Cloudflare Workers

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.

MCP integration for Cloudflare Workers and edge services

Cloudflare MCP Server connects AI coding agents to Cloudflare's edge platform through the Model Context Protocol. It enables agents to manage Workers, KV stores, R2 storage, D1 databases, and other Cloudflare services directly from AI assistants, streamlining edge application development and deployment workflows.

Frontend cloud platform

Frontend cloud platform and the creators of Next.js, providing instant Git-push deployments, a global edge network, and serverless compute for modern web apps. Automatic preview URLs for every pull request, Edge Functions for low-latency dynamic content, Image Optimization, Web Analytics, and the Vercel AI SDK for building AI-powered apps. Supports Next.js, React, Svelte, Nuxt, Astro, and all major frameworks. Generous free tier for personal projects and used by enterprises like Washington Post.

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.