SageMaker HyperPod now supports custom AMIs for Slurm clusters
Amazon SageMaker HyperPod now allows custom AMIs for Slurm-orchestrated clusters, simplifying the deployment of pre-configured, security-hardened environments for AI/ML workloads. This addresses challenges with complex lifecycle scripts, enabling faster startup times, improved reliability, and enhanced security compliance. The feature is available in all supported AWS Regions and can be specified via several SageMaker APIs.
- →Support for custom AMIs in SageMaker HyperPod Slurm clusters
- →Accelerate AI/ML training with pre-approved, secure environments
- →Integration with SageMaker APIs for cluster management
Features (1) ›
- Support for custom AMIs in SageMaker HyperPod Slurm clusters
SageMaker HyperPod now supports custom AMIs for Slurm-orchestrated clusters, enabling customers to deploy environments with pre-configured security, compliance, and operational requirements. This allows for faster cluster startup and improved reliability by embedding necessary tools and libraries directly into the image.
Enhancements (2) ›
- Accelerate AI/ML training with pre-approved, secure environments
Security teams can embed organizational policies into base images, allowing AI/ML teams to use pre-approved environments. This accelerates time-to-training while meeting enterprise security standards and reducing inconsistencies across cluster nodes.
- Integration with SageMaker APIs for cluster management
Customers can specify custom AMIs when creating new HyperPod Slurm clusters using the CreateCluster API, adding instance groups with the UpdateCluster API, or patching existing clusters with the UpdateClusterSoftware API. Custom AMIs must be built using HyperPod's public base AMIs for compatibility.
https://aws.amazon.com/about-aws/whats-new/2026/07/hyperpod-custom-ami-slurm/