Getting Started
Introduction
The Open-Source Serverless GPU Container Runtime
Beta9 is an open-source platform for running scalable serverless GPU workloads across cloud providers.
Features
- Scale out workloads to thousands of GPU (or CPU) containers
- Ultrafast cold-start for custom ML models
- Instantly run remote containers, right from your Python interpreter
- Distribute workloads across multiple cloud providers
- Easily deploy task queues and functions using simple Python abstractions
We use Beta9 internally at Beam to run AI applications for users at scale.
How it works
Beta9 is designed for launching remote serverless containers quickly. There are a few things that make this possible:
- A custom, lazy loading image format (CLIP) backed by S3/FUSE
- A fast, redis-based container scheduling engine
- Content-addressed storage for caching images and files
- A custom runc container runtime
Installation
Local Install
Run Beta9 on your laptop.
Kubernetes Install
Run Beta9 in any existing Kubernetes cluster.
Try Beam Cloud
Use the fully-managed cloud product.
Note for existing cloud users
This section of the documentation is for Beta9, the open-source version of Beam.
Beam and Beta9 have similar functionality.
You can switch between either product by changing the SDK imports and CLI commands used:
| beam.cloud | Beta9 | |
|---|---|---|
| Imports | from beam import endpoint | from beta9 import endpoint |
| CLI Commands | beam serve app.py:function | beta9 serve app.py:function |