[ aws . sagemaker ]

describe-user-profile

Description

Describes a user profile. For more information, see CreateUserProfile .

See also: AWS API Documentation

Synopsis

  describe-user-profile
--domain-id <value>
--user-profile-name <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--domain-id (string)

The domain ID.

--user-profile-name (string)

The user profile name. This value is not case sensitive.

--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. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination.

--output (string)

The formatting style for command output.

  • json

  • text

  • table

  • yaml

  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on

  • off

  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64

  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

DomainId -> (string)

The ID of the domain that contains the profile.

UserProfileArn -> (string)

The user profile Amazon Resource Name (ARN).

UserProfileName -> (string)

The user profile name.

HomeEfsFileSystemUid -> (string)

The ID of the user’s profile in the Amazon Elastic File System (EFS) volume.

Status -> (string)

The status.

LastModifiedTime -> (timestamp)

The last modified time.

CreationTime -> (timestamp)

The creation time.

FailureReason -> (string)

The failure reason.

SingleSignOnUserIdentifier -> (string)

The IAM Identity Center user identifier.

SingleSignOnUserValue -> (string)

The IAM Identity Center user value.

UserSettings -> (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. If you use the LifecycleConfigArns parameter, then this parameter is also required.

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.

Note

JupyterServer apps only support the system value.

For KernelGateway apps , the system value is translated to ml.t3.medium . KernelGateway apps also support all other values for available instance types.

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. If you use this parameter, the DefaultResourceSpec parameter is also required.

Note

To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.

(string)

CodeRepositories -> (list)

A list of Git repositories that SageMaker automatically displays to users for cloning in the JupyterServer application.

(structure)

A Git repository that SageMaker automatically displays to users for cloning in the JupyterServer application.

RepositoryUrl -> (string)

The URL of the Git repository.

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.

Note

The Amazon SageMaker Studio UI does not use the default instance type value set here. The default instance type set here is used when Apps are created using the Amazon Web Services Command Line Interface or Amazon Web Services CloudFormation and the instance type parameter value is not passed.

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.

Note

JupyterServer apps only support the system value.

For KernelGateway apps , the system value is translated to ml.t3.medium . KernelGateway apps also support all other values for available instance types.

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.

Note

To remove a Lifecycle Config, you must set LifecycleConfigArns to an empty list.

(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.

Note

JupyterServer apps only support the system value.

For KernelGateway apps , the system value is translated to ml.t3.medium . KernelGateway apps also support all other values for available instance types.

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.

DefaultResourceSpec -> (structure)

Specifies the ARN’s of a SageMaker image and SageMaker image version, and the instance type that the version runs on.

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.

Note

JupyterServer apps only support the system value.

For KernelGateway apps , the system value is translated to ml.t3.medium . KernelGateway apps also support all other values for available instance types.

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 RSession 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.

CanvasAppSettings -> (structure)

The Canvas app settings.

TimeSeriesForecastingSettings -> (structure)

Time series forecast settings for the Canvas app.

Status -> (string)

Describes whether time series forecasting is enabled or disabled in the Canvas app.

AmazonForecastRoleArn -> (string)

The IAM role that Canvas passes to Amazon Forecast for time series forecasting. By default, Canvas uses the execution role specified in the UserProfile that launches the Canvas app. If an execution role is not specified in the UserProfile , Canvas uses the execution role specified in the Domain that owns the UserProfile . To allow time series forecasting, this IAM role should have the AmazonSageMakerCanvasForecastAccess policy attached and forecast.amazonaws.com added in the trust relationship as a service principal.