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AWS v6.73.0 published on Wednesday, Mar 19, 2025 by Pulumi
pulumi/pulumi-aws

aws.sagemaker.NotebookInstance

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AWS v6.73.0 published on Wednesday, Mar 19, 2025 by Pulumi
pulumi/pulumi-aws

    Provides a SageMaker AI Notebook Instance resource.

    Example Usage

    Basic usage

    import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const ni = new aws.sagemaker.NotebookInstance("ni", {
    name: "my-notebook-instance",
    roleArn: role.arn,
    instanceType: "ml.t2.medium",
    tags: {
        Name: "foo",
    },
});

    import pulumi
import pulumi_aws as aws

ni = aws.sagemaker.NotebookInstance("ni",
    name="my-notebook-instance",
    role_arn=role["arn"],
    instance_type="ml.t2.medium",
    tags={
        "Name": "foo",
    })

    package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := sagemaker.NewNotebookInstance(ctx, "ni", &sagemaker.NotebookInstanceArgs{
			Name:         pulumi.String("my-notebook-instance"),
			RoleArn:      pulumi.Any(role.Arn),
			InstanceType: pulumi.String("ml.t2.medium"),
			Tags: pulumi.StringMap{
				"Name": pulumi.String("foo"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var ni = new Aws.Sagemaker.NotebookInstance("ni", new()
    {
        Name = "my-notebook-instance",
        RoleArn = role.Arn,
        InstanceType = "ml.t2.medium",
        Tags = 
        {
            { "Name", "foo" },
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.NotebookInstance;
import com.pulumi.aws.sagemaker.NotebookInstanceArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var ni = new NotebookInstance("ni", NotebookInstanceArgs.builder()
            .name("my-notebook-instance")
            .roleArn(role.arn())
            .instanceType("ml.t2.medium")
            .tags(Map.of("Name", "foo"))
            .build());

    }
}

    resources:
  ni:
    type: aws:sagemaker:NotebookInstance
    properties:
      name: my-notebook-instance
      roleArn: ${role.arn}
      instanceType: ml.t2.medium
      tags:
        Name: foo

    Code repository usage

    import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const example = new aws.sagemaker.CodeRepository("example", {
    codeRepositoryName: "my-notebook-instance-code-repo",
    gitConfig: {
        repositoryUrl: "https://github.com/github/docs.git",
    },
});
const ni = new aws.sagemaker.NotebookInstance("ni", {
    name: "my-notebook-instance",
    roleArn: role.arn,
    instanceType: "ml.t2.medium",
    defaultCodeRepository: example.codeRepositoryName,
    tags: {
        Name: "foo",
    },
});

    import pulumi
import pulumi_aws as aws

example = aws.sagemaker.CodeRepository("example",
    code_repository_name="my-notebook-instance-code-repo",
    git_config={
        "repository_url": "https://github.com/github/docs.git",
    })
ni = aws.sagemaker.NotebookInstance("ni",
    name="my-notebook-instance",
    role_arn=role["arn"],
    instance_type="ml.t2.medium",
    default_code_repository=example.code_repository_name,
    tags={
        "Name": "foo",
    })

    package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v6/go/aws/sagemaker"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		example, err := sagemaker.NewCodeRepository(ctx, "example", &sagemaker.CodeRepositoryArgs{
			CodeRepositoryName: pulumi.String("my-notebook-instance-code-repo"),
			GitConfig: &sagemaker.CodeRepositoryGitConfigArgs{
				RepositoryUrl: pulumi.String("https://github.com/github/docs.git"),
			},
		})
		if err != nil {
			return err
		}
		_, err = sagemaker.NewNotebookInstance(ctx, "ni", &sagemaker.NotebookInstanceArgs{
			Name:                  pulumi.String("my-notebook-instance"),
			RoleArn:               pulumi.Any(role.Arn),
			InstanceType:          pulumi.String("ml.t2.medium"),
			DefaultCodeRepository: example.CodeRepositoryName,
			Tags: pulumi.StringMap{
				"Name": pulumi.String("foo"),
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var example = new Aws.Sagemaker.CodeRepository("example", new()
    {
        CodeRepositoryName = "my-notebook-instance-code-repo",
        GitConfig = new Aws.Sagemaker.Inputs.CodeRepositoryGitConfigArgs
        {
            RepositoryUrl = "https://github.com/github/docs.git",
        },
    });

    var ni = new Aws.Sagemaker.NotebookInstance("ni", new()
    {
        Name = "my-notebook-instance",
        RoleArn = role.Arn,
        InstanceType = "ml.t2.medium",
        DefaultCodeRepository = example.CodeRepositoryName,
        Tags = 
        {
            { "Name", "foo" },
        },
    });

});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.sagemaker.CodeRepository;
import com.pulumi.aws.sagemaker.CodeRepositoryArgs;
import com.pulumi.aws.sagemaker.inputs.CodeRepositoryGitConfigArgs;
import com.pulumi.aws.sagemaker.NotebookInstance;
import com.pulumi.aws.sagemaker.NotebookInstanceArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var example = new CodeRepository("example", CodeRepositoryArgs.builder()
            .codeRepositoryName("my-notebook-instance-code-repo")
            .gitConfig(CodeRepositoryGitConfigArgs.builder()
                .repositoryUrl("https://github.com/github/docs.git")
                .build())
            .build());

        var ni = new NotebookInstance("ni", NotebookInstanceArgs.builder()
            .name("my-notebook-instance")
            .roleArn(role.arn())
            .instanceType("ml.t2.medium")
            .defaultCodeRepository(example.codeRepositoryName())
            .tags(Map.of("Name", "foo"))
            .build());

    }
}

    resources:
  example:
    type: aws:sagemaker:CodeRepository
    properties:
      codeRepositoryName: my-notebook-instance-code-repo
      gitConfig:
        repositoryUrl: https://github.com/github/docs.git
  ni:
    type: aws:sagemaker:NotebookInstance
    properties:
      name: my-notebook-instance
      roleArn: ${role.arn}
      instanceType: ml.t2.medium
      defaultCodeRepository: ${example.codeRepositoryName}
      tags:
        Name: foo

    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,
                     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_groups: Optional[Sequence[str]] = None,
                     subnet_id: Optional[str] = None,
                     tags: Optional[Mapping[str, str]] = None,
                     volume_size: 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:sagemaker:NotebookInstance
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    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.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var notebookInstanceResource = new Aws.Sagemaker.NotebookInstance("notebookInstanceResource", new()
{
    InstanceType = "string",
    RoleArn = "string",
    Name = "string",
    PlatformIdentifier = "string",
    InstanceMetadataServiceConfiguration = new Aws.Sagemaker.Inputs.NotebookInstanceInstanceMetadataServiceConfigurationArgs
    {
        MinimumInstanceMetadataServiceVersion = "string",
    },
    DefaultCodeRepository = "string",
    KmsKeyId = "string",
    LifecycleConfigName = "string",
    DirectInternetAccess = "string",
    AdditionalCodeRepositories = new[]
    {
        "string",
    },
    RootAccess = "string",
    SecurityGroups = new[]
    {
        "string",
    },
    SubnetId = "string",
    Tags = 
    {
        { "string", "string" },
    },
    VolumeSize = 0,
});

    example, err := sagemaker.NewNotebookInstance(ctx, "notebookInstanceResource", &sagemaker.NotebookInstanceArgs{
	InstanceType:       pulumi.String("string"),
	RoleArn:            pulumi.String("string"),
	Name:               pulumi.String("string"),
	PlatformIdentifier: pulumi.String("string"),
	InstanceMetadataServiceConfiguration: &sagemaker.NotebookInstanceInstanceMetadataServiceConfigurationArgs{
		MinimumInstanceMetadataServiceVersion: pulumi.String("string"),
	},
	DefaultCodeRepository: pulumi.String("string"),
	KmsKeyId:              pulumi.String("string"),
	LifecycleConfigName:   pulumi.String("string"),
	DirectInternetAccess:  pulumi.String("string"),
	AdditionalCodeRepositories: pulumi.StringArray{
		pulumi.String("string"),
	},
	RootAccess: pulumi.String("string"),
	SecurityGroups: pulumi.StringArray{
		pulumi.String("string"),
	},
	SubnetId: pulumi.String("string"),
	Tags: pulumi.StringMap{
		"string": pulumi.String("string"),
	},
	VolumeSize: pulumi.Int(0),
})

    var notebookInstanceResource = new NotebookInstance("notebookInstanceResource", NotebookInstanceArgs.builder()
    .instanceType("string")
    .roleArn("string")
    .name("string")
    .platformIdentifier("string")
    .instanceMetadataServiceConfiguration(NotebookInstanceInstanceMetadataServiceConfigurationArgs.builder()
        .minimumInstanceMetadataServiceVersion("string")
        .build())
    .defaultCodeRepository("string")
    .kmsKeyId("string")
    .lifecycleConfigName("string")
    .directInternetAccess("string")
    .additionalCodeRepositories("string")
    .rootAccess("string")
    .securityGroups("string")
    .subnetId("string")
    .tags(Map.of("string", "string"))
    .volumeSize(0)
    .build());

    notebook_instance_resource = aws.sagemaker.NotebookInstance("notebookInstanceResource",
    instance_type="string",
    role_arn="string",
    name="string",
    platform_identifier="string",
    instance_metadata_service_configuration={
        "minimum_instance_metadata_service_version": "string",
    },
    default_code_repository="string",
    kms_key_id="string",
    lifecycle_config_name="string",
    direct_internet_access="string",
    additional_code_repositories=["string"],
    root_access="string",
    security_groups=["string"],
    subnet_id="string",
    tags={
        "string": "string",
    },
    volume_size=0)

    const notebookInstanceResource = new aws.sagemaker.NotebookInstance("notebookInstanceResource", {
    instanceType: "string",
    roleArn: "string",
    name: "string",
    platformIdentifier: "string",
    instanceMetadataServiceConfiguration: {
        minimumInstanceMetadataServiceVersion: "string",
    },
    defaultCodeRepository: "string",
    kmsKeyId: "string",
    lifecycleConfigName: "string",
    directInternetAccess: "string",
    additionalCodeRepositories: ["string"],
    rootAccess: "string",
    securityGroups: ["string"],
    subnetId: "string",
    tags: {
        string: "string",
    },
    volumeSize: 0,
});

    type: aws:sagemaker:NotebookInstance
properties:
    additionalCodeRepositories:
        - string
    defaultCodeRepository: string
    directInternetAccess: string
    instanceMetadataServiceConfiguration:
        minimumInstanceMetadataServiceVersion: string
    instanceType: string
    kmsKeyId: string
    lifecycleConfigName: string
    name: string
    platformIdentifier: string
    roleArn: string
    rootAccess: string
    securityGroups:
        - string
    subnetId: string
    tags:
        string: string
    volumeSize: 0

    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 name of ML compute instance type.
    RoleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    AcceleratorTypes List<string>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    AdditionalCodeRepositories List<string>
    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.
    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.
    DirectInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    InstanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    Name string
    The name of the notebook instance (must be unique).
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    RootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    SecurityGroups List<string>
    The associated security groups.
    SubnetId string
    The VPC subnet ID.
    Tags Dictionary<string, string>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    VolumeSize int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    InstanceType string
    The name of ML compute instance type.
    RoleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    AcceleratorTypes []string
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    AdditionalCodeRepositories []string
    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.
    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.
    DirectInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    InstanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    Name string
    The name of the notebook instance (must be unique).
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    RootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    SecurityGroups []string
    The associated security groups.
    SubnetId string
    The VPC subnet ID.
    Tags map[string]string
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    VolumeSize int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    instanceType String
    The name of ML compute instance type.
    roleArn String
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    acceleratorTypes List<String>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories List<String>
    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.
    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.
    directInternetAccess String
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    name String
    The name of the notebook instance (must be unique).
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    rootAccess String
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups List<String>
    The associated security groups.
    subnetId String
    The VPC subnet ID.
    tags Map<String,String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    volumeSize Integer
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    instanceType string
    The name of ML compute instance type.
    roleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    acceleratorTypes string[]
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories string[]
    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.
    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.
    directInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    kmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    name string
    The name of the notebook instance (must be unique).
    platformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    rootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups string[]
    The associated security groups.
    subnetId string
    The VPC subnet ID.
    tags {[key: string]: string}
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    volumeSize number
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    instance_type str
    The name of ML compute instance type.
    role_arn str
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    accelerator_types Sequence[str]
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additional_code_repositories Sequence[str]
    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.
    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.
    direct_internet_access str
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instance_metadata_service_configuration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycle_config_name str
    The name of a lifecycle configuration to associate with the notebook instance.
    name str
    The name of the notebook instance (must be unique).
    platform_identifier str
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    root_access str
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    security_groups Sequence[str]
    The associated security groups.
    subnet_id str
    The VPC subnet ID.
    tags Mapping[str, str]
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    volume_size int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    instanceType String
    The name of ML compute instance type.
    roleArn String
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    acceleratorTypes List<String>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories List<String>
    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.
    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.
    directInternetAccess String
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration Property Map
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    name String
    The name of the notebook instance (must be unique).
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    rootAccess String
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups List<String>
    The associated security groups.
    subnetId String
    The VPC subnet ID.
    tags Map<String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    volumeSize Number
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.

    Outputs

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

    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    Id string
    The provider-assigned unique ID for this managed resource.
    NetworkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    TagsAll Dictionary<string, string>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    Url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    Id string
    The provider-assigned unique ID for this managed resource.
    NetworkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    TagsAll map[string]string
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    Url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    id String
    The provider-assigned unique ID for this managed resource.
    networkInterfaceId String
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    tagsAll Map<String,String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url String
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    arn string
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    id string
    The provider-assigned unique ID for this managed resource.
    networkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    tagsAll {[key: string]: string}
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    arn str
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    id str
    The provider-assigned unique ID for this managed resource.
    network_interface_id str
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    tags_all Mapping[str, str]
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url str
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this notebook instance.
    id String
    The provider-assigned unique ID for this managed resource.
    networkInterfaceId String
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    tagsAll Map<String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url String
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.

    Look up Existing NotebookInstance Resource

    Get an existing NotebookInstance resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: NotebookInstanceState, opts?: CustomResourceOptions): NotebookInstance
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        accelerator_types: Optional[Sequence[str]] = None,
        additional_code_repositories: Optional[Sequence[str]] = None,
        arn: Optional[str] = None,
        default_code_repository: Optional[str] = None,
        direct_internet_access: Optional[str] = None,
        instance_metadata_service_configuration: Optional[NotebookInstanceInstanceMetadataServiceConfigurationArgs] = None,
        instance_type: Optional[str] = None,
        kms_key_id: Optional[str] = None,
        lifecycle_config_name: Optional[str] = None,
        name: Optional[str] = None,
        network_interface_id: Optional[str] = None,
        platform_identifier: Optional[str] = None,
        role_arn: Optional[str] = None,
        root_access: Optional[str] = None,
        security_groups: Optional[Sequence[str]] = None,
        subnet_id: Optional[str] = None,
        tags: Optional[Mapping[str, str]] = None,
        tags_all: Optional[Mapping[str, str]] = None,
        url: Optional[str] = None,
        volume_size: Optional[int] = None) -> NotebookInstance
    func GetNotebookInstance(ctx *Context, name string, id IDInput, state *NotebookInstanceState, opts ...ResourceOption) (*NotebookInstance, error)
    public static NotebookInstance Get(string name, Input<string> id, NotebookInstanceState? state, CustomResourceOptions? opts = null)
    public static NotebookInstance get(String name, Output<String> id, NotebookInstanceState state, CustomResourceOptions options)
    resources:  _:    type: aws:sagemaker:NotebookInstance    get:      id: ${id}
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    AcceleratorTypes List<string>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    AdditionalCodeRepositories List<string>
    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.
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    DirectInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    InstanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    InstanceType string
    The name of ML compute instance type.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    Name string
    The name of the notebook instance (must be unique).
    NetworkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    RoleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    RootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    SecurityGroups List<string>
    The associated security groups.
    SubnetId string
    The VPC subnet ID.
    Tags Dictionary<string, string>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll Dictionary<string, string>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    Url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    VolumeSize int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    AcceleratorTypes []string
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    AdditionalCodeRepositories []string
    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.
    Arn string
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    DirectInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    InstanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    InstanceType string
    The name of ML compute instance type.
    KmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    LifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    Name string
    The name of the notebook instance (must be unique).
    NetworkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    PlatformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    RoleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    RootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    SecurityGroups []string
    The associated security groups.
    SubnetId string
    The VPC subnet ID.
    Tags map[string]string
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    TagsAll map[string]string
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    Url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    VolumeSize int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    acceleratorTypes List<String>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories List<String>
    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.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    directInternetAccess String
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    instanceType String
    The name of ML compute instance type.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    name String
    The name of the notebook instance (must be unique).
    networkInterfaceId String
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    roleArn String
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    rootAccess String
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups List<String>
    The associated security groups.
    subnetId String
    The VPC subnet ID.
    tags Map<String,String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String,String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url String
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    volumeSize Integer
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    acceleratorTypes string[]
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories string[]
    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.
    arn string
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    directInternetAccess string
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration NotebookInstanceInstanceMetadataServiceConfiguration
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    instanceType string
    The name of ML compute instance type.
    kmsKeyId string
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName string
    The name of a lifecycle configuration to associate with the notebook instance.
    name string
    The name of the notebook instance (must be unique).
    networkInterfaceId string
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    platformIdentifier string
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    roleArn string
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    rootAccess string
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups string[]
    The associated security groups.
    subnetId string
    The VPC subnet ID.
    tags {[key: string]: string}
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll {[key: string]: string}
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url string
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    volumeSize number
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    accelerator_types Sequence[str]
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additional_code_repositories Sequence[str]
    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.
    arn str
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    direct_internet_access str
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instance_metadata_service_configuration NotebookInstanceInstanceMetadataServiceConfigurationArgs
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    instance_type str
    The name of ML compute instance type.
    kms_key_id str
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycle_config_name str
    The name of a lifecycle configuration to associate with the notebook instance.
    name str
    The name of the notebook instance (must be unique).
    network_interface_id str
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    platform_identifier str
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    role_arn str
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    root_access str
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    security_groups Sequence[str]
    The associated security groups.
    subnet_id str
    The VPC subnet ID.
    tags Mapping[str, str]
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tags_all Mapping[str, str]
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url str
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    volume_size int
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.
    acceleratorTypes List<String>
    A list of Elastic Inference (EI) instance types to associate with this notebook instance. See Elastic Inference Accelerator for more details. Valid values: ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge.

    Deprecated: accelerator_types is deprecated. Use instance_type instead.

    additionalCodeRepositories List<String>
    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.
    arn String
    The Amazon Resource Name (ARN) assigned by AWS to this 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.
    directInternetAccess String
    Set to Disabled to disable internet access to notebook. Requires security_groups and subnet_id to be set. Supported values: Enabled (Default) or Disabled. If set to Disabled, the notebook instance will be able to access resources only in your VPC, and will not be able to connect to Amazon SageMaker AI training and endpoint services unless your configure a NAT Gateway in your VPC.
    instanceMetadataServiceConfiguration Property Map
    Information on the IMDS configuration of the notebook instance. Conflicts with instance_metadata_service_configuration. see details below.
    instanceType String
    The name of ML compute instance type.
    kmsKeyId String
    The AWS Key Management Service (AWS KMS) key that Amazon SageMaker AI uses to encrypt the model artifacts at rest using Amazon S3 server-side encryption.
    lifecycleConfigName String
    The name of a lifecycle configuration to associate with the notebook instance.
    name String
    The name of the notebook instance (must be unique).
    networkInterfaceId String
    The network interface ID that Amazon SageMaker AI created at the time of creating the instance. Only available when setting subnet_id.
    platformIdentifier String
    The platform identifier of the notebook instance runtime environment. This value can be either notebook-al1-v1, notebook-al2-v1, notebook-al2-v2, or notebook-al2-v3, depending on which version of Amazon Linux you require.
    roleArn String
    The ARN of the IAM role to be used by the notebook instance which allows SageMaker AI to call other services on your behalf.
    rootAccess String
    Whether root access is Enabled or Disabled for users of the notebook instance. The default value is Enabled.
    securityGroups List<String>
    The associated security groups.
    subnetId String
    The VPC subnet ID.
    tags Map<String>
    A map of tags to assign to the resource. If configured with a provider default_tags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
    tagsAll Map<String>
    A map of tags assigned to the resource, including those inherited from the provider default_tags configuration block.

    Deprecated: Please use tags instead.

    url String
    The URL that you use to connect to the Jupyter notebook that is running in your notebook instance.
    volumeSize Number
    The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB.

    Supporting Types

    NotebookInstanceInstanceMetadataServiceConfiguration, NotebookInstanceInstanceMetadataServiceConfigurationArgs

    MinimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.
    MinimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.
    minimumInstanceMetadataServiceVersion String
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.
    minimumInstanceMetadataServiceVersion string
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.
    minimum_instance_metadata_service_version str
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.
    minimumInstanceMetadataServiceVersion String
    Indicates the minimum IMDS version that the notebook instance supports. When passed "1" is passed. This means that both IMDSv1 and IMDSv2 are supported. Valid values are 1 and 2.

    Import

    Using pulumi import, import SageMaker AI Notebook Instances using the name. For example:

    $ pulumi import aws:sagemaker/notebookInstance:NotebookInstance test_notebook_instance my-notebook-instance

    To learn more about importing existing cloud resources, see Importing resources.

    Package Details

    Repository
    AWS Classic pulumi/pulumi-aws
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the aws Terraform Provider.
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    AWS v6.73.0 published on Wednesday, Mar 19, 2025 by Pulumi
    pulumi/pulumi-aws