Posted by NetApp on January 24, 2019:

Standards are ubiquitous in all areas of our lives. Sometimes it seems as if it’s always been that way.  In fact, standards evolve over time. One standard that comes to mind is electricity. Today we rarely think about electricity, but it wasn’t always that way. Over time, mechanical power gave way to on-premises electrical power to centralized generation over standard voltages and frequencies. Today, we simply plug in without giving it a second thought. The voltage, frequency, and receptacles are all standardized.  Appliance makers only worry about the interface, not the generation. For the most part, electricity is very reliable; it’s always on. Electrical outlets allow us to plug in almost without thought. Thanks to standardization, new computers, appliances, servers, and phones can tap seamlessly into the electrical grid.

Like electricity, the FlexPod® converged infrastructure solution from NetApp and Cisco is becoming a standard. What makes a converged infrastructure a standard? It would be an industry leader, able to handle nearly all workloads, including different versions of applications. It would have a long history of growth and be built on existing standards and standard processes. And it would be growing and evolving to handle new workloads and technologies.

Cisco is voicing their support as are partners on FlexPod for AI:

Bob Olwig, Vice President of Corporate Business Development, WWT

“WWT is excited to partner with NetApp as they launch a disruptive solution that provides systems integrators like WWT with a compelling solution to address the exploding AI/ML segment and cloud connected CI or the Data Fabric that our customers expect from us. FlexPod is a trusted platform that combines a unified management and unified fabric with best-of-breed compute, network, storage, and management products into an easy-to-deploy architecture., “FlexPod is a trusted and proven architecture from NetApp and Cisco that complements WWT’s broad portfolio of solutions and services for deep learning, giving customers an AI stack that can be implemented quickly with extreme efficiency and reduce any risk.”

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