It all began when technology expands the definition of the utilisation of IoT devices. IoT devices that become more connected to the internet, either to receive from or send back data to the cloud leads to the generation of ginormous amount of data, thus significantly set about the need to shift to a more reliable computing paradigm called edge computing. Subsequently, the abundance amount of data that grow exponentially as people are becoming heavily internet-dependent, edge computing is no longer enough, hence the need for another shift – from edge computing to hyperscale edge computing.
At its core, the development of edge computing aims to process the flooding amount of data produced or consumed by people and devices as close to the data resources (either on the device itself or on the network edge) as possible. With this foundation, edge computing solves many infrastructure challenges that came about the traditional computing model which include excess latency, bandwidth limitations and network congestion.
Hyperscale edge computing is an evolution of model and application, the expansion of edge computing through integration of the computing paradigm itself and hyperscale data centers. Most importantly it is the future. There are many aspects that mark the beginning of hyperscale edge computing. Nevertheless, the dawn of hyperscale edge computing originates from the same root of problem that brought about the development of edge computing – Ocean of data, enormous and exponentially overflowing but with bigger pain point, inability to scale up according to business or users demands.
Thus, from edge computing to hyperscale edge computing, is a promising solution to these problems where hyperscale data center serves to provide scalability by increasing computing ability, memory, networking infrastructure, or storage resources to respond to demands combines with edge computing that offers comprehensive data analysis leading to better insights, quicker respond time and improve user experiences.
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