Definition
Edge computing means running computation near the source of the data or the user, whether that is a server in a nearby city, a device in a factory or a phone, rather than sending everything to a distant central data centre. The goal is lower latency, less bandwidth use and the ability to keep working when the connection to the cloud is slow or absent. It complements the cloud rather than replacing it: the edge handles the immediate, the cloud handles the heavy and the historical.
In a company, edge computing appears in two very different forms. In web products, edge platforms from CDN and cloud providers run your code in hundreds of locations so a user in Singapore and a user in Madrid both get a response in tens of milliseconds. In physical operations, edge devices in stores, vehicles, farms and factories run software and AI models locally, for example detecting a defect on a production line without waiting for a round trip to the cloud.
The misconception is that edge computing is a niche for industrial companies. In 2026 it also matters for AI: running smaller models directly on phones, laptops and local servers is cheaper, faster and better for privacy than sending every request to a hosted model, and device makers now ship hardware designed for it. The realistic picture is a spectrum, with each task running wherever the balance of speed, cost and data sensitivity is best.
In practice
A retail chain runs its camera-based shelf monitoring on a small server in each store. Alerts fire in seconds, video never leaves the premises, and the head office receives only summaries, which cuts bandwidth costs and simplifies privacy compliance.
Why it matters
Edge computing is how you get software that feels instant and keeps working when the network does not. If your product depends on speed or handles sensitive data at physical locations, it should be part of your architecture discussion.
Frequently asked questions
- What is the difference between edge computing and cloud computing?
- Cloud computing centralises processing in large data centres. Edge computing moves part of that processing close to the user or device to reduce delay and bandwidth. They work together: the edge handles fast, local decisions and the cloud handles storage, heavy analysis and coordination across locations.
- What are examples of edge computing?
- Content and code served from a CDN location near the user, AI models running on a phone or laptop, quality inspection cameras in a factory, point-of-sale systems that keep working offline, and vehicles that process sensor data on board. Anywhere a round trip to the cloud would be too slow or too expensive.