Beam is a cloud platform where you can provision infrastructure, develop on remote runtimes from your local machine, and deploy apps as serverless functions — without leaving your IDE
Beam is currently in private beta. If you’re reading this, you’re one of the first people to try it.
Configure your runtime in Python - tell us how many GPUs you need and which libraries you want installed, and Beam will spawn a remote environment for you.
You can write and run your code locally - except when you enter your shell, your code will run on Beam instead of your local machine.
Deploy your apps as serverless REST APIs, scheduled cron jobs, or webhooks - all in just four lines of Python.
Deploy ML models on serverless runtimes. Your app will scale automatically with traffic and spin down when idle.
Develop on your local IDE, while running on remote GPUs
Instantly jump from hacking on a script to serving an API in production
Save money on your cloud bill. Beam is serverless and charges simple usage-based, per-second pricing
Deploy Stable Diffusion using a GPU
Scraping a website and running the results through an ML model
Deploying a pre-trained ML model as a REST API
Apps. Each project in Beam is called an app. When you first start Beam, you’ll be prompted to define your environment through the Beam.App()
method in the SDK.
Triggers. Triggers are actions that can invoke your Beam apps. For example, a REST API trigger allows your Beam app to be invoked via a REST API. A webhook trigger will allow your Beam app to be invoked asyncronously using a webhook, and so on.
Outputs. Outputs are file paths that can be used to save files created when your functions are run.