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pipelines

kubeflow/pipelines

Machine Learning Pipelines for Kubeflow

GitHub Website

GraphCanon updated 3w · GitHub synced 3w

4.2k stars2.1k forksLast push 3w Python Apache-2.0

Decision brief

Pipelines from Kubeflow is optimized for Kubernetes environments and supports MLOps workflows with Emissary Executor by default.

Good fit when

Use Pipelines when you are working in an existing Kubernetes cluster as it integrates seamlessly without any configuration hassles specific to container runtimes like Docker.
Prefer this tool if your project requires seamless model training and deployment within the Kubeflow ecosystem for data science endeavors.

Avoid when

Avoid Pipelines from Kubeflow if you require support on a non-Kubernetes environment, as it is tightly integrated with Kubernetes services.
Do not use this tool if your operations necessitate legacy Docker container runtime integration without the adaptability provided by Emissary Executor.

Observed Jul 17, 2026 · Source: enrich:decision_facts

pipelines alternatives Trust report

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Maintenance and security

Full trust report

Maintenance: Very active (0d since push); As of 3w
Provenance: Not a fork · Organization account; As of 3w
Security (OSV): 2 low (2 low); As of 1mo

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install pipelines

PyPI

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Provides machine learning pipelines in Kubernetes environments for data science and MLOps workflows.

Capability facts

Languages: python
Source: github.language · Aug 3, 2026

README

Installation

Kubeflow Pipelines can be installed as part of the Kubeflow Platform. Alternatively you can deploy Kubeflow Pipelines as a standalone service.
The Docker container runtime has been deprecated on Kubernetes 1.20+. Kubeflow Pipelines has switched to use Emissary Executor by default from Kubeflow Pipelines 1.8. Emissary executor is Container runtime agnostic, meaning you are able to run Kubeflow Pipelines on Kubernetes cluster with any Container runtimes.

For agents

This page has a .md twin and JSON over the API.

/tools/kubeflow-pipelines.md GET /api/graphcanon/tools/kubeflow-pipelines GET /api/graphcanon/graph?tool=kubeflow-pipelines