Six AI agent SDKs for enterprise Kubernetes, compared
There’s a question we hear constantly from platform and engineering leaders right now, “which agent SDK should we standardize on for our Kubernetes clusters?”
The honest answer is that the question is slightly wrong, and the rest of this post explains why. But it’s a fair question, so let’s compare the contenders first.
If you’re an enterprise running on-premise or in your own VPC, the SDK you pick has to do two things most of the “build an agent in 20 lines” tutorials skip over. It has to run in a container you control, and it has to talk to a model you can host yourself. That second one rules out a surprising amount.
The six SDKs most people are actually using
These are the ones with the most mindshare in mid-2026. There are others, but these are the names that come up in every conversation. They sit on a rough spectrum of model freedom: most will happily run against a model you host yourself, the OpenAI SDK will too but treats that as a side path, and one of them (Anthropic’s) is tied to a single vendor’s models. I’ve ordered them with the most flexible first.
LangGraph
LangChain’s Continue reading