Deploy to a Serverless Container Runtime
Run the model on Cloud Run or App Runner.
Deploy to a Serverless Container Runtime is a free MLOps Academy lesson on CoddyKit — lesson 2 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the MLOps Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Skip the Servers
A serverless container runtime runs your image without you managing any VMs. You hand over a container, and the platform handles the rest. ☁️
Two Popular Choices
Google offers Cloud Run and AWS offers App Runner. Both pull your image from a registry and expose it behind a managed HTTPS URL.
Deploy from an Image
You point the runtime at your pushed image and it creates a service. With Cloud Run, one deploy command turns an image into a live URL.
gcloud run deploy model-api --image registry.example.com/team/model-api:1.0.0Listen on the Right Port
The platform sends traffic to a port it chooses, exposed as the PORT environment variable. Your app must bind to that value, not a hardcoded one.
uvicorn main:app --host 0.0.0.0 --port ${PORT}Bind to All Interfaces
Inside a container, bind the server to 0.0.0.0, not 127.0.0.1. Otherwise the platform cannot route outside traffic into your process.
Stateless Containers Only
Instances start and stop at any time, so anything saved to local disk can vanish. Keep the service stateless and store data externally.
You Pay for What You Serve
Serverless billing is usually per request and per active second. When no one calls your model, idle time can cost almost nothing. 💸
Mind the Cold Start
If an idle service scaled to zero, the next request waits for a container to boot. That delay is a cold start, common with big model files.
Keep a Warm Instance
To dodge cold starts, set a minimum instances floor. The platform keeps that many containers warm and ready to answer instantly.
gcloud run deploy model-api --min-instances 1Watch the Live Logs
The runtime streams your container output to its logs console. Tail them right after a deploy to confirm the model loaded cleanly.
From Image to Live URL
That is the whole loop: push an image, run one deploy, and the platform returns a public URL serving your model over HTTPS.
Quick Check
Let us check why your first request can feel slow.
Recap
You deployed an image to a serverless runtime, bound to PORT on 0.0.0.0, stayed stateless, and tamed cold starts. Your model is live. 🎉
Frequently asked questions
Is the “Deploy to a Serverless Container Runtime” lesson free?
Yes — the full text of “Deploy to a Serverless Container Runtime” is free to read here on the web, and the MLOps Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the MLOps Academy course, upgrade to CoddyKit PRO.
What will I learn in “Deploy to a Serverless Container Runtime”?
Run the model on Cloud Run or App Runner. You practise MLOps Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start MLOps Academy?
No prior experience is required. MLOps Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 2 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “Deploy to a Serverless Container Runtime” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this MLOps Academy lesson?
Yes. Every MLOps Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Push Your Image to a Registry
- Deploy to a Serverless Container Runtime
- Configure Autoscaling and Concurrency
- Manage Secrets and Config in the Cloud