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.12xlarge"|"ml.c5.18xlarge"|"ml.c5.24xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.p3dn.24xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge",
      "LifecycleConfigArn": "string"
    }
  },
  "RStudioServerProAppSettings": {
    "AccessStatus": "ENABLED"|"DISABLED",
    "UserGroup": "R_STUDIO_ADMIN"|"R_STUDIO_USER"
  },
  "RSessionAppSettings": {

  }
}

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See ‘aws help’ for descriptions of global parameters.

Output

UserProfileArn -> (string)

The user profile Amazon Resource Name (ARN).