AWS Batch now supports quota management and preemption for SageMaker Training jobs
News
This article announces AWS Batch quota management and preemption support for SageMaker Training jobs, enabling efficient GPU resource allocation and prioritization across teams.
- Create up to 20 quota shares per job queue with dedicated capacity limits
- Cross-share preemption automatically restores borrowed capacity to original owners
- In-share preemption allows high-priority jobs to preempt lower-priority jobs
- Monitor capacity utilization at queue, quota share, and job-level granularity
- Update job priorities after submission to influence preemption decisions
- Configure preemption retry limits to control preemption behavior
- Integrates directly with SageMaker Python SDK via aws_batch module
- Available in all AWS Regions where AWS Batch is supported
This feature enables teams to efficiently share GPU resources while prioritizing business-critical training jobs through intelligent preemption and quota management.
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