This page documents AI Studio, our development environment for notebooks, jobs and deployments. Saturn Cloud also offers dedicated inference endpoints built with NVIDIA DSX. Talk to us about dedicated GPU capacity.

Production Examples

Examples for deploying production applications

Ready to deploy your data science work? These examples show you how to turn your models and analyses into production applications that others can use.

Start here based on your goal

Create an API for your model: Deploy with FastAPI to serve predictions via HTTP endpoints that other applications can call.

Build an interactive dashboard: Create user-friendly interfaces with Streamlit or Dash for exploring data and models.

Schedule automated tasks: Set up recurring jobs to process data, retrain models, or generate reports on a schedule.

Prerequisites

Before deploying to production, make sure you have:

Create a Job

Setting and executing a job on Saturn Cloud

Create an API with FastAPI

Use FastAPI to create RESTful APIs in Python and deploy them in Saturn Cloud

Create an API with Flask

Use Flask to create APIs in Python and deploy them on Saturn Cloud

Create a Dashboard with Panel

Use Panel to create a dashboard with Python

Create a Dashboard with Voila

Use *Voila* to create a dashboard with Python

Create a Dashboard with Dash

Use Dash to create dashboards in Python and deploy them on Saturn Cloud

Create a Dashboard with Streamlit

Use Streamlit to create dashboards in Python and deploy them on Saturn Cloud