Amazon SageMaker HyperPod now features managed node automatic scaling, thanks to the integration with Karpenter. This new capability empowers users to efficiently scale their SageMaker HyperPod clusters, adapting seamlessly to both inference and training workloads.
Key Benefits of Karpenter Integration
Karpenter is a powerful open-source Kubernetes cluster autoscaler that automatically provisions and manages compute resources based on real-time demand. By integrating Karpenter with SageMaker HyperPod, you can dynamically scale clusters up or down, optimizing both performance and cost. This means your infrastructure automatically matches your ML workloads, ensuring you never overpay for unused resources.
How to Enable and Configure Karpenter
Setting up Karpenter in your SageMaker HyperPod EKS clusters is straightforward. The integration offers detailed configuration options, allowing you to tailor auto scaling behavior according to your specific needs. AWS provides comprehensive documentation to guide you through enabling and customizing Karpenter within your environment.
Auto scaling with Karpenter marks a significant leap for SageMaker HyperPod users, delivering unmatched flexibility, efficiency, and cost savings.
Sources:
https://aws.amazon.com/blogs/machine-learning/introducing-auto-scaling-on-amazon-sagemaker-hyperpod/
