The networking demands of big data analytics, flash-based and scale out storage, and hyper-converged compute solutions are driving a migration from legacy fibre channel to next generation IP-based storage networks. These next generation storage applications require an open, programmable, lossless and highly available IP storage networking solution in order to support their unique traffic patterns.
The drive to develop and deliver innovative products and services in the future will be fueled increasingly by companies' ability to acquire and analyze vast amounts of structured and un-structured data.
Large and small enterprises are racing to acquire this capability by leveraging the vast computing power of the public cloud and by re-engineering their datacenters into private clouds.
Big Data provides a tremendous help to organizations making critical decisions that drive their businesses. At the same time, Big Data requires storing and efficiently processing terabytes or exabytes of unstructured data, which creates an extraordinary challenge for CTOs and Network Operators, requiring new and innovative technologies.
The Big Data framework is comprised of distributed file systems, databases, and data mining algorithms. For a successful implementation, Big Data deployments require a highly scalable, high-performance, and easy to manage interconnect, advanced turnkey management solutions, and familiar visualization tools.
With up to 32GB of dynamic buffer memory the Arista 7280R Universal Leaf platform complements the Arista 7500R Universal Spine to meet the IP/Ethernet storage challenge of massive east to west traffic by delivering a compelling IP Storage networking solution. This includes deterministic latency characteristics, any-to-any non-blocking host communication, open programmability via EOS and deep packet buffers capable of absorbing the largest of storage IO bursts and traffic patterns.
Arista Networks Storage networking solutions enable an organization to build clusters that keep up with the growth in data, minimize operational expenses, and deliver sophisticated data analytics.