K8sGPT

Open-source browser infrastructure for AI agents at scale

Steel is an open-source browser API purpose-built for AI agents, providing managed headless browser sessions with anti-bot bypass, proxy rotation, CAPTCHA solving, and session persistence. It handles the infrastructure layer that browser automation agents like Browser Use and Stagehand run on top of. Self-hostable or available as a cloud service. Over 6,000 GitHub stars.

Open-source background jobs and AI workflows for TypeScript

Trigger.dev is an open-source platform for building and deploying background jobs, AI agents, and long-running workflows in TypeScript. It eliminates serverless timeouts with durable task execution, automatic retries, queue-based concurrency control, and elastic scaling. Used by 30,000+ developers at companies like MagicSchool and Icon.com, it processes hundreds of millions of agent runs monthly. Backed by a $16M Series A led by Dalton Caldwell's Standard Capital fund.

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.

Google’s open-source Kubernetes assistant that translates natural-language intent into precise cluster operations.

kubectl-ai is an AI-powered Kubernetes assistant from Google Cloud Platform. It acts as an intelligent interface for cluster work, translating operator intent into Kubernetes commands and workflows. The key distinction from reactive diagnosis tools is that kubectl-ai is designed as an interactive natural-language interface for planning and executing Kubernetes operations, with provider configuration and MCP-oriented workflows around the CLI.

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.