Amazon SageMaker AI has introduced instance preference lists for its training and processing jobs. This new feature allows users to define an ordered list of instance types, and SageMaker AI will automatically launch the job on the first available type.
Key Points
- Amazon SageMaker AI now offers instance preference lists.
- These lists are available for both training and processing jobs.
- Users can specify an ordered list of up to five instance types.
- SageMaker AI automatically launches jobs on the first instance type with available capacity.
- This feature aims to eliminate manual retry loops and capacity-watching scripts.
Context
According to the AWS Machine Learning Blog, the introduction of instance preference lists in Amazon SageMaker AI addresses the operational challenge of securing compute capacity for AI workloads. This enhancement automates the process of finding available resources.
Why It Matters
This update simplifies the management of AI training and processing jobs for builders using Amazon SageMaker AI, potentially reducing delays and operational overhead associated with resource allocation.
What To Do
- Review the Amazon SageMaker AI documentation for details on configuring instance preference lists.
- Test the new feature with your existing training and processing jobs to evaluate its impact on job initiation times.
- Compare the efficiency gains against previous methods involving manual capacity checks or retry scripts.