start_cluster_health_check `async` ¶

start_cluster_health_check(
    cluster_name: ClusterNameOrArn,
    deep_health_check_configurations: DeepHealthCheckConfigurations,
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
) -> StartClusterHealthCheckResponse

Start deep health checks for a SageMaker HyperPod cluster. You can use DescribeClusterNode API to track progress of the deep health checks. The unhealthy nodes will be automatically rebooted or replaced. Please see Resilience-related Kubernetes labels by SageMaker HyperPod for details.

Parameters:

cluster_name (ClusterNameOrArn) –

The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.
deep_health_check_configurations (DeepHealthCheckConfigurations) –

A list of configurations containing instance group names, EC2 instance IDs, and deep health checks to perform.

Raises:

ResourceNotFound –

Resource being access is not found.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_sagemaker/_services/async_sage_maker.py

async def start_cluster_health_check(
    self,
    cluster_name: "capo_sagemaker.types.cluster_name_or_arn.ClusterNameOrArn",
    deep_health_check_configurations: "capo_sagemaker.types.deep_health_check_configurations.DeepHealthCheckConfigurations",
    *,
    config_overrides: Optional[AsyncSageMakerClientConfig] = None,
) -> "capo_sagemaker.types.start_cluster_health_check_response.StartClusterHealthCheckResponse":
    """<p>Start deep health checks for a SageMaker HyperPod cluster. You can use <a href="https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_DescribeClusterNode.html">DescribeClusterNode</a> API to track progress of the deep health checks. The unhealthy nodes will be automatically rebooted or replaced. Please see <a href="https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-hyperpod-eks-resiliency-node-labels.html"> Resilience-related Kubernetes labels by SageMaker HyperPod</a> for details.</p>

    Args:
        cluster_name: <p>The string name or the Amazon Resource Name (ARN) of the SageMaker HyperPod cluster.</p>
        deep_health_check_configurations: <p>A list of configurations containing instance group names, EC2 instance IDs, and deep health checks to perform.</p>

    Raises:
        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.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_sagemaker.types.start_cluster_health_check_request.StartClusterHealthCheckRequest]",
    ) -> AsyncOperationResponse[
        "capo_sagemaker.types.start_cluster_health_check_response.StartClusterHealthCheckResponse"
    ]:
        import capo_sagemaker._operations.sage_maker.start_cluster_health_check

        (
            output,
            http_response,
        ) = await capo_sagemaker._operations.sage_maker.start_cluster_health_check.async_start_cluster_health_check(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("StartClusterHealthCheck")
    )
    input_: capo_sagemaker.types.start_cluster_health_check_request.StartClusterHealthCheckRequest = {
        "cluster_name": cluster_name,
        "deep_health_check_configurations": deep_health_check_configurations,
    }

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output

start_cluster_health_check async ¶

start_cluster_health_check `async` ¶