create-app¶
Description¶
Creates a running App for the specified UserProfile. Supported Apps are JupyterServer and KernelGateway. This operation is automatically invoked by Amazon SageMaker Studio upon access to the associated Domain, and when new kernel configurations are selected by the user. A user may have multiple Apps active simultaneously.
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
Synopsis¶
create-app
--domain-id <value>
--user-profile-name <value>
--app-type <value>
--app-name <value>
[--tags <value>]
[--resource-spec <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--cli-auto-prompt <value>]
Options¶
--domain-id (string)
The domain ID.
--user-profile-name (string)
The user profile name.
--app-type (string)
The type of app.
Possible values:
JupyterServer
KernelGateway
TensorBoard
--app-name (string)
The name of the app.
--tags (list)
Each tag consists of a key and an optional value. Tag keys must be unique per resource.
(structure)
Describes a tag.
Key -> (string)
The tag key.
Value -> (string)
The tag value.
Shorthand Syntax:
Key=string,Value=string ...
JSON Syntax:
[
{
"Key": "string",
"Value": "string"
}
...
]
--resource-spec (structure)
The instance type and the Amazon Resource Name (ARN) of the SageMaker image created on the instance.
SageMakerImageArn -> (string)
The Amazon Resource Name (ARN) of the SageMaker image created on the instance.
InstanceType -> (string)
The instance type.
Shorthand Syntax:
SageMakerImageArn=string,InstanceType=string
JSON Syntax:
{
"SageMakerImageArn": "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.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.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge"
}
--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.
--cli-auto-prompt (boolean)
Automatically prompt for CLI input parameters.
See ‘aws help’ for descriptions of global parameters.