Create a BentoML project: the `service.py` whose typed `@bentoml.api` methods become an HTTP API, plus its runtime image and a built Bento. Writes one from scratch, or converts existing code — a script, a notebook, a FastAPI/Flask app, an MLflow model, a…
Build a local BentoML project into a Bento, containerize it into an OCI/Docker image, smoke-test it locally, and push it to a container registry (Docker Hub, GHCR, ECR, private registry, kind/minikube local load, or ttl.sh). Use when the user asks to…
Generate a standalone, committable production deploy-script bundle (deploy/deploy.py + one config.yml — overrides only — from which the Kubernetes manifests are rendered) that builds, containerizes, pushes, deploys, and verifies a BentoML service without any…
Deploy a containerized BentoML service directly onto one or more plain AWS EC2 instances with Docker — no Kubernetes. Takes a pushed container image (built by the bentoml-containerize skill), either uses the user's existing instances over SSH or provisions a…
Deploy a containerized BentoML service to a vanilla Kubernetes cluster using plain kubectl manifests (no Helm, no operators, no BentoCloud/Yatai). Takes a pushed container image (from the bentoml-containerize skill), discovers the bento's service topology,…