Edge computing is not a straightforward topic. In simple terms Edge computing is the practice of capturing, storing, processing and analyzing data near the client, where the data is generated, instead of in a centralized data-processing warehouse.
Edge is a strategy to extend a uniform environment all the way from the core datacenter to physical locations near users and data. Just as a hybrid cloud strategy allows organizations to run the same workloads both in their own datacenters and on public cloud infrastructure (like Amazon Web Services, Microsoft Azure, or Google Cloud), an edge strategy extends a cloud environment out to many more locations. Edge computing is in use today across many industries, including telecommunications, manufacturing, transportation, utilities, and many others. The reasons people implement edge computing are as diverse as the organizations they support.
SMany edge use cases are rooted in the need to process data locally in real time—situations where transmitting the data to a datacenter for processing causes unacceptable levels of latency. For an example of edge computing driven by the need for real-time data processing, think of a modern manufacturing plant. On the factory floor, Internet of Things (IoT) sensors generate a steady stream of data that can be used to prevent breakdowns and improve operations. By one estimate, a modern plant with 2,000 pieces of equipment can generate 2,200 terabytes of data a month. It’s faster—and less costly—to process that trove of data close to the equipment, rather than transmit it to a remote datacenter first. But it’s still desirable for the equipment to be linked through a centralized data platform. That way, for example, equipment can receive standardized software updates and share filtered data that can help improve operations in other factory locations. Connected vehicles are another common example of edge computing. Buses and trains carry computers to track passenger flow and service delivery. Delivery drivers can find the most efficient routes with the technology onboard their trucks. When deployed using an edge computing strategy, each vehicle runs the same standardized platform as the rest of the fleet, making services more reliable and ensuring that data is protected uniformly.