All 64 Dependencies
Every package Beta9 depends on, ranked by repo health score.
Beta9 is the open-source engine powering Beam, a serverless runtime built for AI and ML workloads. It provides a Pythonic decorator-based API to deploy endpoints, task queues, functions, sandboxes, and persistent pods on GPU-enabled containers without managing Kubernetes, Docker registries, or autoscaling logic yourself. The platform uses a custom container runtime based on runc/runsc with CRIU checkpoint-restore support and a proprietary CLIP image format that enables container launch times measured in milliseconds rather than minutes.
The Go backend handles all orchestration: a gateway service exposes gRPC and HTTP APIs derived from protobuf definitions, a scheduler manages container placement across worker pools, and provider integrations cover AWS EC2, Lambda Labs, Crusoe, OCI, Hydra, and generic Kubernetes clusters. Redis serves as the primary coordination store for worker state, task queues, container lifecycle, and the backlog scheduler that bins work into available worker capacity.
The Python SDK (`pip install beam-client`) mirrors the server abstractions precisely. Decorating a function with `@endpoint`, `@task_queue`, or `@function` is all that is required to deploy it as a versioned, autoscaling service. Volume mounts, cloud bucket integration, hot-reloading during development, webhook callbacks, and scheduled jobs are all first-class SDK primitives. For code execution sandboxes, the `Sandbox` class provides a remote isolated environment with file system access, port exposure, process management, and memory snapshot/restore.
Beta9 can be self-hosted on any Kubernetes cluster using the provided Helm chart, with k3d-based local development via a single `make setup` command. The project is released under AGPL-3.0, making it free to self-host but requiring that modifications be shared under the same license if distributed as a network service.
