CreateStudioLifecycleConfig
Creates a new Amazon SageMaker AI Studio Lifecycle Configuration.
Request Syntax
{
"StudioLifecycleConfigAppType": "string",
"StudioLifecycleConfigContent": "string",
"StudioLifecycleConfigName": "string",
"Tags": [
{
"Key": "string",
"Value": "string"
}
]
}Request Parameters
For information about the parameters that are common to all actions, see Common Parameters.
The request accepts the following data in JSON format.
- StudioLifecycleConfigAppType
-
The App type that the Lifecycle Configuration is attached to.
Type: String
Valid Values:
JupyterServer | KernelGateway | CodeEditor | JupyterLabRequired: Yes
- StudioLifecycleConfigContent
-
The content of your Amazon SageMaker AI Studio Lifecycle Configuration script. This content must be base64 encoded.
Type: String
Length Constraints: Minimum length of 1. Maximum length of 16384.
Pattern:
[\S\s]+Required: Yes
- StudioLifecycleConfigName
-
The name of the Amazon SageMaker AI Studio Lifecycle Configuration to create.
Type: String
Length Constraints: Maximum length of 63.
Pattern:
^[a-zA-Z0-9](-*[a-zA-Z0-9]){0,62}Required: Yes
- Tags
-
Tags to be associated with the Lifecycle Configuration. Each tag consists of a key and an optional value. Tag keys must be unique per resource. Tags are searchable using the Search API.
Type: Array of Tag objects
Array Members: Minimum number of 0 items. Maximum number of 50 items.
Required: No
Response Syntax
{
"StudioLifecycleConfigArn": "string"
}Response Elements
If the action is successful, the service sends back an HTTP 200 response.
The following data is returned in JSON format by the service.
- StudioLifecycleConfigArn
-
The ARN of your created Lifecycle Configuration.
Type: String
Length Constraints: Maximum length of 256.
Pattern:
^(arn:aws[a-z\-]*:sagemaker:[a-z0-9\-]*:[0-9]{12}:studio-lifecycle-config/.*|None)$
Errors
For information about the errors that are common to all actions, see Common Errors.
- ResourceInUse
-
Resource being accessed is in use.
HTTP Status Code: 400
See Also
For more information about using this API in one of the language-specific AWS SDKs, see the following:
