Kubeflow How-To: From Install to Pipelines, Trainer, Katib, and KServe
Introduction TL;DR: Kubeflow is an ecosystem for running reproducible ML workflows on Kubernetes—from notebooks and pipelines to distributed training and model serving. (Kubeflow) In practice, “using Kubeflow” means wiring together Profiles/Namespaces, Notebooks, Pipelines (KFP), training (Trainer), tuning (Katib), and serving (KServe) with clear operational boundaries. (Kubeflow) 1) What “Kubeflow” is in 2026: Projects vs Platform Kubeflow can be installed as standalone projects (e.g., Pipelines-only) or as the integrated Kubeflow AI reference platform. The official “Installing Kubeflow” guide explicitly frames these as two installation methods. (Kubeflow) ...