Module Smaws_Client_SageMaker.CreateTrainingPlan

Creates a new training plan in SageMaker to reserve compute capacity.

Amazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU capacity for large-scale AI model training. It provides a way to secure predictable access to computational resources within specific timelines and budgets, without the need to manage underlying infrastructure.

How it works

Plans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod clusters, automatically provisioning resources, setting up infrastructure, executing workloads, and handling infrastructure failures.

Plan creation workflow

Plan composition

A plan can consist of one or more Reserved Capacities, each defined by a specific instance type, quantity, Availability Zone, duration, and start and end times. For more information about Reserved Capacity, see

 {{:https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_ReservedCapacitySummary.html}ReservedCapacitySummary} 

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val error_to_string : [ Smaws_Lib.Protocols.AwsJson.error | `ResourceInUse of Types.resource_in_use | `ResourceLimitExceeded of Types.resource_limit_exceeded | `ResourceNotFound of Types.resource_not_found ] -> string
val request : 'http_type Smaws_Lib.Context.t -> Types.create_training_plan_request -> (Types.create_training_plan_response, [> Smaws_Lib.Protocols.AwsJson.error | `ResourceInUse of Types.resource_in_use | `ResourceLimitExceeded of Types.resource_limit_exceeded | `ResourceNotFound of Types.resource_not_found ]) Stdlib.result