Adds nodes to a HyperPod cluster by incrementing the target count for one or more instance groups. This operation returns a unique NodeLogicalId for each node being added, which can be used to track the provisioning status of the node. This API provides a safer alternative to UpdateCluster for scaling operations by avoiding unintended configuration changes.
This API is only supported for clusters using Continuous as the NodeProvisioningMode.
Parameters:
-
cluster_name
(ClusterNameOrArn)
–
The name of the HyperPod cluster to which you want to add nodes.
-
client_token
(Optional[String], default:
None
)
–
A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is valid for 8 hours. If you retry the request with the same client token within this timeframe and the same parameters, the API returns the same set of NodeLogicalIds with their latest status.
-
nodes_to_add
(Optional[AddClusterNodeSpecificationList], default:
None
)
–
A list of instance groups and the number of nodes to add to each. You can specify up to 5 instance groups in a single request, with a maximum of 50 nodes total across all instance groups.
Raises:
Source code in docs_src/capo_sagemaker/_services/sage_maker.py
| def batch_add_cluster_nodes(
self,
cluster_name: "capo_sagemaker.types.cluster_name_or_arn.ClusterNameOrArn",
*,
config_overrides: Optional[SageMakerClientConfig] = None,
client_token: Optional["capo_sagemaker.types.string.String"] = None,
nodes_to_add: Optional[
"capo_sagemaker.types.add_cluster_node_specification_list.AddClusterNodeSpecificationList"
] = None,
) -> "capo_sagemaker.types.batch_add_cluster_nodes_response.BatchAddClusterNodesResponse":
"""<p>Adds nodes to a HyperPod cluster by incrementing the target count for one or more instance groups. This operation returns a unique <code>NodeLogicalId</code> for each node being added, which can be used to track the provisioning status of the node. This API provides a safer alternative to <code>UpdateCluster</code> for scaling operations by avoiding unintended configuration changes.</p> <note> <p>This API is only supported for clusters using <code>Continuous</code> as the <code>NodeProvisioningMode</code>.</p> </note>
Args:
cluster_name: <p>The name of the HyperPod cluster to which you want to add nodes.</p>
client_token: <p>A unique, case-sensitive identifier that you provide to ensure the idempotency of the request. This token is valid for 8 hours. If you retry the request with the same client token within this timeframe and the same parameters, the API returns the same set of <code>NodeLogicalIds</code> with their latest status.</p>
nodes_to_add: <p>A list of instance groups and the number of nodes to add to each. You can specify up to 5 instance groups in a single request, with a maximum of 50 nodes total across all instance groups.</p>
Raises:
capo_sagemaker.errors.resource_limit_exceeded.ResourceLimitExceeded: <p> You have exceeded an SageMaker resource limit. For example, you might have too many training jobs created. </p>
capo_sagemaker.errors.resource_not_found.ResourceNotFound: <p>Resource being access is not found.</p>
capo_sagemaker.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_sagemaker.types.batch_add_cluster_nodes_request.BatchAddClusterNodesRequest]",
) -> OperationResponse[
"capo_sagemaker.types.batch_add_cluster_nodes_response.BatchAddClusterNodesResponse"
]:
import capo_sagemaker._operations.sage_maker.batch_add_cluster_nodes
output, http_response = (
capo_sagemaker._operations.sage_maker.batch_add_cluster_nodes.batch_add_cluster_nodes(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("BatchAddClusterNodes")
)
input_: capo_sagemaker.types.batch_add_cluster_nodes_request.BatchAddClusterNodesRequest = {
"cluster_name": cluster_name
}
if client_token is None:
client_token = str(uuid.uuid4())
input_["client_token"] = client_token
if nodes_to_add is not None:
input_["nodes_to_add"] = nodes_to_add
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|