CfnCluster
- class aws_cdk.aws_sagemaker.CfnCluster(scope, id, *, instance_groups, cluster_name=None, node_recovery=None, orchestrator=None, tags=None, vpc_config=None)
Bases:
CfnResource
Creates a SageMaker HyperPod cluster.
SageMaker HyperPod is a capability of SageMaker for creating and managing persistent clusters for developing large machine learning models, such as large language models (LLMs) and diffusion models. To learn more, see Amazon SageMaker HyperPod in the Amazon SageMaker Developer Guide .
- See:
http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-sagemaker-cluster.html
- CloudformationResource:
AWS::SageMaker::Cluster
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cfn_cluster = sagemaker.CfnCluster(self, "MyCfnCluster", instance_groups=[sagemaker.CfnCluster.ClusterInstanceGroupProperty( execution_role="executionRole", instance_count=123, instance_group_name="instanceGroupName", instance_type="instanceType", life_cycle_config=sagemaker.CfnCluster.ClusterLifeCycleConfigProperty( on_create="onCreate", source_s3_uri="sourceS3Uri" ), # the properties below are optional current_count=123, instance_storage_configs=[sagemaker.CfnCluster.ClusterInstanceStorageConfigProperty( ebs_volume_config=sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty( volume_size_in_gb=123 ) )], on_start_deep_health_checks=["onStartDeepHealthChecks"], threads_per_core=123 )], # the properties below are optional cluster_name="clusterName", node_recovery="nodeRecovery", orchestrator=sagemaker.CfnCluster.OrchestratorProperty( eks=sagemaker.CfnCluster.ClusterOrchestratorEksConfigProperty( cluster_arn="clusterArn" ) ), tags=[CfnTag( key="key", value="value" )], vpc_config=sagemaker.CfnCluster.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] ) )
- Parameters:
scope (
Construct
) – Scope in which this resource is defined.id (
str
) – Construct identifier for this resource (unique in its scope).instance_groups (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ClusterInstanceGroupProperty
,Dict
[str
,Any
]]]]) – The instance groups of the SageMaker HyperPod cluster.cluster_name (
Optional
[str
]) – The name of the SageMaker HyperPod cluster.node_recovery (
Optional
[str
]) – Specifies whether to enable or disable the automatic node recovery feature of SageMaker HyperPod. Available values areAutomatic
for enabling andNone
for disabling.orchestrator (
Union
[IResolvable
,OrchestratorProperty
,Dict
[str
,Any
],None
]) – The orchestrator type for the SageMaker HyperPod cluster. Currently,'eks'
is the only available option.tags (
Optional
[Sequence
[Union
[CfnTag
,Dict
[str
,Any
]]]]) – A tag object that consists of a key and an optional value, used to manage metadata for SageMaker AWS resources. You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags . For more information on adding metadata to your AWS resources with tagging, see Tagging AWS resources . For advice on best practices for managing AWS resources with tagging, see Tagging Best Practices: Implement an Effective AWS Resource Tagging Strategy .vpc_config (
Union
[IResolvable
,VpcConfigProperty
,Dict
[str
,Any
],None
]) – Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to. You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .
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_dependency(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_depends_on(target)
(deprecated) Indicates that this resource depends on another resource and cannot be provisioned unless the other resource has been successfully provisioned.
- Parameters:
target (
CfnResource
) –- Deprecated:
use addDependency
- Stability:
deprecated
- 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 prefixpath
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 toaddOverride
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 intermediate 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
). In some cases, a snapshot can be taken of the resource prior to deletion (RemovalPolicy.SNAPSHOT
). A list of resources that support this policy can be found in the following link:- Parameters:
policy (
Optional
[RemovalPolicy
]) –apply_to_update_replace_policy (
Optional
[bool
]) – Apply the same deletion policy to the resource’s “UpdateReplacePolicy”. Default: truedefault (
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 resource, please consult that specific resource’s documentation.
- See:
- Return type:
None
- get_att(attribute_name, type_hint=None)
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.type_hint (
Optional
[ResolutionTypeHint
]) –
- Return type:
- 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
- obtain_dependencies()
Retrieves an array of resources this resource depends on.
This assembles dependencies on resources across stacks (including nested stacks) automatically.
- Return type:
List
[Union
[Stack
,CfnResource
]]
- obtain_resource_dependencies()
Get a shallow copy of dependencies between this resource and other resources in the same stack.
- Return type:
List
[CfnResource
]
- 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
- remove_dependency(target)
Indicates that this resource no longer depends on another resource.
This can be used for resources across stacks (including nested stacks) and the dependency will automatically be removed from the relevant scope.
- Parameters:
target (
CfnResource
) –- Return type:
None
- replace_dependency(target, new_target)
Replaces one dependency with another.
- Parameters:
target (
CfnResource
) – The dependency to replace.new_target (
CfnResource
) – The new dependency to add.
- 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::Cluster'
- attr_cluster_arn
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
- CloudformationAttribute:
ClusterArn
- attr_cluster_status
The status of the SageMaker HyperPod cluster.
- CloudformationAttribute:
ClusterStatus
- attr_creation_time
The time when the SageMaker HyperPod cluster is created.
- CloudformationAttribute:
CreationTime
- attr_failure_message
The failure message of the SageMaker HyperPod cluster.
- CloudformationAttribute:
FailureMessage
- cdk_tag_manager
Tag Manager which manages the tags for this resource.
- cfn_options
Options for this resource, such as condition, update policy etc.
- cfn_resource_type
AWS resource type.
- cluster_name
The name of the SageMaker HyperPod cluster.
- 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.
- instance_groups
The instance groups of the SageMaker HyperPod cluster.
- 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 tree node.
- node_recovery
Specifies whether to enable or disable the automatic node recovery feature of SageMaker HyperPod.
- orchestrator
The orchestrator type for the SageMaker HyperPod cluster.
- 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 })
.
- stack
The stack in which this element is defined.
CfnElements must be defined within a stack scope (directly or indirectly).
- tags
A tag object that consists of a key and an optional value, used to manage metadata for SageMaker AWS resources.
- vpc_config
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to.
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(x)
Check whether the given object is a CfnResource.
- Parameters:
x (
Any
) –- Return type:
bool
- classmethod is_construct(x)
Checks if
x
is a construct.Use this method instead of
instanceof
to properly detectConstruct
instances, even when the construct library is symlinked.Explanation: in JavaScript, multiple copies of the
constructs
library on disk are seen as independent, completely different libraries. As a consequence, the classConstruct
in each copy of theconstructs
library is seen as a different class, and an instance of one class will not test asinstanceof
the other class.npm install
will not create installations like this, but users may manually symlink construct libraries together or use a monorepo tool: in those cases, multiple copies of theconstructs
library can be accidentally installed, andinstanceof
will behave unpredictably. It is safest to avoid usinginstanceof
, and using this type-testing method instead.- Parameters:
x (
Any
) – Any object.- Return type:
bool
- Returns:
true if
x
is an object created from a class which extendsConstruct
.
ClusterEbsVolumeConfigProperty
- class CfnCluster.ClusterEbsVolumeConfigProperty(*, volume_size_in_gb=None)
Bases:
object
Defines the configuration for attaching an additional Amazon Elastic Block Store (EBS) volume to each instance of the SageMaker HyperPod cluster instance group.
To learn more, see SageMaker HyperPod release notes: June 20, 2024 .
- Parameters:
volume_size_in_gb (
Union
[int
,float
,None
]) – The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to/opt/sagemaker
.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cluster_ebs_volume_config_property = sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty( volume_size_in_gb=123 )
Attributes
- volume_size_in_gb
The size in gigabytes (GB) of the additional EBS volume to be attached to the instances in the SageMaker HyperPod cluster instance group.
The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to
/opt/sagemaker
.
ClusterInstanceGroupProperty
- class CfnCluster.ClusterInstanceGroupProperty(*, execution_role, instance_count, instance_group_name, instance_type, life_cycle_config, current_count=None, instance_storage_configs=None, on_start_deep_health_checks=None, threads_per_core=None)
Bases:
object
The configuration information of the instance group within the HyperPod cluster.
- Parameters:
execution_role (
str
) – The execution role for the instance group to assume.instance_count (
Union
[int
,float
]) – The number of instances in an instance group of the SageMaker HyperPod cluster.instance_group_name (
str
) – The name of the instance group of a SageMaker HyperPod cluster.instance_type (
str
) – The instance type of the instance group of a SageMaker HyperPod cluster.life_cycle_config (
Union
[IResolvable
,ClusterLifeCycleConfigProperty
,Dict
[str
,Any
]]) – The lifecycle configuration for a SageMaker HyperPod cluster.current_count (
Union
[int
,float
,None
]) – The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.instance_storage_configs (
Union
[IResolvable
,Sequence
[Union
[IResolvable
,ClusterInstanceStorageConfigProperty
,Dict
[str
,Any
]]],None
]) – The configurations of additional storage specified to the instance group where the instance (node) is launched.on_start_deep_health_checks (
Optional
[Sequence
[str
]]) – A flag indicating whether deep health checks should be performed when the HyperPod cluster instance group is created or updated. Deep health checks are comprehensive, invasive tests that validate the health of the underlying hardware and infrastructure components.threads_per_core (
Union
[int
,float
,None
]) – The number of threads per CPU core you specified underCreateCluster
.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cluster_instance_group_property = sagemaker.CfnCluster.ClusterInstanceGroupProperty( execution_role="executionRole", instance_count=123, instance_group_name="instanceGroupName", instance_type="instanceType", life_cycle_config=sagemaker.CfnCluster.ClusterLifeCycleConfigProperty( on_create="onCreate", source_s3_uri="sourceS3Uri" ), # the properties below are optional current_count=123, instance_storage_configs=[sagemaker.CfnCluster.ClusterInstanceStorageConfigProperty( ebs_volume_config=sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty( volume_size_in_gb=123 ) )], on_start_deep_health_checks=["onStartDeepHealthChecks"], threads_per_core=123 )
Attributes
- current_count
The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.
- execution_role
The execution role for the instance group to assume.
- instance_count
The number of instances in an instance group of the SageMaker HyperPod cluster.
- instance_group_name
The name of the instance group of a SageMaker HyperPod cluster.
- instance_storage_configs
The configurations of additional storage specified to the instance group where the instance (node) is launched.
- instance_type
The instance type of the instance group of a SageMaker HyperPod cluster.
- life_cycle_config
The lifecycle configuration for a SageMaker HyperPod cluster.
- on_start_deep_health_checks
A flag indicating whether deep health checks should be performed when the HyperPod cluster instance group is created or updated.
Deep health checks are comprehensive, invasive tests that validate the health of the underlying hardware and infrastructure components.
- threads_per_core
The number of threads per CPU core you specified under
CreateCluster
.
ClusterInstanceStorageConfigProperty
- class CfnCluster.ClusterInstanceStorageConfigProperty(*, ebs_volume_config=None)
Bases:
object
Defines the configuration for attaching additional storage to the instances in the SageMaker HyperPod cluster instance group.
To learn more, see SageMaker HyperPod release notes: June 20, 2024 .
- Parameters:
ebs_volume_config (
Union
[IResolvable
,ClusterEbsVolumeConfigProperty
,Dict
[str
,Any
],None
]) – Defines the configuration for attaching additional Amazon Elastic Block Store (EBS) volumes to the instances in the SageMaker HyperPod cluster instance group. The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to/opt/sagemaker
.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cluster_instance_storage_config_property = sagemaker.CfnCluster.ClusterInstanceStorageConfigProperty( ebs_volume_config=sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty( volume_size_in_gb=123 ) )
Attributes
- ebs_volume_config
Defines the configuration for attaching additional Amazon Elastic Block Store (EBS) volumes to the instances in the SageMaker HyperPod cluster instance group.
The additional EBS volume is attached to each instance within the SageMaker HyperPod cluster instance group and mounted to
/opt/sagemaker
.
ClusterLifeCycleConfigProperty
- class CfnCluster.ClusterLifeCycleConfigProperty(*, on_create, source_s3_uri)
Bases:
object
The lifecycle configuration for a SageMaker HyperPod cluster.
- Parameters:
on_create (
str
) – The file name of the entrypoint script of lifecycle scripts underSourceS3Uri
. This entrypoint script runs during cluster creation.source_s3_uri (
str
) – An Amazon S3 bucket path where your lifecycle scripts are stored. .. epigraph:: Make sure that the S3 bucket path starts withs3://sagemaker-
. The IAM role for SageMaker HyperPod has the managed`AmazonSageMakerClusterInstanceRolePolicy
<https://docs.aws.amazon.com/sagemaker/latest/dg/security-iam-awsmanpol-cluster.html>`_ attached, which allows access to S3 buckets with the specific prefixsagemaker-
.
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cluster_life_cycle_config_property = sagemaker.CfnCluster.ClusterLifeCycleConfigProperty( on_create="onCreate", source_s3_uri="sourceS3Uri" )
Attributes
- on_create
The file name of the entrypoint script of lifecycle scripts under
SourceS3Uri
.This entrypoint script runs during cluster creation.
- source_s3_uri
An Amazon S3 bucket path where your lifecycle scripts are stored.
Make sure that the S3 bucket path starts with
s3://sagemaker-
. The IAM role for SageMaker HyperPod has the managed`AmazonSageMakerClusterInstanceRolePolicy
<https://docs.aws.amazon.com/sagemaker/latest/dg/security-iam-awsmanpol-cluster.html>`_ attached, which allows access to S3 buckets with the specific prefixsagemaker-
.
ClusterOrchestratorEksConfigProperty
- class CfnCluster.ClusterOrchestratorEksConfigProperty(*, cluster_arn)
Bases:
object
The configuration for the Amazon EKS cluster that is used as the orchestrator for the SageMaker HyperPod cluster.
This includes the Amazon Resource Name (ARN) of the EKS cluster
- Parameters:
cluster_arn (
str
) – The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker cluster_orchestrator_eks_config_property = sagemaker.CfnCluster.ClusterOrchestratorEksConfigProperty( cluster_arn="clusterArn" )
Attributes
- cluster_arn
The Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
OrchestratorProperty
- class CfnCluster.OrchestratorProperty(*, eks)
Bases:
object
The orchestrator for a SageMaker HyperPod cluster.
- Parameters:
eks (
Union
[IResolvable
,ClusterOrchestratorEksConfigProperty
,Dict
[str
,Any
]]) – The configuration of the Amazon EKS orchestrator cluster for the SageMaker HyperPod cluster.- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker orchestrator_property = sagemaker.CfnCluster.OrchestratorProperty( eks=sagemaker.CfnCluster.ClusterOrchestratorEksConfigProperty( cluster_arn="clusterArn" ) )
Attributes
- eks
The configuration of the Amazon EKS orchestrator cluster for the SageMaker HyperPod cluster.
VpcConfigProperty
- class CfnCluster.VpcConfigProperty(*, security_group_ids, subnets)
Bases:
object
Specifies an Amazon Virtual Private Cloud (VPC) that your SageMaker jobs, hosted models, and compute resources have access to.
You can control access to and from your resources by configuring a VPC. For more information, see Give SageMaker Access to Resources in your Amazon VPC .
- Parameters:
security_group_ids (
Sequence
[str
]) – The VPC security group IDs, in the formsg-xxxxxxxx
. Specify the security groups for the VPC that is specified in theSubnets
field.subnets (
Sequence
[str
]) – The ID of the subnets in the VPC to which you want to connect your training job or model. For information about the availability of specific instance types, see Supported Instance Types and Availability Zones .
- See:
- ExampleMetadata:
fixture=_generated
Example:
# The code below shows an example of how to instantiate this type. # The values are placeholders you should change. from aws_cdk import aws_sagemaker as sagemaker vpc_config_property = sagemaker.CfnCluster.VpcConfigProperty( security_group_ids=["securityGroupIds"], subnets=["subnets"] )
Attributes
- security_group_ids
The VPC security group IDs, in the form
sg-xxxxxxxx
.Specify the security groups for the VPC that is specified in the
Subnets
field.
- subnets
The ID of the subnets in the VPC to which you want to connect your training job or model.
For information about the availability of specific instance types, see Supported Instance Types and Availability Zones .