Mental BoundInstead of sending all data to a central cloud, edge computing runs workloads on devices or servers near the data source — at cell towers, in retail stores, on factory floors, or in IoT gateways. The goal: process data where it's generated, then send only summaries or alerts to the cloud.
Benefits include lower latency (critical for real-time applications), reduced bandwidth costs, and the ability to operate when connectivity is poor. Use cases range from video analytics at the camera to real-time fraud detection at the point of sale. Trade-offs: edge nodes have limited compute, require different deployment and monitoring patterns, and add operational complexity. Choose edge when latency or bandwidth constraints make centralization impractical.