# AWS Batch adds quota management to share GPU capacity across SageMaker Training teams

> Original title: Lend and borrow resources across teams with AWS Batch’s quota management for SageMaker Training jobs

- Source: AWS Machine Learning Blog
- Published: 2026-10-29T16:58:57.000Z
- Bad Influence: https://badinfluence.news/items/kt6v63ezio84pls4v7uwlmwmg
- Original: https://aws.amazon.com/blogs/machine-learning/lend-and-borrow-resources-across-teams-with-aws-batchs-quota-management-for-sagemaker-training-jobs/

## Summary

AWS Batch now offers quota management for SageMaker Training jobs, letting administrators divide GPU capacity into quota shares by team or project. Each share sets a resource-sharing strategy (RESERVE, LEND, or LEND_AND_BORROW) and can turn on in-share preemption so higher-priority jobs run first. The post demonstrates the setup with the SageMaker Python SDK v3 using three shares, each capped at one ml.g5.xlarge instance.