Samsung SDS Engineers Share Declarative Underlay Clusters for OpenStack Using Cluster API on PyTorch Channel
HanSol Park and Kangsub Song from Samsung SDS published a video on the official PyTorch channel introducing how to use Cluster API to create and manage declarative underlay clusters for OpenStack. The architecture aims to isolate specialized hardware such as AI/GPU nodes into different clusters and support dynamic resource rebalancing on demand, delivering cloud-native agility at the physical layer.
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HanSol Park and Kangsub Song from Samsung SDS published a video titled "Declarative Underlays: Scaling Purpose-Built Infrastructure(Clusters) for OpenStack with Cluster API" on the official PyTorch channel on September 24, 2026. The session focuses on a production-proven architecture exploring further integration between the OpenStack and Kubernetes ecosystems.
According to the official episode description, the speakers introduced leveraging Cluster API (CAPI) to declaratively create and manage clusters tuned for specific hardware or software needs, such as AI clusters with GPUs, high-speed networking clusters, and dedicated storage. The core of this architecture is treating the underlay as a set of clusters that can be re-balanced on demand, delivering true cloud-native agility to the physical layer.
Specific technical points listed in the episode include repeatable, version-controlled provisioning for declarative underlay clusters; isolating specialized hardware into separate clusters without interfering with other workloads; dynamically rebalancing resources by migrating idle GPU nodes between clusters; integrating OpenStack services; and sharing lessons learned and best-practice patterns for operating at multi-region scale.