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pipelines

kubeflow/pipelines

Machine Learning Pipelines for Kubeflow

GitHub Website

GraphCanon updated Sep 29, 2026 · GitHub synced Sep 29, 2026

48views this month

4.2k stars2.1k forksLast push Sep 28, 2026 Go 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 Sep 29, 2026
Provenance: Not a fork · Organization account; As of Sep 29, 2026
Security (OSV): 2 low (2 low); As of Jul 11, 2026

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

Install

go get github.com/kubeflow/pipelines

pkg.go.dev

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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: go, python
Source: github.language+pyproject.toml · Sep 29, 2026

README

Installation Kubeflow Pipelines can be installed as part of the Kubeflow Platform. Alternatively you can deploy Kubeflow Pipelines as a standalone service. Pipeline execution uses the Argo Emissary executor, which is independent of the Kubernetes container runtime.

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