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The Open-Source Serverless GPU Container Runtime

Beta9 is an open-source platform for running scalable serverless GPU workloads across cloud providers.

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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.

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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

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Installation

Local Install

Run Beta9 on your laptop.

Kubernetes Install

Run Beta9 in any existing Kubernetes cluster.

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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.cloudBeta9
Importsfrom beam import endpointfrom beta9 import endpoint
CLI Commandsbeam serve app.py:functionbeta9 serve app.py:function