What's the difference between edge computing and the cloud-based approach with local data processing? How much of an advantage does it provide, especially for applications requiring low latency? In which scenarios is it more logical to prefer edge computing?
How does Edge Computing impact performance?
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Well, let me tell you what I've seen in real projects here in Madrid, where Edge Computing has become a lifesaver for solutions that can't afford to go to a data center. For example, in factory automation with industrial sensors: if you send the data directly to a local server on-site (instead of sending it to the cloud), you reduce the lag from 100ms+ to less than 5ms. And that makes the difference between a machine stopping or not! AoT (Automation over Time) in a plant in Leganés implemented this with Raspberry Pi clusters, and the response time dropped so much that they even optimized energy consumption by processing only what was necessary.
Another case is autonomous cars: Tesla and others use Edge to filter raw data from cameras and lidar *in situ*, avoiding saturating the cloud with terabytes of irrelevant information. If you relied only on remote servers, on a tight curve at 120km/h, you wouldn’t have time to react. That said, Edge has a limit in capacity vs. cost: for things like real-time big data analysis (e.g., stock predictions), it’s better to combine it with cloud (hybrid architecture). My trick? Start with tests in controlled environments before scaling up.