Red Hat OpenShift Service on AWS supports Capacity Reservations and Capacity Blocks for Machine Learning

Red Hat OpenShift Service on AWS supports Capacity Reservations and Capacity Blocks for Machine Learning Red Hat OpenShift Container Platform | Product Trial About the authors Bala Chandrasekaran Brae Troutman More like this Optimize Cloud Costs with Red Hat OpenShift Virtualization and ROSA on AWS DxOperator from DH2i is now certified for Red Hat OpenShift 4.19 SREs on a plane | Technically Speaking Get started with ROSA Browse by channel Automation Artificial intelligence Open hybrid cloud Security Edge computing Infrastructure Applications Virtualization Share Red Hat OpenShift Service on AWS (ROSA) is a fully managed application platform that offers a more seamless experience for building, deploying, and scaling applications. For machine learning (ML) workloads, ROSA now supports On-Demand Capacity Reservations (ODCR) and Capacity Blocks for ML, allowing cloud architects and platform administrators to strategically utilize their existing AWS purchases to help deliver uninterrupted access to essential compute infrastructure. Today, ROSA is available in over 30 regions and supports over 600 instance types, allowing customers to run diverse workloads according to their business needs. However, maintaining guaranteed or uninterrupted access to a specific infrastructure type in a particular availability zone (AZ) is important for several critical scenarios: GPU-based accelerated computing workloads: Gaining uninterrupted access to accelerated computing (GPU) instances is vital for AI/ML teams conducting training, fine-tuning, or inference workloads. Capacity reservation helps eliminate the risk of compute unavailability for these time-sensitive, resource-intensive tasks. Planned scaling events: Enabling infrastructure scaling events to confidently support planned business events—such as peak traffic seasons, major product launches, or scheduled batch processing—without provisioning delays. High availability and disaster recovery: Enhancing resiliency by guaranteeing capacity when deploying workloads across multiple AZs or executing disaster recovery protocols across regions. Amazon EC2 Capacity Reservations allow you to reserve compute capacity for your Amazon EC2 instances in a specific AZ for any duration. Capacity Blocks for ML allow you to reserve GPU-based accelerated computing instances on a future date to support your short duration ML workloads. With the support for Capacity Reservations for clusters with hosted control planes (HCP), platform administrators can now create ROSA machine pools in their cluster that directly consume the capacity already reserved with AWS. Key best practices for effectively leveraging Capacity Reservations with ROSA: Pre-planning of AZs, instance types, and capacity: Before creation, ensure a precise match between the reserved capacity and the ROSA machine pool attributes. This includes VPC subnets, the number of node replicas, and the instance type.