The architecture provides scalability of compute, storage, and networking at the infrastructure layer, scalability of the control plane and runtime layers, and scalability of application workloads. Storage and compute are decoupled to support independent scaling, contingent upon application requirements. The network layer scales with infrastructure growth.
The architecture provides the flexibility to run multiple workloads on a single platform with resource management and operations management. Workloads can be containerized cloud native applications or can run in virtual machines.
The architecture also implements high-availability features at all levels. Redundant networking is used for the core platform, Elastic Cloud Storage (ECS), PowerScale storage, and ObjectScale storage. Cloud native workloads that are deployed on Kubernetes are replicated automatically when a node fails to match the original replica set requirement.
Overall, the architecture enables data analytics on structured, semistructured, and unstructured data on a single platform. It gives developers, data scientists, and data engineers a single interface for deployment of advanced analytic pipelines. It provides administrators with a production-grade platform that is based on the de facto standard Kubernetes ecosystem.