CreateNotebookInstance - Amazon SageMaker

CreateNotebookInstance

Creates an SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook.

In a CreateNotebookInstance request, specify the type of ML compute instance that you want to run. SageMaker launches the instance, installs common libraries that you can use to explore datasets for model training, and attaches an ML storage volume to the notebook instance.

SageMaker also provides a set of example notebooks. Each notebook demonstrates how to use SageMaker with a specific algorithm or with a machine learning framework.

After receiving the request, SageMaker does the following:

  1. Creates a network interface in the SageMaker VPC.

  2. (Option) If you specified SubnetId, SageMaker creates a network interface in your own VPC, which is inferred from the subnet ID that you provide in the input. When creating this network interface, SageMaker attaches the security group that you specified in the request to the network interface that it creates in your VPC.

  3. Launches an EC2 instance of the type specified in the request in the SageMaker VPC. If you specified SubnetId of your VPC, SageMaker specifies both network interfaces when launching this instance. This enables inbound traffic from your own VPC to the notebook instance, assuming that the security groups allow it.

After creating the notebook instance, SageMaker returns its Amazon Resource Name (ARN). You can't change the name of a notebook instance after you create it.

After SageMaker creates the notebook instance, you can connect to the Jupyter server and work in Jupyter notebooks. For example, you can write code to explore a dataset that you can use for model training, train a model, host models by creating SageMaker endpoints, and validate hosted models.

For more information, see How It Works.

Request Syntax

{ "AcceleratorTypes": [ "string" ], "AdditionalCodeRepositories": [ "string" ], "DefaultCodeRepository": "string", "DirectInternetAccess": "string", "InstanceMetadataServiceConfiguration": { "MinimumInstanceMetadataServiceVersion": "string" }, "InstanceType": "string", "KmsKeyId": "string", "LifecycleConfigName": "string", "NotebookInstanceName": "string", "PlatformIdentifier": "string", "RoleArn": "string", "RootAccess": "string", "SecurityGroupIds": [ "string" ], "SubnetId": "string", "Tags": [ { "Key": "string", "Value": "string" } ], "VolumeSizeInGB": number }

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.

AcceleratorTypes

A list of Elastic Inference (EI) instance types to associate with this notebook instance. Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker.

Type: Array of strings

Valid Values: ml.eia1.medium | ml.eia1.large | ml.eia1.xlarge | ml.eia2.medium | ml.eia2.large | ml.eia2.xlarge

Required: No

AdditionalCodeRepositories

An array of up to three Git repositories to associate 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 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 Notebook Instances.

Type: Array of strings

Array Members: Maximum number of 3 items.

Length Constraints: Minimum length of 1. Maximum length of 1024.

Pattern: ^https://([^/]+)/?(.*)$|^[a-zA-Z0-9](-*[a-zA-Z0-9])*

Required: No

DefaultCodeRepository

A Git repository to associate 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 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 Notebook Instances.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 1024.

Pattern: ^https://([^/]+)/?(.*)$|^[a-zA-Z0-9](-*[a-zA-Z0-9])*

Required: No

DirectInternetAccess

Sets whether SageMaker 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 training and endpoint services unless you configure a NAT Gateway in your VPC.

For more information, see Notebook Instances Are Internet-Enabled by Default. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.

Type: String

Valid Values: Enabled | Disabled

Required: No

InstanceMetadataServiceConfiguration

Information on the IMDS configuration of the notebook instance

Type: InstanceMetadataServiceConfiguration object

Required: No

InstanceType

The type of ML compute instance to launch for the notebook instance.

Type: String

Valid Values: ml.t2.medium | ml.t2.large | ml.t2.xlarge | ml.t2.2xlarge | ml.t3.medium | ml.t3.large | ml.t3.xlarge | ml.t3.2xlarge | ml.m4.xlarge | ml.m4.2xlarge | ml.m4.4xlarge | ml.m4.10xlarge | ml.m4.16xlarge | ml.m5.xlarge | ml.m5.2xlarge | ml.m5.4xlarge | ml.m5.12xlarge | ml.m5.24xlarge | ml.m5d.large | ml.m5d.xlarge | ml.m5d.2xlarge | ml.m5d.4xlarge | ml.m5d.8xlarge | ml.m5d.12xlarge | ml.m5d.16xlarge | ml.m5d.24xlarge | ml.c4.xlarge | ml.c4.2xlarge | ml.c4.4xlarge | ml.c4.8xlarge | ml.c5.xlarge | ml.c5.2xlarge | ml.c5.4xlarge | ml.c5.9xlarge | ml.c5.18xlarge | ml.c5d.xlarge | ml.c5d.2xlarge | ml.c5d.4xlarge | ml.c5d.9xlarge | ml.c5d.18xlarge | ml.p2.xlarge | ml.p2.8xlarge | ml.p2.16xlarge | ml.p3.2xlarge | ml.p3.8xlarge | ml.p3.16xlarge | ml.p3dn.24xlarge | ml.g4dn.xlarge | ml.g4dn.2xlarge | ml.g4dn.4xlarge | ml.g4dn.8xlarge | ml.g4dn.12xlarge | ml.g4dn.16xlarge | ml.r5.large | ml.r5.xlarge | ml.r5.2xlarge | ml.r5.4xlarge | ml.r5.8xlarge | ml.r5.12xlarge | ml.r5.16xlarge | ml.r5.24xlarge | ml.g5.xlarge | ml.g5.2xlarge | ml.g5.4xlarge | ml.g5.8xlarge | ml.g5.16xlarge | ml.g5.12xlarge | ml.g5.24xlarge | ml.g5.48xlarge | ml.inf1.xlarge | ml.inf1.2xlarge | ml.inf1.6xlarge | ml.inf1.24xlarge | ml.p4d.24xlarge | ml.p4de.24xlarge | ml.p5.48xlarge | ml.m6i.large | ml.m6i.xlarge | ml.m6i.2xlarge | ml.m6i.4xlarge | ml.m6i.8xlarge | ml.m6i.12xlarge | ml.m6i.16xlarge | ml.m6i.24xlarge | ml.m6i.32xlarge | ml.m7i.large | ml.m7i.xlarge | ml.m7i.2xlarge | ml.m7i.4xlarge | ml.m7i.8xlarge | ml.m7i.12xlarge | ml.m7i.16xlarge | ml.m7i.24xlarge | ml.m7i.48xlarge | ml.c6i.large | ml.c6i.xlarge | ml.c6i.2xlarge | ml.c6i.4xlarge | ml.c6i.8xlarge | ml.c6i.12xlarge | ml.c6i.16xlarge | ml.c6i.24xlarge | ml.c6i.32xlarge | ml.c7i.large | ml.c7i.xlarge | ml.c7i.2xlarge | ml.c7i.4xlarge | ml.c7i.8xlarge | ml.c7i.12xlarge | ml.c7i.16xlarge | ml.c7i.24xlarge | ml.c7i.48xlarge | ml.r6i.large | ml.r6i.xlarge | ml.r6i.2xlarge | ml.r6i.4xlarge | ml.r6i.8xlarge | ml.r6i.12xlarge | ml.r6i.16xlarge | ml.r6i.24xlarge | ml.r6i.32xlarge | ml.r7i.large | ml.r7i.xlarge | ml.r7i.2xlarge | ml.r7i.4xlarge | ml.r7i.8xlarge | ml.r7i.12xlarge | ml.r7i.16xlarge | ml.r7i.24xlarge | ml.r7i.48xlarge | ml.m6id.large | ml.m6id.xlarge | ml.m6id.2xlarge | ml.m6id.4xlarge | ml.m6id.8xlarge | ml.m6id.12xlarge | ml.m6id.16xlarge | ml.m6id.24xlarge | ml.m6id.32xlarge | ml.c6id.large | ml.c6id.xlarge | ml.c6id.2xlarge | ml.c6id.4xlarge | ml.c6id.8xlarge | ml.c6id.12xlarge | ml.c6id.16xlarge | ml.c6id.24xlarge | ml.c6id.32xlarge | ml.r6id.large | ml.r6id.xlarge | ml.r6id.2xlarge | ml.r6id.4xlarge | ml.r6id.8xlarge | ml.r6id.12xlarge | ml.r6id.16xlarge | ml.r6id.24xlarge | ml.r6id.32xlarge

Required: Yes

KmsKeyId

The Amazon Resource Name (ARN) of a AWS Key Management Service key that SageMaker 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 in the AWS Key Management Service Developer Guide.

Type: String

Length Constraints: Maximum length of 2048.

Pattern: .*

Required: No

LifecycleConfigName

The name of a lifecycle configuration to associate with the notebook instance. For information about lifestyle configurations, see Step 2.1: (Optional) Customize a Notebook Instance.

Type: String

Length Constraints: Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9])*

Required: No

NotebookInstanceName

The name of the new notebook instance.

Type: String

Length Constraints: Maximum length of 63.

Pattern: ^[a-zA-Z0-9](-*[a-zA-Z0-9])*

Required: Yes

PlatformIdentifier

The platform identifier of the notebook instance runtime environment.

Type: String

Length Constraints: Maximum length of 15.

Pattern: ^(notebook-al1-v1|notebook-al2-v1|notebook-al2-v2)$

Required: No

RoleArn

When you send any requests to AWS resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles.

Note

To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.

Type: String

Length Constraints: Minimum length of 20. Maximum length of 2048.

Pattern: ^arn:aws[a-z\-]*:iam::\d{12}:role/?[a-zA-Z_0-9+=,.@\-_/]+$

Required: Yes

RootAccess

Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled.

Note

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.

Type: String

Valid Values: Enabled | Disabled

Required: No

SecurityGroupIds

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

Type: Array of strings

Array Members: Maximum number of 5 items.

Length Constraints: Maximum length of 32.

Pattern: [-0-9a-zA-Z]+

Required: No

SubnetId

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

Type: String

Length Constraints: Maximum length of 32.

Pattern: [-0-9a-zA-Z]+

Required: No

Tags

An array of key-value pairs. You can use tags to categorize your AWS resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging AWS Resources.

Type: Array of Tag objects

Array Members: Minimum number of 0 items. Maximum number of 50 items.

Required: No

VolumeSizeInGB

The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.

Type: Integer

Valid Range: Minimum value of 5. Maximum value of 16384.

Required: No

Response Syntax

{ "NotebookInstanceArn": "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.

NotebookInstanceArn

The Amazon Resource Name (ARN) of the notebook instance.

Type: String

Length Constraints: Maximum length of 256.

Errors

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

ResourceLimitExceeded

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

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: