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SPDX-License-Identifier: CC-BY-SA-4.0

Launches an ML compute instance with the latest version of the libraries and attaches your ML storage volume. After configuring the notebook instance, Amazon SageMaker sets the notebook instance status to InService. A notebook instance’s status must be InService before you can connect to your Jupyter notebook.

{
   "[NotebookInstanceName](#SageMaker-StartNotebookInstance-request-NotebookInstanceName)": "string"
}

For information about the parameters that are common to all actions, see Common Parameters.

The request accepts the following data in JSON format.

** NotebookInstanceName ** The name of the notebook instance to start.
Type: String
Length Constraints: Maximum length of 63.
Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9])*
Required: Yes

If the action is successful, the service sends back an HTTP 200 response with an empty HTTP body.

For information about the errors that are common to all actions, see Common Errors.

ResourceLimitExceeded
You have exceeded an Amazon SageMaker resource limit. For example, you might have too many training jobs created.
HTTP Status Code: 400

For more information about using this API in one of the language-specific AWS SDKs, see the following: + AWS Command Line Interface + AWS SDK for .NET + AWS SDK for C++ + AWS SDK for Go + AWS SDK for Go - Pilot + AWS SDK for Java + AWS SDK for JavaScript + AWS SDK for PHP V3 + AWS SDK for Python + AWS SDK for Ruby V2