Kubeflow Pipelines

Kubeflow Pipelines is a platform for building and deploying portable, scalable machine learning workflows based on Docker containers. It provides a way to orchestrate complex ML workflows with dependencies, enabling data scientists and ML engineers to deploy production-ready ML systems on Kubernetes.

4 APIs 0 Features

Data ScienceKubernetesMachine LearningMLOpsOrchestrationPipelinesWorkflows

APIs

Kubeflow Pipelines REST API

REST API for managing ML pipelines, experiments, runs, and artifacts. Provides programmatic access to create, execute, and monitor ML workflows on a Kubeflow Pipelines deployment.

Kubeflow Pipelines Python SDK

Python SDK for building, compiling, and submitting ML pipelines. Provides decorators and utilities to define pipeline components and workflows using Python.

Kubeflow Pipelines Go Client

Go client library for interacting with the Kubeflow Pipelines API programmatically from Go applications.

Kubeflow Pipelines Metadata API

API for tracking and managing metadata about ML artifacts, executions, and lineage information throughout the ML pipeline lifecycle, backed by ML Metadata (MLMD).

Resources

Sources

aid: kubeflow-pipelines
name: Kubeflow Pipelines
description: >-
  Kubeflow Pipelines is a platform for building and deploying portable,
  scalable machine learning workflows based on Docker containers. It provides
  a way to orchestrate complex ML workflows with dependencies, enabling data
  scientists and ML engineers to deploy production-ready ML systems on
  Kubernetes.
type: Index
image: https://kinlane-productions2.s3.amazonaws.com/apis-json/apis-json-logo.jpg
tags:
  - Data Science
  - Kubernetes
  - Machine Learning
  - MLOps
  - Orchestration
  - Pipelines
  - Workflows
url: https://raw.githubusercontent.com/api-evangelist/kubeflow-pipelines/refs/heads/main/apis.yml
created: '2024-01-01'
modified: '2026-04-28'
specificationVersion: '0.19'
apis:
  - aid: kubeflow-pipelines:rest-api
    name: Kubeflow Pipelines REST API
    description: >-
      REST API for managing ML pipelines, experiments, runs, and artifacts.
      Provides programmatic access to create, execute, and monitor ML workflows
      on a Kubeflow Pipelines deployment.
    humanURL: https://www.kubeflow.org/docs/components/pipelines/reference/api/kubeflow-pipeline-api-spec/
    baseURL: https://your-kubeflow-host/pipeline
    tags:
      - Experiments
      - Pipelines
      - REST API
      - Runs
    properties:
      - type: Documentation
        url: https://www.kubeflow.org/docs/components/pipelines/reference/api/kubeflow-pipeline-api-spec/
      - type: OpenAPI
        url: https://raw.githubusercontent.com/kubeflow/pipelines/master/backend/api/v2beta1/swagger/pipeline.swagger.json
  - aid: kubeflow-pipelines:python-sdk
    name: Kubeflow Pipelines Python SDK
    description: >-
      Python SDK for building, compiling, and submitting ML pipelines. Provides
      decorators and utilities to define pipeline components and workflows
      using Python.
    humanURL: https://kubeflow-pipelines.readthedocs.io/
    baseURL: https://pypi.org/project/kfp/
    tags:
      - Client Library
      - DSL
      - Python
      - SDK
    properties:
      - type: Documentation
        url: https://kubeflow-pipelines.readthedocs.io/
      - type: GitHubRepository
        url: https://github.com/kubeflow/pipelines/tree/master/sdk/python
      - type: Examples
        url: https://github.com/kubeflow/pipelines/tree/master/samples
  - aid: kubeflow-pipelines:go-client
    name: Kubeflow Pipelines Go Client
    description: >-
      Go client library for interacting with the Kubeflow Pipelines API
      programmatically from Go applications.
    humanURL: https://github.com/kubeflow/pipelines/tree/master/backend/api/go_client
    tags:
      - Client Library
      - Go
      - SDK
    properties:
      - type: Documentation
        url: https://pkg.go.dev/github.com/kubeflow/pipelines/backend/api/go_client
      - type: GitHubRepository
        url: https://github.com/kubeflow/pipelines/tree/master/backend/api/go_client
  - aid: kubeflow-pipelines:metadata-api
    name: Kubeflow Pipelines Metadata API
    description: >-
      API for tracking and managing metadata about ML artifacts, executions,
      and lineage information throughout the ML pipeline lifecycle, backed by
      ML Metadata (MLMD).
    humanURL: https://www.kubeflow.org/docs/components/pipelines/concepts/metadata/
    tags:
      - Artifacts
      - Lineage
      - Metadata
      - ML Metadata
    properties:
      - type: Documentation
        url: https://www.kubeflow.org/docs/components/pipelines/concepts/metadata/
      - type: GitHubRepository
        url: https://github.com/google/ml-metadata
common:
  - type: Website
    url: https://www.kubeflow.org/docs/components/pipelines/
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/
  - type: Getting Started
    url: https://www.kubeflow.org/docs/components/pipelines/getting-started/
  - type: GitHubOrg
    url: https://github.com/kubeflow
  - type: GitHubRepository
    url: https://github.com/kubeflow/pipelines
  - type: Blog
    url: https://blog.kubeflow.org/
  - type: Community
    url: https://www.kubeflow.org/docs/about/community/
  - type: Change Log
    url: https://github.com/kubeflow/pipelines/releases
maintainers:
  - FN: Kin Lane
    email: [email protected]