CfnCluster

class aws_cdk.aws_sagemaker.CfnCluster(scope, id, *, cluster_name=None, instance_groups=None, node_provisioning_mode=None, node_recovery=None, orchestrator=None, restricted_instance_groups=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",
    cluster_name="clusterName",
    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,
        image_id="imageId",
        instance_storage_configs=[sagemaker.CfnCluster.ClusterInstanceStorageConfigProperty(
            ebs_volume_config=sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty(
                volume_size_in_gb=123
            )
        )],
        on_start_deep_health_checks=["onStartDeepHealthChecks"],
        override_vpc_config=sagemaker.CfnCluster.VpcConfigProperty(
            security_group_ids=["securityGroupIds"],
            subnets=["subnets"]
        ),
        scheduled_update_config=sagemaker.CfnCluster.ScheduledUpdateConfigProperty(
            schedule_expression="scheduleExpression",

            # the properties below are optional
            deployment_config=sagemaker.CfnCluster.DeploymentConfigProperty(
                auto_rollback_configuration=[sagemaker.CfnCluster.AlarmDetailsProperty(
                    alarm_name="alarmName"
                )],
                rolling_update_policy=sagemaker.CfnCluster.RollingUpdatePolicyProperty(
                    maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                        type="type",
                        value=123
                    ),

                    # the properties below are optional
                    rollback_maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                        type="type",
                        value=123
                    )
                ),
                wait_interval_in_seconds=123
            )
        ),
        threads_per_core=123,
        training_plan_arn="trainingPlanArn"
    )],
    node_provisioning_mode="nodeProvisioningMode",
    node_recovery="nodeRecovery",
    orchestrator=sagemaker.CfnCluster.OrchestratorProperty(
        eks=sagemaker.CfnCluster.ClusterOrchestratorEksConfigProperty(
            cluster_arn="clusterArn"
        )
    ),
    restricted_instance_groups=[sagemaker.CfnCluster.ClusterRestrictedInstanceGroupProperty(
        environment_config=sagemaker.CfnCluster.EnvironmentConfigProperty(
            f_sx_lustre_config=sagemaker.CfnCluster.FSxLustreConfigProperty(
                per_unit_storage_throughput=123,
                size_in_gi_b=123
            )
        ),
        execution_role="executionRole",
        instance_count=123,
        instance_group_name="instanceGroupName",
        instance_type="instanceType",

        # 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"],
        override_vpc_config=sagemaker.CfnCluster.VpcConfigProperty(
            security_group_ids=["securityGroupIds"],
            subnets=["subnets"]
        ),
        threads_per_core=123,
        training_plan_arn="trainingPlanArn"
    )],
    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).

  • cluster_name (Optional[str]) – The name of the SageMaker HyperPod cluster.

  • instance_groups (Union[IResolvable, Sequence[Union[IResolvable, ClusterInstanceGroupProperty, Dict[str, Any]]], None]) – The instance groups of the SageMaker HyperPod cluster. To delete an instance group, remove it from the array.

  • node_provisioning_mode (Optional[str]) – Determines the scaling strategy for the SageMaker HyperPod cluster. When set to ‘Continuous’, enables continuous scaling which dynamically manages node provisioning. If the parameter is omitted, uses the standard scaling approach in previous release.

  • node_recovery (Optional[str]) – Specifies whether to enable or disable the automatic node recovery feature of SageMaker HyperPod. Available values are Automatic for enabling and None 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.

  • restricted_instance_groups (Union[IResolvable, Sequence[Union[IResolvable, ClusterRestrictedInstanceGroupProperty, Dict[str, Any]]], None]) – The restricted instance groups of the SageMaker HyperPod cluster.

  • 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 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 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: 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 resource, please consult that specific resource’s documentation.

See:

https://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-attribute-deletionpolicy.html#aws-attribute-deletionpolicy-options

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:

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

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:
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.

cluster_ref

A reference to a Cluster resource.

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_provisioning_mode

Determines the scaling strategy for the SageMaker HyperPod cluster.

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 }).

restricted_instance_groups

The restricted instance groups of the SageMaker HyperPod cluster.

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 detect Construct 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 class Construct in each copy of the constructs library is seen as a different class, and an instance of one class will not test as instanceof 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 the constructs library can be accidentally installed, and instanceof will behave unpredictably. It is safest to avoid using instanceof, 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 extends Construct.

AlarmDetailsProperty

class CfnCluster.AlarmDetailsProperty(*, alarm_name)

Bases: object

The details of the alarm to monitor during the AMI update.

Parameters:

alarm_name (str) – The name of the alarm.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-alarmdetails.html

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

alarm_details_property = sagemaker.CfnCluster.AlarmDetailsProperty(
    alarm_name="alarmName"
)

Attributes

alarm_name

The name of the alarm.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-alarmdetails.html#cfn-sagemaker-cluster-alarmdetails-alarmname

CapacitySizeConfigProperty

class CfnCluster.CapacitySizeConfigProperty(*, type, value)

Bases: object

The configuration of the size measurements of the AMI update.

Using this configuration, you can specify whether SageMaker should update your instance group by an amount or percentage of instances.

Parameters:

  • type (str) – Specifies whether SageMaker should process the update by amount or percentage of instances.

  • value (Union[int, float]) – Specifies the amount or percentage of instances SageMaker updates at a time.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-capacitysizeconfig.html

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

capacity_size_config_property = sagemaker.CfnCluster.CapacitySizeConfigProperty(
    type="type",
    value=123
)

Attributes

type

Specifies whether SageMaker should process the update by amount or percentage of instances.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-capacitysizeconfig.html#cfn-sagemaker-cluster-capacitysizeconfig-type

value

Specifies the amount or percentage of instances SageMaker updates at a time.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-capacitysizeconfig.html#cfn-sagemaker-cluster-capacitysizeconfig-value

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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterebsvolumeconfig.html

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 .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterebsvolumeconfig.html#cfn-sagemaker-cluster-clusterebsvolumeconfig-volumesizeingb

ClusterInstanceGroupProperty

class CfnCluster.ClusterInstanceGroupProperty(*, execution_role, instance_count, instance_group_name, instance_type, life_cycle_config, current_count=None, image_id=None, instance_storage_configs=None, on_start_deep_health_checks=None, override_vpc_config=None, scheduled_update_config=None, threads_per_core=None, training_plan_arn=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.

  • image_id (Optional[str]) – AMI Id to be used for launching EC2 instances - HyperPodPublicAmiId or CustomAmiId.

  • 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.

  • override_vpc_config (Union[IResolvable, VpcConfigProperty, Dict[str, Any], None]) – The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.

  • scheduled_update_config (Union[IResolvable, ScheduledUpdateConfigProperty, Dict[str, Any], None]) – The configuration object of the schedule that SageMaker follows when updating the AMI.

  • threads_per_core (Union[int, float, None]) – The number of threads per CPU core you specified under CreateCluster .

  • training_plan_arn (Optional[str]) – The Amazon Resource Name (ARN) of the training plan to use for this cluster instance group. For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html

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,
    image_id="imageId",
    instance_storage_configs=[sagemaker.CfnCluster.ClusterInstanceStorageConfigProperty(
        ebs_volume_config=sagemaker.CfnCluster.ClusterEbsVolumeConfigProperty(
            volume_size_in_gb=123
        )
    )],
    on_start_deep_health_checks=["onStartDeepHealthChecks"],
    override_vpc_config=sagemaker.CfnCluster.VpcConfigProperty(
        security_group_ids=["securityGroupIds"],
        subnets=["subnets"]
    ),
    scheduled_update_config=sagemaker.CfnCluster.ScheduledUpdateConfigProperty(
        schedule_expression="scheduleExpression",

        # the properties below are optional
        deployment_config=sagemaker.CfnCluster.DeploymentConfigProperty(
            auto_rollback_configuration=[sagemaker.CfnCluster.AlarmDetailsProperty(
                alarm_name="alarmName"
            )],
            rolling_update_policy=sagemaker.CfnCluster.RollingUpdatePolicyProperty(
                maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                    type="type",
                    value=123
                ),

                # the properties below are optional
                rollback_maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                    type="type",
                    value=123
                )
            ),
            wait_interval_in_seconds=123
        )
    ),
    threads_per_core=123,
    training_plan_arn="trainingPlanArn"
)

Attributes

current_count

The number of instances that are currently in the instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-currentcount

execution_role

The execution role for the instance group to assume.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-executionrole

image_id

AMI Id to be used for launching EC2 instances - HyperPodPublicAmiId or CustomAmiId.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-imageid

instance_count

The number of instances in an instance group of the SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-instancecount

instance_group_name

The name of the instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-instancegroupname

instance_storage_configs

The configurations of additional storage specified to the instance group where the instance (node) is launched.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-instancestorageconfigs

instance_type

The instance type of the instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-instancetype

life_cycle_config

The lifecycle configuration for a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-lifecycleconfig

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-onstartdeephealthchecks

override_vpc_config

The customized Amazon VPC configuration at the instance group level that overrides the default Amazon VPC configuration of the SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-overridevpcconfig

scheduled_update_config

The configuration object of the schedule that SageMaker follows when updating the AMI.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-scheduledupdateconfig

threads_per_core

The number of threads per CPU core you specified under CreateCluster .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-threadspercore

training_plan_arn

The Amazon Resource Name (ARN) of the training plan to use for this cluster instance group.

For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancegroup.html#cfn-sagemaker-cluster-clusterinstancegroup-trainingplanarn

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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancestorageconfig.html

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 .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterinstancestorageconfig.html#cfn-sagemaker-cluster-clusterinstancestorageconfig-ebsvolumeconfig

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 under SourceS3Uri . 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 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 prefix sagemaker- .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterlifecycleconfig.html

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterlifecycleconfig.html#cfn-sagemaker-cluster-clusterlifecycleconfig-oncreate

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 prefix sagemaker- .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterlifecycleconfig.html#cfn-sagemaker-cluster-clusterlifecycleconfig-sources3uri

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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterorchestratoreksconfig.html

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterorchestratoreksconfig.html#cfn-sagemaker-cluster-clusterorchestratoreksconfig-clusterarn

ClusterRestrictedInstanceGroupProperty

class CfnCluster.ClusterRestrictedInstanceGroupProperty(*, environment_config, execution_role, instance_count, instance_group_name, instance_type, current_count=None, instance_storage_configs=None, on_start_deep_health_checks=None, override_vpc_config=None, threads_per_core=None, training_plan_arn=None)

Bases: object

Details of a restricted instance group in a SageMaker HyperPod cluster.

Parameters:

  • environment_config (Union[IResolvable, EnvironmentConfigProperty, Dict[str, Any]]) – The configuration for the restricted instance groups (RIG) environment.

  • execution_role (str) – The execution role for the instance group to assume.

  • instance_count (Union[int, float]) – The number of instances you specified to add to the restricted instance group of a 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.

  • current_count (Union[int, float, None]) – The number of instances that are currently in the restricted instance group of a SageMaker HyperPod cluster.

  • instance_storage_configs (Union[IResolvable, Sequence[Union[IResolvable, ClusterInstanceStorageConfigProperty, Dict[str, Any]]], None]) – The instance storage configuration for the instance group.

  • on_start_deep_health_checks (Optional[Sequence[str]]) – Nodes will undergo advanced stress test to detect and replace faulty instances, based on the type of deep health check(s) passed in.

  • override_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.

  • threads_per_core (Union[int, float, None]) – The number you specified to TreadsPerCore in CreateCluster for enabling or disabling multithreading. For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading.

  • training_plan_arn (Optional[str]) – The Amazon Resource Name (ARN) of the training plan to use for this cluster restricted instance group. For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html

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_restricted_instance_group_property = sagemaker.CfnCluster.ClusterRestrictedInstanceGroupProperty(
    environment_config=sagemaker.CfnCluster.EnvironmentConfigProperty(
        f_sx_lustre_config=sagemaker.CfnCluster.FSxLustreConfigProperty(
            per_unit_storage_throughput=123,
            size_in_gi_b=123
        )
    ),
    execution_role="executionRole",
    instance_count=123,
    instance_group_name="instanceGroupName",
    instance_type="instanceType",

    # 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"],
    override_vpc_config=sagemaker.CfnCluster.VpcConfigProperty(
        security_group_ids=["securityGroupIds"],
        subnets=["subnets"]
    ),
    threads_per_core=123,
    training_plan_arn="trainingPlanArn"
)

Attributes

current_count

The number of instances that are currently in the restricted instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-currentcount

environment_config

The configuration for the restricted instance groups (RIG) environment.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-environmentconfig

execution_role

The execution role for the instance group to assume.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-executionrole

instance_count

The number of instances you specified to add to the restricted instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-instancecount

instance_group_name

The name of the instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-instancegroupname

instance_storage_configs

The instance storage configuration for the instance group.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-instancestorageconfigs

instance_type

The instance type of the instance group of a SageMaker HyperPod cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-instancetype

on_start_deep_health_checks

Nodes will undergo advanced stress test to detect and replace faulty instances, based on the type of deep health check(s) passed in.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-onstartdeephealthchecks

override_vpc_config

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-overridevpcconfig

threads_per_core

The number you specified to TreadsPerCore in CreateCluster for enabling or disabling multithreading.

For instance types that support multithreading, you can specify 1 for disabling multithreading and 2 for enabling multithreading.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-threadspercore

training_plan_arn

The Amazon Resource Name (ARN) of the training plan to use for this cluster restricted instance group.

For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see CreateTrainingPlan.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-clusterrestrictedinstancegroup.html#cfn-sagemaker-cluster-clusterrestrictedinstancegroup-trainingplanarn

DeploymentConfigProperty

class CfnCluster.DeploymentConfigProperty(*, auto_rollback_configuration=None, rolling_update_policy=None, wait_interval_in_seconds=None)

Bases: object

The deployment configuration for an endpoint, which contains the desired deployment strategy and rollback configurations.

Parameters:

  • auto_rollback_configuration (Union[IResolvable, Sequence[Union[IResolvable, AlarmDetailsProperty, Dict[str, Any]]], None]) – Automatic rollback configuration for handling endpoint deployment failures and recovery.

  • rolling_update_policy (Union[IResolvable, RollingUpdatePolicyProperty, Dict[str, Any], None]) – Specifies a rolling deployment strategy for updating a SageMaker endpoint.

  • wait_interval_in_seconds (Union[int, float, None]) – The duration in seconds that SageMaker waits before updating more instances in the cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-deploymentconfig.html

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

deployment_config_property = sagemaker.CfnCluster.DeploymentConfigProperty(
    auto_rollback_configuration=[sagemaker.CfnCluster.AlarmDetailsProperty(
        alarm_name="alarmName"
    )],
    rolling_update_policy=sagemaker.CfnCluster.RollingUpdatePolicyProperty(
        maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
            type="type",
            value=123
        ),

        # the properties below are optional
        rollback_maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
            type="type",
            value=123
        )
    ),
    wait_interval_in_seconds=123
)

Attributes

auto_rollback_configuration

Automatic rollback configuration for handling endpoint deployment failures and recovery.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-deploymentconfig.html#cfn-sagemaker-cluster-deploymentconfig-autorollbackconfiguration

rolling_update_policy

Specifies a rolling deployment strategy for updating a SageMaker endpoint.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-deploymentconfig.html#cfn-sagemaker-cluster-deploymentconfig-rollingupdatepolicy

wait_interval_in_seconds

The duration in seconds that SageMaker waits before updating more instances in the cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-deploymentconfig.html#cfn-sagemaker-cluster-deploymentconfig-waitintervalinseconds

EnvironmentConfigProperty

class CfnCluster.EnvironmentConfigProperty(*, f_sx_lustre_config=None)

Bases: object

The configuration for the restricted instance groups (RIG) environment.

Parameters:

f_sx_lustre_config (Union[IResolvable, FSxLustreConfigProperty, Dict[str, Any], None]) – Configuration settings for an Amazon FSx for Lustre file system to be used with the cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-environmentconfig.html

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

environment_config_property = sagemaker.CfnCluster.EnvironmentConfigProperty(
    f_sx_lustre_config=sagemaker.CfnCluster.FSxLustreConfigProperty(
        per_unit_storage_throughput=123,
        size_in_gi_b=123
    )
)

Attributes

f_sx_lustre_config

Configuration settings for an Amazon FSx for Lustre file system to be used with the cluster.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-environmentconfig.html#cfn-sagemaker-cluster-environmentconfig-fsxlustreconfig

FSxLustreConfigProperty

class CfnCluster.FSxLustreConfigProperty(*, per_unit_storage_throughput, size_in_gib)

Bases: object

Configuration settings for an Amazon FSx for Lustre file system to be used with the cluster.

Parameters:

  • per_unit_storage_throughput (Union[int, float]) – The throughput capacity of the Amazon FSx for Lustre file system, measured in MB/s per TiB of storage.

  • size_in_gib (Union[int, float]) – The storage capacity of the Amazon FSx for Lustre file system, specified in gibibytes (GiB).

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-fsxlustreconfig.html

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

f_sx_lustre_config_property = sagemaker.CfnCluster.FSxLustreConfigProperty(
    per_unit_storage_throughput=123,
    size_in_gi_b=123
)

Attributes

per_unit_storage_throughput

The throughput capacity of the Amazon FSx for Lustre file system, measured in MB/s per TiB of storage.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-fsxlustreconfig.html#cfn-sagemaker-cluster-fsxlustreconfig-perunitstoragethroughput

size_in_gib

The storage capacity of the Amazon FSx for Lustre file system, specified in gibibytes (GiB).

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-fsxlustreconfig.html#cfn-sagemaker-cluster-fsxlustreconfig-sizeingib

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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-orchestrator.html

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-orchestrator.html#cfn-sagemaker-cluster-orchestrator-eks

RollingUpdatePolicyProperty

class CfnCluster.RollingUpdatePolicyProperty(*, maximum_batch_size, rollback_maximum_batch_size=None)

Bases: object

Specifies a rolling deployment strategy for updating a SageMaker endpoint.

Parameters:

  • maximum_batch_size (Union[IResolvable, CapacitySizeConfigProperty, Dict[str, Any]]) – Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet. Value must be between 5% to 50% of the variant’s total instance count.

  • rollback_maximum_batch_size (Union[IResolvable, CapacitySizeConfigProperty, Dict[str, Any], None]) – Batch size for rollback to the old endpoint fleet. Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-rollingupdatepolicy.html

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

rolling_update_policy_property = sagemaker.CfnCluster.RollingUpdatePolicyProperty(
    maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
        type="type",
        value=123
    ),

    # the properties below are optional
    rollback_maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
        type="type",
        value=123
    )
)

Attributes

maximum_batch_size

Batch size for each rolling step to provision capacity and turn on traffic on the new endpoint fleet, and terminate capacity on the old endpoint fleet.

Value must be between 5% to 50% of the variant’s total instance count.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-rollingupdatepolicy.html#cfn-sagemaker-cluster-rollingupdatepolicy-maximumbatchsize

rollback_maximum_batch_size

Batch size for rollback to the old endpoint fleet.

Each rolling step to provision capacity and turn on traffic on the old endpoint fleet, and terminate capacity on the new endpoint fleet. If this field is absent, the default value will be set to 100% of total capacity which means to bring up the whole capacity of the old fleet at once during rollback.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-rollingupdatepolicy.html#cfn-sagemaker-cluster-rollingupdatepolicy-rollbackmaximumbatchsize

ScheduledUpdateConfigProperty

class CfnCluster.ScheduledUpdateConfigProperty(*, schedule_expression, deployment_config=None)

Bases: object

The configuration object of the schedule that SageMaker follows when updating the AMI.

Parameters:

  • schedule_expression (str) – A cron expression that specifies the schedule that SageMaker follows when updating the AMI.

  • deployment_config (Union[IResolvable, DeploymentConfigProperty, Dict[str, Any], None]) – The configuration to use when updating the AMI versions.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-scheduledupdateconfig.html

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

scheduled_update_config_property = sagemaker.CfnCluster.ScheduledUpdateConfigProperty(
    schedule_expression="scheduleExpression",

    # the properties below are optional
    deployment_config=sagemaker.CfnCluster.DeploymentConfigProperty(
        auto_rollback_configuration=[sagemaker.CfnCluster.AlarmDetailsProperty(
            alarm_name="alarmName"
        )],
        rolling_update_policy=sagemaker.CfnCluster.RollingUpdatePolicyProperty(
            maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                type="type",
                value=123
            ),

            # the properties below are optional
            rollback_maximum_batch_size=sagemaker.CfnCluster.CapacitySizeConfigProperty(
                type="type",
                value=123
            )
        ),
        wait_interval_in_seconds=123
    )
)

Attributes

deployment_config

The configuration to use when updating the AMI versions.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-scheduledupdateconfig.html#cfn-sagemaker-cluster-scheduledupdateconfig-deploymentconfig

schedule_expression

A cron expression that specifies the schedule that SageMaker follows when updating the AMI.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-scheduledupdateconfig.html#cfn-sagemaker-cluster-scheduledupdateconfig-scheduleexpression

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 form sg-xxxxxxxx . Specify the security groups for the VPC that is specified in the Subnets 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:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-vpcconfig.html

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.

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-vpcconfig.html#cfn-sagemaker-cluster-vpcconfig-securitygroupids

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 .

See:

http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-properties-sagemaker-cluster-vpcconfig.html#cfn-sagemaker-cluster-vpcconfig-subnets