I built an open-source alternative to Microsoft's KAITO that works on ANY Kubernetes cluster

Из ленты dev.to devops — кратко, чтобы не потерять.

Six months ago, my team needed to deploy DeepSeek-R1 for internal use. We have a Kubernetes cluster — like everyone does in 2026 — so I started looking for tools. The problem There are basically three options for running LLMs on Kubernetes: KAITO (Microsoft) — CNCF Sandbox, 1600+ stars, but Azure-only. We are on AWS. KServe — CNCF Incubating, solid project, but requires Knative + ISTIO + 5+ other components. Raw vLLM — Great for serving, but you need to separately set up monitoring, tracing, auth, API keys, rate limiting, autoscaling. So I did what any engineer would do: I built my own. What I built kube-llmops is a Kubernetes-native LLMOps platform that deploys everything you need with one Helm chart: Model serving — vLLM, llama.cpp, or TEI, auto-selected based on model format AI Gateway

Полный текст и контекст у первоисточника: https://dev.to/gaearuiw/i-built-an-open-source-alternative-to-microsofts-kaito-that-works-on-any-kubernetes-cluster-2db3