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Qumulo Data Platform Embraces Next-Gen of Networking

Collaborates with Arista Networks, Intel and joins Ultra Ethernet Consortium.

Qumulo, Inc. became the first networked storage supplier to join the Ultra Ethernet Consortium.

Ultra Ethernet Consortium

Additionally, it announced a collaboration with Intel Corporation and Arista Networks to advance the state-of-the-art in IT infrastructure at the intersection of networking, storage, and data management. These technologies enhance the performance and operations of firm’s Scale Anywhere Data Management platform from the edge to the data center to the public cloud delivering valuable operational benefits to data center, network, and storage operators.

The Ultra Ethernet Consortium’s work will shape the way data flows across the network, bringing systems, storage, and networks closer together while simplifying architectures with massive performance and reliability improvements,” stated Kiran Bhageshpur, CTO. “Coupling UEC’s forthcoming enhancements with today’s development and execution with data center switching leader Arista Networks in hundreds of production real-world scale anywhere primary storage systems reshapes what is possible in data management for the enterprise.”

Qumulo has deployed over an exabyte of storage across hundreds of customers jointly with Arista Networks EOS-based switching and routing systems. Benefiting from Arista’s buffer architecture in the 7280/7800 series and proven leaf/spine architecture, Qumulo customers are delivering primary enterprise storage at terabyte-through-exabyte scale on a converged network, eliminating costly legacy storage networks.

Our UC San Diego customers require dedicated networks for storage interconnect, based on a standard ethernet infrastructure at up to 200Gb/s of provisioned performance. The Data Science Machine Learning Platform (DSMLP) runs on Qumulo, where thousands of students execute performance-sensitive AI workloads concurrently. These students require optimal configurations to ensure efficiency when running GPUs over thousands of NFS connections,” said Brian Balderston, director of infrastructure, San Diego Supercomputer Center. “With an Arista deep buffer leaf-and-spine and Qumulo Scale Anywhere data management, we are able to segment performance required for the DSMLP, lower costs, and deliver a common filesystem for other student organizations as well.”

Key to improving performance is not just using the right vendors with modernized architectures but also material product integration that delivers operational value, simplifying configuration and troubleshooting while also leveraging each IT technology’s strengths and capabilities appropriately. The result is a consistent primary storage system that is utilized across the enterprise for critical business systems, SIEM systems, backups, training and inference in AI workloads, and large-scale distributed systems and applications in the data center and cloud.

As we develop high performance and scale networks for the largest AI pods on open and interoperable IP and Ethernet protocols, the evolution to Ultra Ethernet is to simplify the network and bring compute, AI processing, and storage together,” said Ed Chapman, VP business development and strategic alliances, Arista Networks. “Qumulo joining the UEC is further validation that Ethernet and IP are the right foundation for the next gen of general purpose, cloud, and AI computing and storage.”

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