Edge computing refers to the concept of bringing computing services closer to service consumers or data sources. Fueled by emerging use cases like IoT, AR/VR, robotics, machine learning, and telco network functions that require service provisioning closer to users, edge computing helps solve the key challenges of bandwidth, latency, resiliency, and data sovereignty. Edge computing moves some portion of the storage and computes resources out of the central data centre and closer to the source of the data itself. Rather than transmitting raw data to a central data centre for processing and analysis, that work is instead performed where the data is generated — whether that's a retail store, a factory floor, a sprawling utility or across a smart city.
Edge computing is all a matter of location. In traditional enterprise computing, data is produced at a client endpoint, such as a user's computer. That data is moved across a WAN such as the internet, through the corporate LAN, where the data is stored and worked upon by an enterprise application. Results of that work are then conveyed back to the client endpoint. This remains a proven and time-tested approach to client-server computing for most typical business applications.
Edge computing, joined with machine learning, enables faster decision-making processes
Edge computing can optimize IoT applications, in particular ones that require real-time actions
North America is currently estimated to be the largest edge computing market, representing almost 50% of the global revenue share
Edge computing enables increased security and resiliency because its decentralized nature eliminates a single central point of failure
Edge computing brings speed with its locational proximity delivering the additional speed that some actions require
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