AWS Fundamentals Logo
AWS Fundamentals
L1 ConstructAWS::SageMaker::NotebookInstance

CfnNotebookInstance

The `AWS::SageMaker::NotebookInstance` resource creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook. For more information, see [Use Notebook Instances](https://docs.aws.amazon.com/sagemaker/latest/dg/nbi.html) .

Import

import { CfnNotebookInstance } from 'aws-cdk-lib/aws-sagemaker';

Or use the module namespace:

import * as sagemaker from 'aws-cdk-lib/aws-sagemaker';
// sagemaker.CfnNotebookInstance

Properties

Configuration passed to the constructor as CfnNotebookInstanceProps.

instanceTypeRequired
string

The type of ML compute instance to launch for the notebook instance. > Expect some interruption of service if this parameter is changed as CloudFormation stops a notebook instance and starts it up again to update it.

roleArnRequired
string

When you send any requests to AWS resources from the notebook instance, SageMaker AI assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker AI can perform these tasks. The policy must allow the SageMaker AI service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see [SageMaker AI Roles](https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html) . > To be able to pass this role to SageMaker AI, the caller of this API must have the `iam:PassRole` permission.

acceleratorTypesOptional
string[]

A list of Amazon Elastic Inference (EI) instance types to associate with the notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see [Using Elastic Inference in Amazon SageMaker](https://docs.aws.amazon.com/sagemaker/latest/dg/ei.html) . *Valid Values:* `ml.eia1.medium | ml.eia1.large | ml.eia1.xlarge | ml.eia2.medium | ml.eia2.large | ml.eia2.xlarge` .

additionalCodeRepositoriesOptional
string[]

An array of up to three Git repositories associated with the notebook instance. These can be either the names of Git repositories stored as resources in your account, or the URL of Git repositories in [AWS CodeCommit](https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance. For more information, see [Associating Git Repositories with SageMaker AI Notebook Instances](https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html) .

defaultCodeRepositoryOptional
string

The Git repository associated with the notebook instance as its default code repository. This can be either the name of a Git repository stored as a resource in your account, or the URL of a Git repository in [AWS CodeCommit](https://docs.aws.amazon.com/codecommit/latest/userguide/welcome.html) or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository. For more information, see [Associating Git Repositories with SageMaker AI Notebook Instances](https://docs.aws.amazon.com/sagemaker/latest/dg/nbi-git-repo.html) .

directInternetAccessOptional
string

Sets whether SageMaker AI provides internet access to the notebook instance. If you set this to `Disabled` this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker AI training and endpoint services unless you configure a NAT Gateway in your VPC. For more information, see [Notebook Instances Are Internet-Enabled by Default](https://docs.aws.amazon.com/sagemaker/latest/dg/appendix-additional-considerations.html#appendix-notebook-and-internet-access) . You can set the value of this parameter to `Disabled` only if you set a value for the `SubnetId` parameter.

instanceMetadataServiceConfigurationOptional
IResolvable | InstanceMetadataServiceConfigurationProperty

Information on the IMDS configuration of the notebook instance.

kmsKeyIdOptional
string

The Amazon Resource Name (ARN) of a AWS Key Management Service key that SageMaker AI uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see [Enabling and Disabling Keys](https://docs.aws.amazon.com/kms/latest/developerguide/enabling-keys.html) in the *AWS Key Management Service Developer Guide* .

lifecycleConfigNameOptional
string

The name of a lifecycle configuration to associate with the notebook instance. For information about lifecycle configurations, see [Customize a Notebook Instance](https://docs.aws.amazon.com/sagemaker/latest/dg/notebook-lifecycle-config.html) in the *Amazon SageMaker Developer Guide* .

notebookInstanceNameOptional
string

The name of the new notebook instance.

platformIdentifierOptional
string

The platform identifier of the notebook instance runtime environment. The default value is `notebook-al2-v2` .

rootAccessOptional
string

Whether root access is enabled or disabled for users of the notebook instance. The default value is `Enabled` . > Lifecycle configurations need root access to be able to set up a notebook instance. Because of this, lifecycle configurations associated with a notebook instance always run with root access even if you disable root access for users.

securityGroupIdsOptional
string[]

The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.

subnetIdOptional
string

The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.

tagsOptional
CfnTag[]

A list of key-value pairs to apply to this resource. For more information, see [Resource Tag](https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-resource-tags.html) and [Using Cost Allocation Tags](https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what) . You can add tags later by using the `CreateTags` API.

volumeSizeInGbOptional
number

The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. > Expect some interruption of service if this parameter is changed as CloudFormation stops a notebook instance and starts it up again to update it.

CloudFormation Resource

This L1 construct maps directly to the following CloudFormation resource type.

Learn AWS the Practical Way

Our bi-weekly newsletter teaches hands-on AWS fundamentals. No certification fluff - just practical knowledge.

Subscribe to Newsletter