It’s fundamentally impossible to manage each of these deployments if they don’t share a more secure control plane via automation, management and orchestration. With the disparate nature of edge computing, consistency is key - an edge deployment could theoretically be hundreds of thousands of tiny sensors connected to a data aggregation tier which help to provide real-time feedback to what the sensors are actually monitoring. eBay, for example, is adopting edge computing by decentralizing its datacenters with the intent to create a faster, more consistent user experience by moving data and online services closer to users. Whatever the specific workload for edge, the need is the same: Faster responses for more timely services, whatever they may be. This could be small-form servers on cell towers, sensors monitoring a global energy network or next-generation factory automation systems that anticipate maintenance needs. Where "traditional" cloud deployments are about centralizing on a single infrastructure that can scale up as business needs dictate, edge is focused on "scaling out" geographically. Why edge computing is "hybrid or die"Įdge computing turns the concept of cloud computing on its head. If edge computing is going to be a realistic future for enterprise IT, it needs the hybrid cloud AND open source to thrive. The foundation of edge computing must be open or it WILL fail.īold statements? Sure, but from my point of view, they are wholly accurate. It simply does not exist without the hybrid cloud. But unlike the other footprints, edge computing has two key delineating factors: In a sense, edge computing is a summation of the other four footprints, blending pieces from each to create infrastructure aimed at tackling specific customer demands that traditional IT models cannot address. We can look at the edge as the newest IT footprint, becoming an extension of the data center just like bare-metal, virtual environments, private cloud and public cloud. Whether it's the Internet-of-Things (IoT), fog computing or edge computing, the intent is to bring computing resources like processing power and storage closer to the end user or data source to improve the ability to scale, responsiveness and the overall service experience. The past year has seen the rise of applications that push enterprise IT to the (literal) edge, from using autonomous vehicles guided by artificial intelligence (AI) to vast sensor networks that rely on 5G for instant connectivity and emergency reaction times.