Edge computing refers to a model in which processing power is placed closer to where data is being created in the physical world: While cloud computing platforms like Amazon Web Services are hosted from the retailer's own massive data centers scattered across the world, edge computing focuses on smartening up the car, robot, or other systems right on the device or placing a processor in closer proximity.
It's a concept that's only become more popular as a surge in connected devices — like Tesla's semi-autonomous cars or camera-laden robots in Amazon's factories — collides with the rise of cloud computing, presenting an opportunity for both.
"Edge computing is actually a counterbalance to the cloud," Gartner analyst Bob Gill told Insider. "It's a perfect complement to the cloud that solves for the weakness of the cloud."
As the flexibility, efficiency, and pricing of cloud computing have led firms to abandon their in-house data centers, it's created a new set of technical challenges. While the cloud offers immense raw computing power, relying on it comes with trade-offs, too.
"People realized that not all the things that they want to do in the cloud worked well in the cloud," IDC analyst Dave McCarthy told Insider.
Specifically, edge computing can help solve issues of latency (where systems need to be able to process data incredibly fast), bandwidth (where machines are generating vast amounts of data that would be inefficient to send to a distant data center), autonomy (where systems need to be able to function without network connection), or compliance (like when information needs to remain within a specific country to adhere with local regulations).
Gartner expects that by 2022 more than 50% of enterprise-generated data will be created and processed outside the traditional data center or cloud. READ MORE
