@cloudarch
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Edge Computing
A computing paradigm that processes data at or near its source — at the "edge" of the network — rather than sending it all to a central cloud datacenter. Edge computing reduces latency, lowers bandwidth costs, and enables real-time processing for users around the globe.
“Serving the API from edge nodes cut response times from 200ms to 20ms for international users.”
Serverless
A cloud execution model where the provider manages server infrastructure automatically. Developers deploy individual functions that scale from zero to millions of invocations without provisioning or maintaining servers. "Serverless" doesn't mean no servers exist — just that you don't manage them.
“The app scaled to 100,000 concurrent users during the launch without any ops intervention, thanks to serverless.”
Throughput
The amount of work a system can process in a given time period. In APIs it's usually measured in requests per second; in AI inference it's tokens per second. Throughput and latency are related but distinct — a system can have high throughput while still having high latency for individual requests.
“The inference cluster achieved 10,000 tokens per second throughput across all concurrent users.”