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// Code generated by software.amazon.smithy.rust.codegen.smithy-rs. DO NOT EDIT.
pub use crate::operation::create_cluster::_create_cluster_input::CreateClusterInputBuilder;
pub use crate::operation::create_cluster::_create_cluster_output::CreateClusterOutputBuilder;
impl crate::operation::create_cluster::builders::CreateClusterInputBuilder {
/// Sends a request with this input using the given client.
pub async fn send_with(
self,
client: &crate::Client,
) -> ::std::result::Result<
crate::operation::create_cluster::CreateClusterOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_cluster::CreateClusterError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let mut fluent_builder = client.create_cluster();
fluent_builder.inner = self;
fluent_builder.send().await
}
}
/// Fluent builder constructing a request to `CreateCluster`.
///
/// <p>Creates an Amazon 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 <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod.html">Amazon SageMaker HyperPod</a> in the <i>Amazon SageMaker Developer Guide</i>.</p>
#[derive(::std::clone::Clone, ::std::fmt::Debug)]
pub struct CreateClusterFluentBuilder {
handle: ::std::sync::Arc<crate::client::Handle>,
inner: crate::operation::create_cluster::builders::CreateClusterInputBuilder,
config_override: ::std::option::Option<crate::config::Builder>,
}
impl
crate::client::customize::internal::CustomizableSend<
crate::operation::create_cluster::CreateClusterOutput,
crate::operation::create_cluster::CreateClusterError,
> for CreateClusterFluentBuilder
{
fn send(
self,
config_override: crate::config::Builder,
) -> crate::client::customize::internal::BoxFuture<
crate::client::customize::internal::SendResult<
crate::operation::create_cluster::CreateClusterOutput,
crate::operation::create_cluster::CreateClusterError,
>,
> {
::std::boxed::Box::pin(async move { self.config_override(config_override).send().await })
}
}
impl CreateClusterFluentBuilder {
/// Creates a new `CreateClusterFluentBuilder`.
pub(crate) fn new(handle: ::std::sync::Arc<crate::client::Handle>) -> Self {
Self {
handle,
inner: ::std::default::Default::default(),
config_override: ::std::option::Option::None,
}
}
/// Access the CreateCluster as a reference.
pub fn as_input(&self) -> &crate::operation::create_cluster::builders::CreateClusterInputBuilder {
&self.inner
}
/// Sends the request and returns the response.
///
/// If an error occurs, an `SdkError` will be returned with additional details that
/// can be matched against.
///
/// By default, any retryable failures will be retried twice. Retry behavior
/// is configurable with the [RetryConfig](aws_smithy_types::retry::RetryConfig), which can be
/// set when configuring the client.
pub async fn send(
self,
) -> ::std::result::Result<
crate::operation::create_cluster::CreateClusterOutput,
::aws_smithy_runtime_api::client::result::SdkError<
crate::operation::create_cluster::CreateClusterError,
::aws_smithy_runtime_api::client::orchestrator::HttpResponse,
>,
> {
let input = self
.inner
.build()
.map_err(::aws_smithy_runtime_api::client::result::SdkError::construction_failure)?;
let runtime_plugins = crate::operation::create_cluster::CreateCluster::operation_runtime_plugins(
self.handle.runtime_plugins.clone(),
&self.handle.conf,
self.config_override,
);
crate::operation::create_cluster::CreateCluster::orchestrate(&runtime_plugins, input).await
}
/// Consumes this builder, creating a customizable operation that can be modified before being sent.
pub fn customize(
self,
) -> crate::client::customize::CustomizableOperation<
crate::operation::create_cluster::CreateClusterOutput,
crate::operation::create_cluster::CreateClusterError,
Self,
> {
crate::client::customize::CustomizableOperation::new(self)
}
pub(crate) fn config_override(mut self, config_override: impl ::std::convert::Into<crate::config::Builder>) -> Self {
self.set_config_override(::std::option::Option::Some(config_override.into()));
self
}
pub(crate) fn set_config_override(&mut self, config_override: ::std::option::Option<crate::config::Builder>) -> &mut Self {
self.config_override = config_override;
self
}
/// <p>The name for the new SageMaker HyperPod cluster.</p>
pub fn cluster_name(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.cluster_name(input.into());
self
}
/// <p>The name for the new SageMaker HyperPod cluster.</p>
pub fn set_cluster_name(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_cluster_name(input);
self
}
/// <p>The name for the new SageMaker HyperPod cluster.</p>
pub fn get_cluster_name(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_cluster_name()
}
///
/// Appends an item to `InstanceGroups`.
///
/// To override the contents of this collection use [`set_instance_groups`](Self::set_instance_groups).
///
/// <p>The instance groups to be created in the SageMaker HyperPod cluster.</p>
pub fn instance_groups(mut self, input: crate::types::ClusterInstanceGroupSpecification) -> Self {
self.inner = self.inner.instance_groups(input);
self
}
/// <p>The instance groups to be created in the SageMaker HyperPod cluster.</p>
pub fn set_instance_groups(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::ClusterInstanceGroupSpecification>>) -> Self {
self.inner = self.inner.set_instance_groups(input);
self
}
/// <p>The instance groups to be created in the SageMaker HyperPod cluster.</p>
pub fn get_instance_groups(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::ClusterInstanceGroupSpecification>> {
self.inner.get_instance_groups()
}
///
/// Appends an item to `RestrictedInstanceGroups`.
///
/// To override the contents of this collection use [`set_restricted_instance_groups`](Self::set_restricted_instance_groups).
///
/// <p>The specialized instance groups for training models like Amazon Nova to be created in the SageMaker HyperPod cluster.</p>
pub fn restricted_instance_groups(mut self, input: crate::types::ClusterRestrictedInstanceGroupSpecification) -> Self {
self.inner = self.inner.restricted_instance_groups(input);
self
}
/// <p>The specialized instance groups for training models like Amazon Nova to be created in the SageMaker HyperPod cluster.</p>
pub fn set_restricted_instance_groups(
mut self,
input: ::std::option::Option<::std::vec::Vec<crate::types::ClusterRestrictedInstanceGroupSpecification>>,
) -> Self {
self.inner = self.inner.set_restricted_instance_groups(input);
self
}
/// <p>The specialized instance groups for training models like Amazon Nova to be created in the SageMaker HyperPod cluster.</p>
pub fn get_restricted_instance_groups(
&self,
) -> &::std::option::Option<::std::vec::Vec<crate::types::ClusterRestrictedInstanceGroupSpecification>> {
self.inner.get_restricted_instance_groups()
}
/// <p>Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You can control access to and from your resources by configuring your VPC. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html">Give SageMaker access to resources in your Amazon VPC</a>.</p><note>
/// <p>When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:</p>
/// <ul>
/// <li>
/// <p>Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.</p></li>
/// <li>
/// <p>In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see <a href="https://docs.aws.amazon.com/eks/latest/userguide/deploy-ipv6-cluster.html#_deploy_an_ipv6_cluster_with_eksctl">Amazon EKS IPv6 Cluster Deployment</a>.</p></li>
/// </ul>
/// <p>Additional resources for IPv6 configuration:</p>
/// <ul>
/// <li>
/// <p>For information about adding IPv6 support to your VPC, see to <a href="https://docs.aws.amazon.com/vpc/latest/userguide/vpc-migrate-ipv6.html">IPv6 Support for VPC</a>.</p></li>
/// <li>
/// <p>For information about creating a new IPv6-compatible VPC, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/create-vpc.html">Amazon VPC Creation Guide</a>.</p></li>
/// <li>
/// <p>To configure SageMaker HyperPod with a custom Amazon VPC, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-prerequisites.html#sagemaker-hyperpod-prerequisites-optional-vpc">Custom Amazon VPC Setup for SageMaker HyperPod</a>.</p></li>
/// </ul>
/// </note>
pub fn vpc_config(mut self, input: crate::types::VpcConfig) -> Self {
self.inner = self.inner.vpc_config(input);
self
}
/// <p>Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You can control access to and from your resources by configuring your VPC. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html">Give SageMaker access to resources in your Amazon VPC</a>.</p><note>
/// <p>When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:</p>
/// <ul>
/// <li>
/// <p>Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.</p></li>
/// <li>
/// <p>In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see <a href="https://docs.aws.amazon.com/eks/latest/userguide/deploy-ipv6-cluster.html#_deploy_an_ipv6_cluster_with_eksctl">Amazon EKS IPv6 Cluster Deployment</a>.</p></li>
/// </ul>
/// <p>Additional resources for IPv6 configuration:</p>
/// <ul>
/// <li>
/// <p>For information about adding IPv6 support to your VPC, see to <a href="https://docs.aws.amazon.com/vpc/latest/userguide/vpc-migrate-ipv6.html">IPv6 Support for VPC</a>.</p></li>
/// <li>
/// <p>For information about creating a new IPv6-compatible VPC, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/create-vpc.html">Amazon VPC Creation Guide</a>.</p></li>
/// <li>
/// <p>To configure SageMaker HyperPod with a custom Amazon VPC, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-prerequisites.html#sagemaker-hyperpod-prerequisites-optional-vpc">Custom Amazon VPC Setup for SageMaker HyperPod</a>.</p></li>
/// </ul>
/// </note>
pub fn set_vpc_config(mut self, input: ::std::option::Option<crate::types::VpcConfig>) -> Self {
self.inner = self.inner.set_vpc_config(input);
self
}
/// <p>Specifies the Amazon Virtual Private Cloud (VPC) that is associated with the Amazon SageMaker HyperPod cluster. You can control access to and from your resources by configuring your VPC. For more information, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/infrastructure-give-access.html">Give SageMaker access to resources in your Amazon VPC</a>.</p><note>
/// <p>When your Amazon VPC and subnets support IPv6, network communications differ based on the cluster orchestration platform:</p>
/// <ul>
/// <li>
/// <p>Slurm-orchestrated clusters automatically configure nodes with dual IPv6 and IPv4 addresses, allowing immediate IPv6 network communications.</p></li>
/// <li>
/// <p>In Amazon EKS-orchestrated clusters, nodes receive dual-stack addressing, but pods can only use IPv6 when the Amazon EKS cluster is explicitly IPv6-enabled. For information about deploying an IPv6 Amazon EKS cluster, see <a href="https://docs.aws.amazon.com/eks/latest/userguide/deploy-ipv6-cluster.html#_deploy_an_ipv6_cluster_with_eksctl">Amazon EKS IPv6 Cluster Deployment</a>.</p></li>
/// </ul>
/// <p>Additional resources for IPv6 configuration:</p>
/// <ul>
/// <li>
/// <p>For information about adding IPv6 support to your VPC, see to <a href="https://docs.aws.amazon.com/vpc/latest/userguide/vpc-migrate-ipv6.html">IPv6 Support for VPC</a>.</p></li>
/// <li>
/// <p>For information about creating a new IPv6-compatible VPC, see <a href="https://docs.aws.amazon.com/vpc/latest/userguide/create-vpc.html">Amazon VPC Creation Guide</a>.</p></li>
/// <li>
/// <p>To configure SageMaker HyperPod with a custom Amazon VPC, see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-prerequisites.html#sagemaker-hyperpod-prerequisites-optional-vpc">Custom Amazon VPC Setup for SageMaker HyperPod</a>.</p></li>
/// </ul>
/// </note>
pub fn get_vpc_config(&self) -> &::std::option::Option<crate::types::VpcConfig> {
self.inner.get_vpc_config()
}
///
/// Appends an item to `Tags`.
///
/// To override the contents of this collection use [`set_tags`](Self::set_tags).
///
/// <p>Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see <a href="https://docs.aws.amazon.com/tag-editor/latest/userguide/tagging.html">Tagging Amazon Web Services Resources User Guide</a>.</p>
pub fn tags(mut self, input: crate::types::Tag) -> Self {
self.inner = self.inner.tags(input);
self
}
/// <p>Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see <a href="https://docs.aws.amazon.com/tag-editor/latest/userguide/tagging.html">Tagging Amazon Web Services Resources User Guide</a>.</p>
pub fn set_tags(mut self, input: ::std::option::Option<::std::vec::Vec<crate::types::Tag>>) -> Self {
self.inner = self.inner.set_tags(input);
self
}
/// <p>Custom tags for managing the SageMaker HyperPod cluster as an Amazon Web Services resource. You can add tags to your cluster in the same way you add them in other Amazon Web Services services that support tagging. To learn more about tagging Amazon Web Services resources in general, see <a href="https://docs.aws.amazon.com/tag-editor/latest/userguide/tagging.html">Tagging Amazon Web Services Resources User Guide</a>.</p>
pub fn get_tags(&self) -> &::std::option::Option<::std::vec::Vec<crate::types::Tag>> {
self.inner.get_tags()
}
/// <p>The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, supported values are <code>"Eks"</code> and <code>"Slurm"</code>, which is to use an Amazon Elastic Kubernetes Service or Slurm cluster as the orchestrator.</p><note>
/// <p>If you specify the <code>Orchestrator</code> field, you must provide exactly one orchestrator configuration: either <code>Eks</code> or <code>Slurm</code>. Specifying both or providing an empty configuration returns a validation error.</p>
/// </note>
pub fn orchestrator(mut self, input: crate::types::ClusterOrchestrator) -> Self {
self.inner = self.inner.orchestrator(input);
self
}
/// <p>The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, supported values are <code>"Eks"</code> and <code>"Slurm"</code>, which is to use an Amazon Elastic Kubernetes Service or Slurm cluster as the orchestrator.</p><note>
/// <p>If you specify the <code>Orchestrator</code> field, you must provide exactly one orchestrator configuration: either <code>Eks</code> or <code>Slurm</code>. Specifying both or providing an empty configuration returns a validation error.</p>
/// </note>
pub fn set_orchestrator(mut self, input: ::std::option::Option<crate::types::ClusterOrchestrator>) -> Self {
self.inner = self.inner.set_orchestrator(input);
self
}
/// <p>The type of orchestrator to use for the SageMaker HyperPod cluster. Currently, supported values are <code>"Eks"</code> and <code>"Slurm"</code>, which is to use an Amazon Elastic Kubernetes Service or Slurm cluster as the orchestrator.</p><note>
/// <p>If you specify the <code>Orchestrator</code> field, you must provide exactly one orchestrator configuration: either <code>Eks</code> or <code>Slurm</code>. Specifying both or providing an empty configuration returns a validation error.</p>
/// </note>
pub fn get_orchestrator(&self) -> &::std::option::Option<crate::types::ClusterOrchestrator> {
self.inner.get_orchestrator()
}
/// <p>The node recovery mode for the SageMaker HyperPod cluster. When set to <code>Automatic</code>, SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set to <code>None</code>, cluster administrators will need to manually manage any faulty cluster instances.</p>
pub fn node_recovery(mut self, input: crate::types::ClusterNodeRecovery) -> Self {
self.inner = self.inner.node_recovery(input);
self
}
/// <p>The node recovery mode for the SageMaker HyperPod cluster. When set to <code>Automatic</code>, SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set to <code>None</code>, cluster administrators will need to manually manage any faulty cluster instances.</p>
pub fn set_node_recovery(mut self, input: ::std::option::Option<crate::types::ClusterNodeRecovery>) -> Self {
self.inner = self.inner.set_node_recovery(input);
self
}
/// <p>The node recovery mode for the SageMaker HyperPod cluster. When set to <code>Automatic</code>, SageMaker HyperPod will automatically reboot or replace faulty nodes when issues are detected. When set to <code>None</code>, cluster administrators will need to manually manage any faulty cluster instances.</p>
pub fn get_node_recovery(&self) -> &::std::option::Option<crate::types::ClusterNodeRecovery> {
self.inner.get_node_recovery()
}
/// <p>The configuration for managed tier checkpointing on the HyperPod cluster. When enabled, this feature uses a multi-tier storage approach for storing model checkpoints, providing faster checkpoint operations and improved fault tolerance across cluster nodes.</p>
pub fn tiered_storage_config(mut self, input: crate::types::ClusterTieredStorageConfig) -> Self {
self.inner = self.inner.tiered_storage_config(input);
self
}
/// <p>The configuration for managed tier checkpointing on the HyperPod cluster. When enabled, this feature uses a multi-tier storage approach for storing model checkpoints, providing faster checkpoint operations and improved fault tolerance across cluster nodes.</p>
pub fn set_tiered_storage_config(mut self, input: ::std::option::Option<crate::types::ClusterTieredStorageConfig>) -> Self {
self.inner = self.inner.set_tiered_storage_config(input);
self
}
/// <p>The configuration for managed tier checkpointing on the HyperPod cluster. When enabled, this feature uses a multi-tier storage approach for storing model checkpoints, providing faster checkpoint operations and improved fault tolerance across cluster nodes.</p>
pub fn get_tiered_storage_config(&self) -> &::std::option::Option<crate::types::ClusterTieredStorageConfig> {
self.inner.get_tiered_storage_config()
}
/// <p>The mode for provisioning nodes in the cluster. You can specify the following modes:</p>
/// <ul>
/// <li>
/// <p><b>Continuous</b>: Scaling behavior that enables 1) concurrent operation execution within instance groups, 2) continuous retry mechanisms for failed operations, 3) enhanced customer visibility into cluster events through detailed event streams, 4) partial provisioning capabilities. Your clusters and instance groups remain <code>InService</code> while scaling. This mode is only supported for EKS orchestrated clusters.</p></li>
/// </ul>
pub fn node_provisioning_mode(mut self, input: crate::types::ClusterNodeProvisioningMode) -> Self {
self.inner = self.inner.node_provisioning_mode(input);
self
}
/// <p>The mode for provisioning nodes in the cluster. You can specify the following modes:</p>
/// <ul>
/// <li>
/// <p><b>Continuous</b>: Scaling behavior that enables 1) concurrent operation execution within instance groups, 2) continuous retry mechanisms for failed operations, 3) enhanced customer visibility into cluster events through detailed event streams, 4) partial provisioning capabilities. Your clusters and instance groups remain <code>InService</code> while scaling. This mode is only supported for EKS orchestrated clusters.</p></li>
/// </ul>
pub fn set_node_provisioning_mode(mut self, input: ::std::option::Option<crate::types::ClusterNodeProvisioningMode>) -> Self {
self.inner = self.inner.set_node_provisioning_mode(input);
self
}
/// <p>The mode for provisioning nodes in the cluster. You can specify the following modes:</p>
/// <ul>
/// <li>
/// <p><b>Continuous</b>: Scaling behavior that enables 1) concurrent operation execution within instance groups, 2) continuous retry mechanisms for failed operations, 3) enhanced customer visibility into cluster events through detailed event streams, 4) partial provisioning capabilities. Your clusters and instance groups remain <code>InService</code> while scaling. This mode is only supported for EKS orchestrated clusters.</p></li>
/// </ul>
pub fn get_node_provisioning_mode(&self) -> &::std::option::Option<crate::types::ClusterNodeProvisioningMode> {
self.inner.get_node_provisioning_mode()
}
/// <p>The Amazon Resource Name (ARN) of the IAM role that HyperPod assumes to perform cluster autoscaling operations. This role must have permissions for <code>sagemaker:BatchAddClusterNodes</code> and <code>sagemaker:BatchDeleteClusterNodes</code>. This is only required when autoscaling is enabled and when HyperPod is performing autoscaling operations.</p>
pub fn cluster_role(mut self, input: impl ::std::convert::Into<::std::string::String>) -> Self {
self.inner = self.inner.cluster_role(input.into());
self
}
/// <p>The Amazon Resource Name (ARN) of the IAM role that HyperPod assumes to perform cluster autoscaling operations. This role must have permissions for <code>sagemaker:BatchAddClusterNodes</code> and <code>sagemaker:BatchDeleteClusterNodes</code>. This is only required when autoscaling is enabled and when HyperPod is performing autoscaling operations.</p>
pub fn set_cluster_role(mut self, input: ::std::option::Option<::std::string::String>) -> Self {
self.inner = self.inner.set_cluster_role(input);
self
}
/// <p>The Amazon Resource Name (ARN) of the IAM role that HyperPod assumes to perform cluster autoscaling operations. This role must have permissions for <code>sagemaker:BatchAddClusterNodes</code> and <code>sagemaker:BatchDeleteClusterNodes</code>. This is only required when autoscaling is enabled and when HyperPod is performing autoscaling operations.</p>
pub fn get_cluster_role(&self) -> &::std::option::Option<::std::string::String> {
self.inner.get_cluster_role()
}
/// <p>The autoscaling configuration for the cluster. Enables automatic scaling of cluster nodes based on workload demand using a Karpenter-based system.</p>
pub fn auto_scaling(mut self, input: crate::types::ClusterAutoScalingConfig) -> Self {
self.inner = self.inner.auto_scaling(input);
self
}
/// <p>The autoscaling configuration for the cluster. Enables automatic scaling of cluster nodes based on workload demand using a Karpenter-based system.</p>
pub fn set_auto_scaling(mut self, input: ::std::option::Option<crate::types::ClusterAutoScalingConfig>) -> Self {
self.inner = self.inner.set_auto_scaling(input);
self
}
/// <p>The autoscaling configuration for the cluster. Enables automatic scaling of cluster nodes based on workload demand using a Karpenter-based system.</p>
pub fn get_auto_scaling(&self) -> &::std::option::Option<crate::types::ClusterAutoScalingConfig> {
self.inner.get_auto_scaling()
}
}