kubeflow/pipelines — Machine Learning Pipelines for Kubeflow

Description and use

Kubeflow Pipelines offers a reusable, Python‑based framework for constructing, deploying, and managing end‑to‑end ML workflows on Kubernetes, enabling teams to add AI capabilities without building a model stack from scratch. Adoption begins with a small proof‑of‑concept using the README and

Problem

kubeflow/pipelines helps add AI capability without starting from a blank model stack.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Machine Learning Pipelines for Kubeflow

Source