Open-source Modal alternatives

OpenFaaS is a serverless platform that lets developers run event-driven functions and microservices on Kubernetes with little boilerplate code. Your code or a ready-made binary goes into an OCI-compatible container image, and you receive a scalable HTTP endpoint that auto-scales and exposes metrics.

Highlights include ease of use through a UI portal and a one-click install, and the ability to write services and functions in many languages. The project integrates with Prometheus for metrics and with GitOps workflows, and its topics place it in the functions-as-a-service and PaaS categories. The gateway and tooling are written in Go.

Licensing needs attention. The README states that the Community Edition is licensed for individual exploration and hobbyist use, with a 60-day limit for commercial proofs of concept, and that commercial and production use calls for the paid OpenFaaS Standard or Enterprise editions. GitHub reports the license as 'Other'. You run it on your own Kubernetes cluster.

Beam, whose open-source engine lives in the beta9 repository, is a fast runtime for serverless AI workloads. It gives developers a Pythonic interface to deploy and scale AI applications without managing infrastructure. The code is written in Go and released under the AGPL-3.0 license, and topics include GPU, LLM inference, autoscaling, and functions as a service.

Features include sub-second container cold starts using a custom runtime, scheduler, and embedded caching, parallel fan-out to hundreds of containers, hot reloading, webhooks and scheduled jobs, scale-to-zero by default, and mounted distributed storage volumes. GPU support runs on the Beam cloud, with cards such as the RTX 4090 and H100 mentioned, or on your own GPUs.

The project can be self-hosted or used through the hosted platform, which requires creating an account. Beam suits machine learning engineers and startups that want to serve models, run batch jobs, or sandbox untrusted code without operating a Kubernetes GPU cluster themselves.