5 Key Ingredients of an Enterprise Edge Computing Infrastructure

Three experts tell us what an enterprise needs to make edge computing infrastructure practical and profitable.

Scott Fulton III, Contributor

April 19, 2019

1 Min Read
5 Key Ingredients of an Enterprise Edge Computing Infrastructure

You often hear that there’s more than one edge to a data center network. That’s not all that helpful when you’re an enterprise deciding whether building out your processing, storage and networking assets closer to your customers or communications providers makes sense in terms of cost or quality-of-service.

So, we spoke to three leaders in three different product spaces related to edge equipment: Dell EMC for edge servers, Vapor IO for micro data center chasses, and Schneider Electric for power and service resilience. We heard everything there is to hear about the various edges cropping up in the modern data center configuration and distilled here the common elements in all of their perspectives, isolating five things they perceive as critical to the composition of effective data centers at the edge of enterprise networks.

1. Fast, resilient storage

It wouldn’t make sense to build out archival storage at the edge. But the types of applications for which edge computing makes the most sense requires more addressable data space than even the largest tiers of DRAM would allow — for example, multimedia caching for Web applications geared around rich customer experience (outbound traffic) or machine learning applications spotting suspicious activity in videos (inbound traffic).

Edge computing is, by design, autonomous. It’s not an extension of an application running at the core or subservient to the public cloud, so its data storage needs to be ample enough for the job at hand, including supporting any virtual machines involved. It also needs to be local and readily accessible...

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About the Author(s)

Scott Fulton III


Scott M. Fulton, III is a 39-year veteran technology journalist, author, analyst, and content strategist, the latter of which means he thought almost too carefully about the order in which those roles should appear. Decisions like these, he’ll tell you, should be data-driven. His work has appeared in The New Stack since 2014, and in various receptacles and bins since the 1980s.

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