beam-cloud/beta9
Ultrafast serverless GPU inference, sandboxes, and background jobs
What it solves
Beam provides a serverless runtime specifically designed for AI workloads, removing the infrastructure overhead typically associated with deploying and scaling AI applications. It addresses the problem of slow cold starts and the complexity of managing GPU-enabled containers at scale.
How it works
It uses a custom container runtime, scheduler, and embedded caching to launch containers in under a second. It offers a Pythonic interface that allows developers to deploy serverless inference endpoints, run background tasks, and create isolated sandboxes for executing LLM-generated code. The system supports scaling to zero and can be deployed on the Beam managed cloud or self-hosted.
Who it’s for
AI developers who need to deploy models and run large-scale AI workloads without managing servers, as well as those who need secure, isolated environments to run code generated by AI.
Highlights
- Fast Cold Starts: Containers launch in less than a second.
- Scale-to-Zero: Serverless by default to optimize costs.
- GPU Support: Compatible with high-end GPUs like 4090s and H100s.
- Parallelization: Ability to fan out workloads across hundreds of containers.
- Developer Experience: Includes hot-reloading, webhooks, and scheduled jobs.