BeginnerRecording next~50 minAWS
Your First AI API on One Cloud Server
One server, one model, one public URL — the thing you spend the rest of the series growing.
# what you build
Every AI system starts here: a model, a web server in front of it, and an address the world can reach. You will launch a single Ubuntu server, serve a model behind a FastAPI endpoint that streams its answer, put Nginx and free HTTPS in front, and keep it alive with systemd. By the end you have a real endpoint anyone can curl — and a clear idea of what “deploying a model” actually means.
What you end up with
handles after this
~10 people at once
what it costs to run
$5–12 / month
What you will be able to do
- What actually runs on the machine when a model answers a request
- How to size a server for a model — RAM first, and why a GPU is usually overkill here
- Serve a model from a FastAPI endpoint that streams tokens as they arrive
- Nginx as a reverse proxy, with timeouts that survive a slow model
- Keep the service running across crashes and reboots with systemd
- Read the bill — what one always-on AI box really costs per month
The build, step by step
These are the chapters of the video, in order.
- 1Launch the serverPick the instance size, open only the ports you need, log in with an SSH key.
- 2Serve the modelA FastAPI app with one endpoint that streams the answer back token by token.
- 3Put Nginx in frontReverse proxy, timeouts tuned for slow responses, and free HTTPS with Certbot.
- 4Make it survive a rebootA systemd unit, logs you can actually read, and a health check that means something.
- 5Find the ceilingLoad it until it breaks, so you know exactly which rung you are standing on.
The stack
- FastAPI
- Ubuntu
- Nginx
- systemd
- EC2
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