Serverless

What is serverless?

"Serverless" doesn't mean there's no server — it means you stop worrying about it. You write the code and set the trigger; the cloud spins up, runs and bills by usage, then releases it. The server is still there, just hidden from view.

How is it different from traditional hosting?

Traditional: always-on machines
You rent one or several servers running 24/7, paying whether traffic is high or not.
Serverless: woken on demand
No request, no resources. A request arrives and it spins up instantly — you only pay for the time it's actually running.

Why it fits AI tasks

Inference is spiky
Plenty of AI features aren't under constant load — a user clicks now and then, and each click triggers one inference. Serverless matches that on-and-off load perfectly.
No ops
No system upgrades, no scaling to manage. The team focuses on the model and the product.
Watch the cold start and timeouts
Models take time to load, so the first call can be slow (cold start), and there's a time limit per run — long jobs need chunking or a different plan.

Who it's for

For prototypes, low-traffic apps and event-driven functions, serverless is cheap and easy. But for high-frequency, long-running, latency-sensitive workloads, always-on instances usually win.

Bottom line: serverless is "power on demand" — the server wakes only when your code is needed, and you pay only for what you actually use.