CapRover

Deploy web apps anywhere

Zero-downtime deployment tool created by 37signals (Basecamp/HEY) that deploys Docker containers to any VPS or bare metal server over SSH without requiring Kubernetes. Manages rolling deploys, health checks, SSL via Let's Encrypt, container registry, and load balancing with Traefik. Simple YAML-based config. Ideal for small teams deploying Rails, Node.js, or any Dockerized app. Ships as a Ruby gem. 12K+ GitHub stars and a growing alternative to complex container orchestration.

The smallest PaaS implementation

Dokku is a Docker-powered, open-source mini-Heroku that gives you the smallest PaaS implementation for deploying applications on your own server. Push with Git, build via Heroku buildpacks or Dockerfiles, and get automatic subdomains, SSL, zero-downtime deploys, and add-on plugins for databases and services. Ideal for self-hosted developers who want Heroku ergonomics without the cloud vendor bill.

Container orchestration at scale

Kubernetes (K8s) is the industry-standard open-source container orchestration platform originally developed by Google and now maintained by the CNCF. Automates deployment, scaling, self-healing, and networking of containerized workloads across clusters of machines. Runs everywhere from laptops (kind, k3s) to every major cloud (EKS, GKE, AKS), and is the foundation of modern cloud-native infrastructure.

Open-source PaaS alternative to Vercel, Heroku, and Netlify

Dokploy is a free open-source platform-as-a-service for self-hosting applications without cloud vendor lock-in. It provides automated deployments from Git repositories, built-in SSL certificates, database provisioning, Docker and Docker Compose support, and a clean web dashboard for managing multiple applications on your own servers. With 18,000+ GitHub stars, it fills the gap for teams wanting Vercel-like deployment simplicity on their own infrastructure.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.