CfnNotebookInstance

class aws_cdk.aws_sagemaker.CfnNotebookInstance(scope, id, *, instance_type, role_arn, accelerator_types=None, additional_code_repositories=None, default_code_repository=None, direct_internet_access=None, instance_metadata_service_configuration=None, kms_key_id=None, lifecycle_config_name=None, notebook_instance_name=None, platform_identifier=None, root_access=None, security_group_ids=None, subnet_id=None, tags=None, volume_size_in_gb=None)

Bases: CfnResource

A CloudFormation AWS::SageMaker::NotebookInstance.

The AWS::SageMaker::NotebookInstance resource creates an Amazon SageMaker notebook instance. A notebook instance is a machine learning (ML) compute instance running on a Jupyter notebook. For more information, see Use Notebook Instances .

CloudformationResource:: AWS::SageMaker::NotebookInstance
Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
import aws_cdk.aws_sagemaker as sagemaker

cfn_notebook_instance = sagemaker.CfnNotebookInstance(self, "MyCfnNotebookInstance",
    instance_type="instanceType",
    role_arn="roleArn",

    # the properties below are optional
    accelerator_types=["acceleratorTypes"],
    additional_code_repositories=["additionalCodeRepositories"],
    default_code_repository="defaultCodeRepository",
    direct_internet_access="directInternetAccess",
    instance_metadata_service_configuration=sagemaker.CfnNotebookInstance.InstanceMetadataServiceConfigurationProperty(
        minimum_instance_metadata_service_version="minimumInstanceMetadataServiceVersion"
    ),
    kms_key_id="kmsKeyId",
    lifecycle_config_name="lifecycleConfigName",
    notebook_instance_name="notebookInstanceName",
    platform_identifier="platformIdentifier",
    root_access="rootAccess",
    security_group_ids=["securityGroupIds"],
    subnet_id="subnetId",
    tags=[CfnTag(
        key="key",
        value="value"
    )],
    volume_size_in_gb=123
)

Create a new AWS::SageMaker::NotebookInstance.

Parameters:

scope (Construct) –
- scope in which this resource is defined.
id (str) –
- scoped id of the resource.
instance_type (str) – The type of ML compute instance to launch for the notebook instance. .. epigraph:: 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 assumes this role to perform tasks on your behalf. You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles . .. epigraph:: To be able to pass this role to SageMaker, the caller of this API must have the iam:PassRole permission.
accelerator_types (Optional[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. For more information, see Using Elastic Inference in Amazon SageMaker . Valid Values: ml.eia1.medium | ml.eia1.large | ml.eia1.xlarge | ml.eia2.medium | ml.eia2.large | ml.eia2.xlarge .
additional_code_repositories (Optional[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. For more information, see Associating Git Repositories with SageMaker Notebook Instances .
default_code_repository (Optional[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. For more information, see Associating Git Repositories with SageMaker Notebook Instances .
direct_internet_access (Optional[str]) – Sets whether SageMaker provides internet access to the notebook instance. If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC. For more information, see Notebook Instances Are Internet-Enabled by Default . You can set the value of this parameter to Disabled only if you set a value for the SubnetId parameter.
instance_metadata_service_configuration (Union[IResolvable, InstanceMetadataServiceConfigurationProperty, Dict[str, Any], None]) – Information on the IMDS configuration of the notebook instance.
kms_key_id (Optional[str]) – The Amazon Resource Name (ARN) of a AWS Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance. The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the AWS Key Management Service Developer Guide .
lifecycle_config_name (Optional[str]) – The name of a lifecycle configuration to associate with the notebook instance. For information about lifecycle configurations, see Customize a Notebook Instance in the Amazon SageMaker Developer Guide .
notebook_instance_name (Optional[str]) – The name of the new notebook instance.
platform_identifier (Optional[str]) – The platform identifier of the notebook instance runtime environment.
root_access (Optional[str]) – Whether root access is enabled or disabled for users of the notebook instance. The default value is Enabled . .. epigraph:: 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 (Optional[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 (Optional[str]) – The ID of the subnet in a VPC to which you would like to have a connectivity from your ML compute instance.
tags (Optional[Sequence[Union[CfnTag, Dict[str, Any]]]]) – A list of key-value pairs to apply to this resource. For more information, see Resource Tag and Using Cost Allocation Tags . You can add tags later by using the CreateTags API.
volume_size_in_gb (Union[int, float, None]) – The size, in GB, of the ML storage volume to attach to the notebook instance. The default value is 5 GB. .. epigraph:: Expect some interruption of service if this parameter is changed as CloudFormation stops a notebook instance and starts it up again to update it.

Methods

add_deletion_override(path)

Syntactic sugar for addOverride(path, undefined).

Parameters:: path (str) – The path of the value to delete.
Return type:: None

add_depends_on(target)

Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.

This can be used for resources across stacks (or nested stack) boundaries and the dependency will automatically be transferred to the relevant scope.

Parameters:

target (CfnResource) –

Return type:

None

add_metadata(key, value)

Add a value to the CloudFormation Resource Metadata.

Parameters:

key (str) –
value (Any) –

See:

Return type:

None

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

add_override(path, value)

Adds an override to the synthesized CloudFormation resource.

To add a property override, either use addPropertyOverride or prefix path with “Properties.” (i.e. Properties.TopicName).

If the override is nested, separate each nested level using a dot (.) in the path parameter. If there is an array as part of the nesting, specify the index in the path.

To include a literal . in the property name, prefix with a \. In most programming languages you will need to write this as "\\." because the \ itself will need to be escaped.

For example:

cfn_resource.add_override("Properties.GlobalSecondaryIndexes.0.Projection.NonKeyAttributes", ["myattribute"])
cfn_resource.add_override("Properties.GlobalSecondaryIndexes.1.ProjectionType", "INCLUDE")

would add the overrides Example:

"Properties": {
   "GlobalSecondaryIndexes": [
     {
       "Projection": {
         "NonKeyAttributes": [ "myattribute" ]
         ...
       }
       ...
     },
     {
       "ProjectionType": "INCLUDE"
       ...
     },
   ]
   ...
}

The value argument to addOverride will not be processed or translated in any way. Pass raw JSON values in here with the correct capitalization for CloudFormation. If you pass CDK classes or structs, they will be rendered with lowercased key names, and CloudFormation will reject the template.

Parameters:

path (str) –
- The path of the property, you can use dot notation to override values in complex types. Any intermdediate keys will be created as needed.
value (Any) –
- The value. Could be primitive or complex.

Return type:

None

add_property_deletion_override(property_path)

Adds an override that deletes the value of a property from the resource definition.

Parameters:: property_path (str) – The path to the property.
Return type:: None

add_property_override(property_path, value)

Adds an override to a resource property.

Syntactic sugar for addOverride("Properties.<...>", value).

Parameters:

property_path (str) – The path of the property.
value (Any) – The value.

Return type:

None

apply_removal_policy(policy=None, *, apply_to_update_replace_policy=None, default=None)

Sets the deletion policy of the resource based on the removal policy specified.

The Removal Policy controls what happens to this resource when it stops being managed by CloudFormation, either because you’ve removed it from the CDK application or because you’ve made a change that requires the resource to be replaced.

The resource can be deleted (RemovalPolicy.DESTROY), or left in your AWS account for data recovery and cleanup later (RemovalPolicy.RETAIN).

Parameters:

policy (Optional[RemovalPolicy]) –
apply_to_update_replace_policy (Optional[bool]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: true
default (Optional[RemovalPolicy]) – The default policy to apply in case the removal policy is not defined. Default: - Default value is resource specific. To determine the default value for a resoure, please consult that specific resource’s documentation.

Return type:

None

get_att(attribute_name)

Returns a token for an runtime attribute of this resource.

Ideally, use generated attribute accessors (e.g. resource.arn), but this can be used for future compatibility in case there is no generated attribute.

Parameters:: attribute_name (str) – The name of the attribute.
Return type:: Reference

get_metadata(key)

Retrieve a value value from the CloudFormation Resource Metadata.

Parameters:

key (str) –

See:

Return type:

Any

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/metadata-section-structure.html

Note that this is a different set of metadata from CDK node metadata; this metadata ends up in the stack template under the resource, whereas CDK node metadata ends up in the Cloud Assembly.

inspect(inspector)

Examines the CloudFormation resource and discloses attributes.

Parameters:

inspector (TreeInspector) –

tree inspector to collect and process attributes.

Return type:

None

override_logical_id(new_logical_id)

Overrides the auto-generated logical ID with a specific ID.

Parameters:: new_logical_id (str) – The new logical ID to use for this stack element.
Return type:: None

to_string()

Returns a string representation of this construct.

Return type:: str
Returns:: a string representation of this resource

Attributes

CFN_RESOURCE_TYPE_NAME = 'AWS::SageMaker::NotebookInstance'

accelerator_types

A list of Amazon Elastic Inference (EI) instance types to associate with the notebook instance.

Currently, only one instance type can be associated with a notebook instance. For more information, see Using Elastic Inference in Amazon SageMaker .

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-acceleratortypes

additional_code_repositories

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. For more information, see Associating Git Repositories with SageMaker Notebook Instances .

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-additionalcoderepositories

attr_notebook_instance_name

The name of the notebook instance, such as MyNotebookInstance .

CloudformationAttribute:: NotebookInstanceName

cfn_options: Options for this resource, such as condition, update policy etc.

cfn_resource_type: AWS resource type.

creation_stack

return:

the stack trace of the point where this Resource was created from, sourced from the +metadata+ entry typed +aws:cdk:logicalId+, and with the bottom-most node +internal+ entries filtered.

default_code_repository

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. For more information, see Associating Git Repositories with SageMaker Notebook Instances .

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-defaultcoderepository

direct_internet_access

Sets whether SageMaker provides internet access to the notebook instance.

If you set this to Disabled this notebook instance is able to access resources only in your VPC, and is not be able to connect to SageMaker training and endpoint services unless you configure a NAT Gateway in your VPC.

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

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-directinternetaccess

instance_metadata_service_configuration

Information on the IMDS configuration of the notebook instance.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-instancemetadataserviceconfiguration

instance_type

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.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-instancetype

kms_key_id

The Amazon Resource Name (ARN) of a AWS Key Management Service key that SageMaker uses to encrypt data on the storage volume attached to your notebook instance.

The KMS key you provide must be enabled. For information, see Enabling and Disabling Keys in the AWS Key Management Service Developer Guide .

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-kmskeyid

lifecycle_config_name

The name of a lifecycle configuration to associate with the notebook instance.

For information about lifecycle configurations, see Customize a Notebook Instance in the Amazon SageMaker Developer Guide .

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-lifecycleconfigname

logical_id

The logical ID for this CloudFormation stack element.

The logical ID of the element is calculated from the path of the resource node in the construct tree.

To override this value, use overrideLogicalId(newLogicalId).

Returns:

the logical ID as a stringified token. This value will only get resolved during synthesis.

node: The construct tree node associated with this construct.

notebook_instance_name

The name of the new notebook instance.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-notebookinstancename

platform_identifier

The platform identifier of the notebook instance runtime environment.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-platformidentifier

ref

Return a string that will be resolved to a CloudFormation { Ref } for this element.

If, by any chance, the intrinsic reference of a resource is not a string, you could coerce it to an IResolvable through Lazy.any({ produce: resource.ref }).

role_arn

When you send any requests to AWS resources from the notebook instance, SageMaker assumes this role to perform tasks on your behalf.

You must grant this role necessary permissions so SageMaker can perform these tasks. The policy must allow the SageMaker service principal (sagemaker.amazonaws.com) permissions to assume this role. For more information, see SageMaker Roles . .. epigraph:

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

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-rolearn

root_access

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.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-rootaccess

security_group_ids

The VPC security group IDs, in the form sg-xxxxxxxx.

The security groups must be for the same VPC as specified in the subnet.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-securitygroupids

stack

The stack in which this element is defined.

CfnElements must be defined within a stack scope (directly or indirectly).

subnet_id

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

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-subnetid

tags

A list of key-value pairs to apply to this resource.

For more information, see Resource Tag and Using Cost Allocation Tags .

You can add tags later by using the CreateTags API.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-tags

volume_size_in_gb

The size, in GB, of the ML storage volume to attach to the notebook instance.

The default value is 5 GB. .. epigraph:

Expect some interruption of service if this parameter is changed as CloudFormation stops a notebook instance and starts it up again to update it.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-notebookinstance.html#cfn-sagemaker-notebookinstance-volumesizeingb

Static Methods

classmethod is_cfn_element(x)

Returns true if a construct is a stack element (i.e. part of the synthesized cloudformation template).

Uses duck-typing instead of instanceof to allow stack elements from different versions of this library to be included in the same stack.

Parameters:

x (Any) –

Return type:

bool

Returns:

The construct as a stack element or undefined if it is not a stack element.

classmethod is_cfn_resource(construct)

Check whether the given construct is a CfnResource.

Parameters:

construct (IConstruct) –

Return type:

bool

classmethod is_construct(x)

Return whether the given object is a Construct.

Parameters:

x (Any) –

Return type:

bool

InstanceMetadataServiceConfigurationProperty

class CfnNotebookInstance.InstanceMetadataServiceConfigurationProperty(*, minimum_instance_metadata_service_version)

Bases: object

Information on the IMDS configuration of the notebook instance.

Parameters:: 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.
Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-notebookinstance-instancemetadataserviceconfiguration.html
ExampleMetadata:: fixture=_generated

Example:

# The code below shows an example of how to instantiate this type.
# The values are placeholders you should change.
import aws_cdk.aws_sagemaker as sagemaker

instance_metadata_service_configuration_property = sagemaker.CfnNotebookInstance.InstanceMetadataServiceConfigurationProperty(
    minimum_instance_metadata_service_version="minimumInstanceMetadataServiceVersion"
)

Attributes

minimum_instance_metadata_service_version

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.

Link:: http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-notebookinstance-instancemetadataserviceconfiguration.html#cfn-sagemaker-notebookinstance-instancemetadataserviceconfiguration-minimuminstancemetadataserviceversion