1. Registry
  2. Packages
  3. AWS Cloud Control
  4. API Docs
  5. sagemaker
  6. NotebookInstance

We recommend new projects start with resources from the AWS provider.

Viewing docs for AWS Cloud Control v1.81.0
published on Monday, Sep 28, 2026 by Pulumi
aws-native logo aws-native logo

We recommend new projects start with resources from the AWS provider.

Viewing docs for AWS Cloud Control v1.81.0
published on Monday, Sep 28, 2026 by Pulumi

    Resource Type definition for AWS::SageMaker::NotebookInstance

    Example Usage

    Example

    using System;
    using System.Collections.Generic;
    using System.Linq;
    using Pulumi;
    using AwsNative = Pulumi.AwsNative;
    
    return await Deployment.RunAsync(() => 
    {
        var basicNotebookInstanceLifecycleConfig = new AwsNative.SageMaker.NotebookInstanceLifecycleConfig("basicNotebookInstanceLifecycleConfig", new()
        {
            OnStart = new[]
            {
                new AwsNative.SageMaker.Inputs.NotebookInstanceLifecycleConfigNotebookInstanceLifecycleHookArgs
                {
                    Content = Convert.ToBase64String(System.Text.Encoding.UTF8.GetBytes("echo 'hello'")),
                },
            },
        });
    
        var executionRole = new AwsNative.Iam.Role("executionRole", new()
        {
            AssumeRolePolicyDocument = new Dictionary<string, object?>
            {
                ["version"] = "2012-10-17",
                ["statement"] = new[]
                {
                    new Dictionary<string, object?>
                    {
                        ["effect"] = "Allow",
                        ["principal"] = new Dictionary<string, object?>
                        {
                            ["service"] = new[]
                            {
                                "sagemaker.amazonaws.com",
                            },
                        },
                        ["action"] = new[]
                        {
                            "sts:AssumeRole",
                        },
                    },
                },
            },
            Path = "/",
            Policies = new[]
            {
                new AwsNative.Iam.Inputs.RolePolicyArgs
                {
                    PolicyName = "root",
                    PolicyDocument = new Dictionary<string, object?>
                    {
                        ["version"] = "2012-10-17",
                        ["statement"] = new[]
                        {
                            new Dictionary<string, object?>
                            {
                                ["effect"] = "Allow",
                                ["action"] = "*",
                                ["resource"] = "*",
                            },
                        },
                    },
                },
            },
        });
    
        var basicNotebookInstance = new AwsNative.SageMaker.NotebookInstance("basicNotebookInstance", new()
        {
            InstanceType = "ml.t2.medium",
            RoleArn = executionRole.Arn,
            LifecycleConfigName = basicNotebookInstanceLifecycleConfig.NotebookInstanceLifecycleConfigName,
        });
    
        return new Dictionary<string, object?>
        {
            ["basicNotebookInstanceId"] = basicNotebookInstance.Id,
            ["basicNotebookInstanceLifecycleConfigId"] = basicNotebookInstanceLifecycleConfig.Id,
        };
    });
    
    package main
    
    import (
    	"encoding/base64"
    
    	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/iam"
    	"github.com/pulumi/pulumi-aws-native/sdk/go/aws/sagemaker"
    	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
    )
    
    func main() {
    	pulumi.Run(func(ctx *pulumi.Context) error {
    		basicNotebookInstanceLifecycleConfig, err := sagemaker.NewNotebookInstanceLifecycleConfig(ctx, "basicNotebookInstanceLifecycleConfig", &sagemaker.NotebookInstanceLifecycleConfigArgs{
    			OnStart: sagemaker.NotebookInstanceLifecycleConfigNotebookInstanceLifecycleHookArray{
    				&sagemaker.NotebookInstanceLifecycleConfigNotebookInstanceLifecycleHookArgs{
    					Content: pulumi.String(base64.StdEncoding.EncodeToString([]byte("echo 'hello'"))),
    				},
    			},
    		})
    		if err != nil {
    			return err
    		}
    		executionRole, err := iam.NewRole(ctx, "executionRole", &iam.RoleArgs{
    			AssumeRolePolicyDocument: pulumi.Any(map[string]interface{}{
    				"version": "2012-10-17",
    				"statement": []map[string]interface{}{
    					map[string]interface{}{
    						"effect": "Allow",
    						"principal": map[string][]string{
    							"service": []string{
    								"sagemaker.amazonaws.com",
    							},
    						},
    						"action": []string{
    							"sts:AssumeRole",
    						},
    					},
    				},
    			}),
    			Path: pulumi.String("/"),
    			Policies: iam.RolePolicyTypeArray{
    				&iam.RolePolicyTypeArgs{
    					PolicyName: pulumi.String("root"),
    					PolicyDocument: pulumi.Any(map[string]interface{}{
    						"version": "2012-10-17",
    						"statement": []map[string]string{
    							{
    								"effect":   "Allow",
    								"action":   "*",
    								"resource": "*",
    							},
    						},
    					}),
    				},
    			},
    		})
    		if err != nil {
    			return err
    		}
    		basicNotebookInstance, err := sagemaker.NewNotebookInstance(ctx, "basicNotebookInstance", &sagemaker.NotebookInstanceArgs{
    			InstanceType:        pulumi.String("ml.t2.medium"),
    			RoleArn:             executionRole.Arn,
    			LifecycleConfigName: basicNotebookInstanceLifecycleConfig.NotebookInstanceLifecycleConfigName,
    		})
    		if err != nil {
    			return err
    		}
    		ctx.Export("basicNotebookInstanceId", basicNotebookInstance.ID())
    		ctx.Export("basicNotebookInstanceLifecycleConfigId", basicNotebookInstanceLifecycleConfig.ID())
    		return nil
    	})
    }
    

    Example coming soon!

    Example coming soon!

    import * as pulumi from "@pulumi/pulumi";
    import * as aws_native from "@pulumi/aws-native";
    
    const basicNotebookInstanceLifecycleConfig = new aws_native.sagemaker.NotebookInstanceLifecycleConfig("basicNotebookInstanceLifecycleConfig", {onStart: [{
        content: Buffer.from("echo 'hello'").toString("base64"),
    }]});
    const executionRole = new aws_native.iam.Role("executionRole", {
        assumeRolePolicyDocument: {
            version: "2012-10-17",
            statement: [{
                effect: "Allow",
                principal: {
                    service: ["sagemaker.amazonaws.com"],
                },
                action: ["sts:AssumeRole"],
            }],
        },
        path: "/",
        policies: [{
            policyName: "root",
            policyDocument: {
                version: "2012-10-17",
                statement: [{
                    effect: "Allow",
                    action: "*",
                    resource: "*",
                }],
            },
        }],
    });
    const basicNotebookInstance = new aws_native.sagemaker.NotebookInstance("basicNotebookInstance", {
        instanceType: "ml.t2.medium",
        roleArn: executionRole.arn,
        lifecycleConfigName: basicNotebookInstanceLifecycleConfig.notebookInstanceLifecycleConfigName,
    });
    export const basicNotebookInstanceId = basicNotebookInstance.id;
    export const basicNotebookInstanceLifecycleConfigId = basicNotebookInstanceLifecycleConfig.id;
    
    import pulumi
    import base64
    import pulumi_aws_native as aws_native
    
    basic_notebook_instance_lifecycle_config = aws_native.sagemaker.NotebookInstanceLifecycleConfig("basicNotebookInstanceLifecycleConfig", on_start=[{
        "content": base64.b64encode("echo 'hello'".encode()).decode(),
    }])
    execution_role = aws_native.iam.Role("executionRole",
        assume_role_policy_document={
            "version": "2012-10-17",
            "statement": [{
                "effect": "Allow",
                "principal": {
                    "service": ["sagemaker.amazonaws.com"],
                },
                "action": ["sts:AssumeRole"],
            }],
        },
        path="/",
        policies=[{
            "policy_name": "root",
            "policy_document": {
                "version": "2012-10-17",
                "statement": [{
                    "effect": "Allow",
                    "action": "*",
                    "resource": "*",
                }],
            },
        }])
    basic_notebook_instance = aws_native.sagemaker.NotebookInstance("basicNotebookInstance",
        instance_type="ml.t2.medium",
        role_arn=execution_role.arn,
        lifecycle_config_name=basic_notebook_instance_lifecycle_config.notebook_instance_lifecycle_config_name)
    pulumi.export("basicNotebookInstanceId", basic_notebook_instance.id)
    pulumi.export("basicNotebookInstanceLifecycleConfigId", basic_notebook_instance_lifecycle_config.id)
    

    Example coming soon!

    Create NotebookInstance Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new NotebookInstance(name: string, args: NotebookInstanceArgs, opts?: CustomResourceOptions);
    @overload
    def NotebookInstance(resource_name: str,
                         args: NotebookInstanceArgs,
                         opts: Optional[ResourceOptions] = None)
    
    @overload
    def NotebookInstance(resource_name: str,
                         opts: Optional[ResourceOptions] = None,
                         instance_type: Optional[str] = None,
                         role_arn: Optional[str] = None,
                         notebook_instance_name: Optional[str] = None,
                         platform_identifier: Optional[str] = None,
                         instance_metadata_service_configuration: Optional[NotebookInstanceInstanceMetadataServiceConfigurationArgs] = None,
                         default_code_repository: Optional[str] = None,
                         kms_key_id: Optional[str] = None,
                         lifecycle_config_name: Optional[str] = None,
                         accelerator_types: Optional[Sequence[str]] = None,
                         direct_internet_access: Optional[str] = None,
                         additional_code_repositories: Optional[Sequence[str]] = None,
                         root_access: Optional[str] = None,
                         security_group_ids: Optional[Sequence[str]] = None,
                         subnet_id: Optional[str] = None,
                         tags: Optional[Sequence[_root_inputs.TagArgs]] = None,
                         volume_size_in_gb: Optional[int] = None)
    func NewNotebookInstance(ctx *Context, name string, args NotebookInstanceArgs, opts ...ResourceOption) (*NotebookInstance, error)
    public NotebookInstance(string name, NotebookInstanceArgs args, CustomResourceOptions? opts = null)
    public NotebookInstance(String name, NotebookInstanceArgs args)
    public NotebookInstance(String name, NotebookInstanceArgs args, CustomResourceOptions options)
    
    type: aws-native:sagemaker:NotebookInstance
    properties: # The arguments to resource properties.
    options: # Bag of options to control resource's behavior.
    
    
    resource "aws-native_sagemaker_notebook_instance" "name" {
        # resource properties
    }

    Parameters

    name string
    The unique name of the resource.
    args NotebookInstanceArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args NotebookInstanceArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args NotebookInstanceArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args NotebookInstanceArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args NotebookInstanceArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    NotebookInstance Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The NotebookInstance resource accepts the following input properties:

    InstanceType 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.
    RoleArn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    AcceleratorTypes List<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.
    AdditionalCodeRepositories List<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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    DefaultCodeRepository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    DirectInternetAccess 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    InstanceMetadataServiceConfiguration Pulumi.AwsNative.SageMaker.Inputs.NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance.
    KmsKeyId 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.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    NotebookInstanceName string
    The name of the new notebook instance.
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    RootAccess 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.
    SecurityGroupIds List<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.
    SubnetId string
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    Tags List<Pulumi.AwsNative.Inputs.Tag>
    A list of key-value pairs to apply to this resource.
    VolumeSizeInGb int
    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.
    InstanceType 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.
    RoleArn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    AcceleratorTypes []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.
    AdditionalCodeRepositories []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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    DefaultCodeRepository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    DirectInternetAccess 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    InstanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance.
    KmsKeyId 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.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    NotebookInstanceName string
    The name of the new notebook instance.
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    RootAccess 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.
    SecurityGroupIds []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.
    SubnetId string
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    Tags TagArgs
    A list of key-value pairs to apply to this resource.
    VolumeSizeInGb int
    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.
    instance_type 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.
    role_arn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    accelerator_types list(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.
    additional_code_repositories list(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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    default_code_repository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    direct_internet_access 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    instance_metadata_service_configuration object
    Information on the IMDS configuration of the notebook instance.
    kms_key_id 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.
    lifecycle_config_name string
    The name of a lifecycle configuration to associate with the notebook instance.
    notebook_instance_name string
    The name of the new notebook instance.
    platform_identifier string
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    root_access 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.
    security_group_ids list(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.
    subnet_id string
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    tags list(object)
    A list of key-value pairs to apply to this resource.
    volume_size_in_gb 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.
    instanceType 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.
    roleArn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    acceleratorTypes List<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.
    additionalCodeRepositories List<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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    defaultCodeRepository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    directInternetAccess 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance.
    kmsKeyId 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.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    notebookInstanceName String
    The name of the new notebook instance.
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    rootAccess 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.
    securityGroupIds List<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.
    subnetId String
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    tags List<Tag>
    A list of key-value pairs to apply to this resource.
    volumeSizeInGb Integer
    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.
    instanceType 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.
    roleArn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    acceleratorTypes 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.
    additionalCodeRepositories 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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    defaultCodeRepository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    directInternetAccess 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance.
    kmsKeyId 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.
    lifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    notebookInstanceName string
    The name of the new notebook instance.
    platformIdentifier string
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    rootAccess 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.
    securityGroupIds 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.
    subnetId string
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    tags Tag[]
    A list of key-value pairs to apply to this resource.
    volumeSizeInGb 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.
    instance_type str
    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.
    role_arn str
    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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    accelerator_types Sequence[str]
    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.
    additional_code_repositories Sequence[str]
    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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    default_code_repository str
    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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    direct_internet_access str
    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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    instance_metadata_service_configuration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance.
    kms_key_id str
    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.
    lifecycle_config_name str
    The name of a lifecycle configuration to associate with the notebook instance.
    notebook_instance_name str
    The name of the new notebook instance.
    platform_identifier str
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    root_access str
    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.
    security_group_ids Sequence[str]
    The VPC security group IDs, in the form sg-xxxxxxxx. The security groups must be for the same VPC as specified in the subnet.
    subnet_id str
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    tags Sequence[TagArgs]
    A list of key-value pairs to apply to this resource.
    volume_size_in_gb int
    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.
    instanceType 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.
    roleArn 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. To be able to pass this role to SageMaker AI, the caller of this API must have the iam:PassRole permission.
    acceleratorTypes List<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.
    additionalCodeRepositories List<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 or in any other Git repository. These repositories are cloned at the same level as the default repository of your notebook instance.
    defaultCodeRepository 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 or in any other Git repository. When you open a notebook instance, it opens in the directory that contains this repository.
    directInternetAccess 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. You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
    instanceMetadataServiceConfiguration Property Map
    Information on the IMDS configuration of the notebook instance.
    kmsKeyId 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.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    notebookInstanceName String
    The name of the new notebook instance.
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. The default value is notebook-al2023-v1.
    rootAccess 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.
    securityGroupIds List<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.
    subnetId String
    The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
    tags List<Property Map>
    A list of key-value pairs to apply to this resource.
    volumeSizeInGb 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.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the NotebookInstance resource produces the following output properties:

    Id string
    The provider-assigned unique ID for this managed resource.
    NotebookInstanceArn string
    The Amazon Resource Name (ARN) of the notebook instance.
    Id string
    The provider-assigned unique ID for this managed resource.
    NotebookInstanceArn string
    The Amazon Resource Name (ARN) of the notebook instance.
    id string
    The provider-assigned unique ID for this managed resource.
    notebook_instance_arn string
    The Amazon Resource Name (ARN) of the notebook instance.
    id String
    The provider-assigned unique ID for this managed resource.
    notebookInstanceArn String
    The Amazon Resource Name (ARN) of the notebook instance.
    id string
    The provider-assigned unique ID for this managed resource.
    notebookInstanceArn string
    The Amazon Resource Name (ARN) of the notebook instance.
    id str
    The provider-assigned unique ID for this managed resource.
    notebook_instance_arn str
    The Amazon Resource Name (ARN) of the notebook instance.
    id String
    The provider-assigned unique ID for this managed resource.
    notebookInstanceArn String
    The Amazon Resource Name (ARN) of the notebook instance.

    Supporting Types

    NotebookInstanceInstanceMetadataServiceConfiguration, NotebookInstanceInstanceMetadataServiceConfigurationArgs

    Information on the IMDS configuration of the notebook instance
    MinimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    MinimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    minimum_instance_metadata_service_version string
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    minimumInstanceMetadataServiceVersion String
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    minimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    minimum_instance_metadata_service_version str
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.
    minimumInstanceMetadataServiceVersion String
    Indicates the minimum IMDS version that the notebook instance supports. When passed as part of CreateNotebookInstance, if no value is selected, then it defaults to IMDSv1. This means that both IMDSv1 and IMDSv2 are supported. If passed as part of UpdateNotebookInstance, there is no default.

    Tag, TagArgs

    A set of tags to apply to the resource.
    Key string
    The key name of the tag
    Value string
    The value of the tag
    Key string
    The key name of the tag
    Value string
    The value of the tag
    key string
    The key name of the tag
    value string
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag
    key string
    The key name of the tag
    value string
    The value of the tag
    key str
    The key name of the tag
    value str
    The value of the tag
    key String
    The key name of the tag
    value String
    The value of the tag

    Package Details

    Repository
    AWS Native pulumi/pulumi-aws-native
    License
    Apache-2.0
    aws-native logo aws-native logo

    We recommend new projects start with resources from the AWS provider.

    Viewing docs for AWS Cloud Control v1.81.0
    published on Monday, Sep 28, 2026 by Pulumi

      Try Pulumi Cloud free.
      Your team will thank you.

      Start free trial