StartNotebookInstanceCommand

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

Example Syntax

Use a bare-bones client and the command you need to make an API call.

import { SageMakerClient, StartNotebookInstanceCommand } from "@aws-sdk/client-sagemaker"; // ES Modules import
// const { SageMakerClient, StartNotebookInstanceCommand } = require("@aws-sdk/client-sagemaker"); // CommonJS import
const client = new SageMakerClient(config);
const input = { // StartNotebookInstanceInput
  NotebookInstanceName: "STRING_VALUE", // required
};
const command = new StartNotebookInstanceCommand(input);
const response = await client.send(command);
// {};

StartNotebookInstanceCommand Input

Parameter
Type
Description
NotebookInstanceName
Required
string | undefined

The name of the notebook instance to start.

StartNotebookInstanceCommand Output

Parameter
Type
Description
$metadata
Required
ResponseMetadata
Metadata pertaining to this request.

Throws

Name
Fault
Details
ResourceLimitExceeded
client

You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created.

SageMakerServiceException
Base exception class for all service exceptions from SageMaker service.