Kubeflow

Kubeflow is an open-source machine learning platform for Kubernetes, designed to make deployments of ML workflows on Kubernetes simple, portable, and scalable. It provides tools for training, serving, tuning, and managing ML models across the full lifecycle.

Kubeflow publishes 4 APIs on the APIs.io network, including Experiments API, Health API, Pipelines API, and 1 more. Tagged areas include Artificial Intelligence, Deep Learning, Kubernetes, Machine-Learning, and MLOps.

Kubeflow’s developer surface includes authentication, documentation, getting-started guide, engineering blog, and 13 more developer resources.

🌐 Visit website 📡 Source on GitHub

32.9/100 thin ▬ flat Agent 23/100 agent aware Full breakdown ↓
scored 2026-08-25 · rubric v0.14.0

AccessFreemiumSelf serve⚡ Free to try

8 APIs 1 MCP Servers

Artificial Intelligence Deep Learning Kubernetes Machine-Learning MLOps Model Serving Model Training Open-Source

Kin Score

Kin Score How this is scored →
scored 2026-08-25 · rubric v0.14.0

Composite quality — 32.9/100 · thin

Contract Quality 11.9 / 25

Developer Ergonomics 7.6 / 20

Access Clarity 3.2 / 20

Operational Transparency 3.8 / 13

Contract Governance 0.0 / 12

Discoverability 6.5 / 10

Agent readiness — 23/100 · agent aware

Machine-Readable Contract 18 / 18

Agentic Access Contract 10 / 10

Documented Reversibility 0 / 6

MCP Server 12 / 12

Machine-Readable Auth 10 / 10

Idempotency 0 / 9

Stable Error Semantics 0 / 8

Request/Response Examples 0 / 7

Rate-Limit Signaling 7 / 7

Typed Event Surface 0 / 6

Agent Skills 0 / 5

Well-Known Catalog 0 / 4

Consent & Bot Identity 0 / 3

A2A Agent Card 0 / 8

Dry-Run / Simulate Mode 0 / 4

Delegated User Identity 0 / 6

Protected Resource Metadata 0 / 5

Registration Without a Human 0 / 6

Agentic Commerce Surface 0 / 5

Improve this rating by publishing the missing artifacts — every area above can be raised, and the full rubric is at apis.io/rating/. This rating is computed from github.com/api-evangelist/kubeflow: open an issue to ask a question, or submit a pull request to add artifacts. Want it done for you? Prioritized profiling — $2,500 →

APIs 8

Individual APIs this provider publishes, each with its own machine-readable definition.

MCP Servers 1

Model Context Protocol servers that expose these APIs to AI agents.

Rate Limits 1

Documented rate limits and quota policies.

Kubeflow Rate Limits

5 limits

RATE LIMITS

FinOps 1

Cost, billing, and metering signals for API financial operations.

Get Started 1

Portal, sign-up, and the first successful call

GettingStarted

GettingStarted

Documentation 3

Reference material describing how the API behaves

MCPDocumentation

MCPDocumentation

ContributionGuide

ContributionGuide

Documentation

Documentation

Agent Surfaces 2

MCP servers, agent skills, and machine-readable catalogs

MCPServer

MCPServer

AgenticAccess

AgenticAccess

Build 2

SDKs, sample code, and the tooling you integrate with

CodeOfConduct

CodeOfConduct

GitHubOrg

GitHubOrg

Access & Security 2

Authentication, authorization, and security posture

DomainSecurity

DomainSecurity

Authentication

Authentication

Operate 3

Status, limits, changes, and where to get help

IssueTracker

IssueTracker

Releases

Releases

Community

Community

Commercial 1

Pricing, plans, and the legal terms of use

License

License

Company 3

The organization behind the API

LinkedIn

Website

Website

Blog

Blog

Source (apis.yml)

aid: kubeflow
name: Kubeflow
description: Kubeflow is an open-source machine learning platform for Kubernetes, designed to make deployments of ML workflows
  on Kubernetes simple, portable, and scalable. It provides tools for training, serving, tuning, and managing ML models across
  the full lifecycle.
type: Index
accessModel:
  pricing: freemium
  onboarding: self-serve
  trial: false
  try_now: true
  public: false
  label: Freemium · Self-serve signup
  confidence: high
  source:
  - plans
  - authentication
  generated: '2026-07-22'
  method: derived
image: https://kinlane-images.s3.amazonaws.com/shared/apis-json/icons/kubeflow.png
tags:
- Artificial Intelligence
- Deep Learning
- Kubernetes
- Machine-Learning
- MLOps
- Model Serving
- Model Training
- Open-Source
tags_raw:
- AI
- Deep Learning
- Kubernetes
- Machine Learning
- MLOps
- Model Serving
- Model Training
- Open Source
url: https://raw.githubusercontent.com/api-evangelist/kubeflow/refs/heads/main/apis.yml
created: '2024-01-15'
modified: '2026-08-15'
specificationVersion: '0.23'
apis:
- aid: kubeflow:metadata-api
  name: Kubeflow Metadata API
  description: API for tracking and managing metadata, artifacts, and lineage for ML workflows running on Kubeflow.
  humanURL: https://www.kubeflow.org/docs/components/pipelines/concepts/metadata/
  tags:
  - Artifacts
  - Metadata
  - ML Tracking
  properties:
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/concepts/metadata/
  - type: GitHubRepository
    url: https://github.com/google/ml-metadata
- aid: kubeflow:katib-api
  name: Katib API
  description: Katib is the Kubeflow component for hyperparameter tuning, neural architecture search, and AutoML, exposing
    a Kubernetes-native API for defining and running tuning experiments.
  humanURL: https://www.kubeflow.org/docs/components/katib/
  tags:
  - AutoML
  - Hyperparameter Tuning
  - Neural Architecture Search
  properties:
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/katib/reference/
  - type: GitHubRepository
    url: https://github.com/kubeflow/katib
- aid: kubeflow:notebooks-api
  name: Kubeflow Notebooks API
  description: API for managing Jupyter notebook server instances within a Kubeflow cluster, providing isolated, browser-based
    development environments.
  humanURL: https://www.kubeflow.org/docs/components/notebooks/
  tags:
  - Development Environment
  - Jupyter
  - Notebooks
  properties:
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/notebooks/
  - type: GitHubRepository
    url: https://github.com/kubeflow/kubeflow/tree/master/components/notebook-controller
- aid: kubeflow:central-dashboard
  name: Kubeflow Central Dashboard API
  description: API supporting the Kubeflow central dashboard and UI components, which provide a unified interface to all installed
    Kubeflow components.
  humanURL: https://www.kubeflow.org/docs/components/central-dash/
  tags:
  - Dashboard
  - Management
  - UI
  properties:
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/central-dash/
  - type: GitHubRepository
    url: https://github.com/kubeflow/kubeflow/tree/master/components/centraldashboard
- aid: kubeflow:kubeflow-experiments-api
  name: Kubeflow Experiments API
  description: Group runs and recurring jobs into logical experiments
  humanURL: https://www.kubeflow.org/docs/components/pipelines/
  baseURL: https://your-kubeflow-instance/pipeline
  tags:
  - Experiments
  properties:
  - type: OpenAPI
    url: openapi/kubeflow-experiments-api-openapi.yml
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/v2/reference/api/kubeflow-pipeline-api-spec/
  - type: GitHubRepository
    url: https://github.com/kubeflow/pipelines
  - type: Documentation
    url: https://kserve.github.io/website/modelserving/v1beta1/
  - type: GitHubRepository
    url: https://github.com/kserve/kserve
- aid: kubeflow:kubeflow-health-api
  name: Kubeflow Health API
  description: Health and auth checks
  humanURL: https://www.kubeflow.org/docs/components/pipelines/
  baseURL: https://your-kubeflow-instance/pipeline
  tags:
  - Health
  properties:
  - type: OpenAPI
    url: openapi/kubeflow-health-api-openapi.yml
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/v2/reference/api/kubeflow-pipeline-api-spec/
  - type: GitHubRepository
    url: https://github.com/kubeflow/pipelines
  - type: Documentation
    url: https://kserve.github.io/website/modelserving/v1beta1/
  - type: GitHubRepository
    url: https://github.com/kserve/kserve
- aid: kubeflow:kubeflow-pipelines-api
  name: Kubeflow Pipelines API
  description: Manage pipeline definitions
  humanURL: https://www.kubeflow.org/docs/components/pipelines/
  baseURL: https://your-kubeflow-instance/pipeline
  tags:
  - Pipelines
  properties:
  - type: OpenAPI
    url: openapi/kubeflow-pipelines-api-openapi.yml
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/v2/reference/api/kubeflow-pipeline-api-spec/
  - type: GitHubRepository
    url: https://github.com/kubeflow/pipelines
  - type: Documentation
    url: https://kserve.github.io/website/modelserving/v1beta1/
  - type: GitHubRepository
    url: https://github.com/kserve/kserve
- aid: kubeflow:kubeflow-pipelineversions-api
  name: Kubeflow PipelineVersions API
  description: Manage versions of pipelines
  humanURL: https://www.kubeflow.org/docs/components/pipelines/
  baseURL: https://your-kubeflow-instance/pipeline
  tags:
  - PipelineVersions
  properties:
  - type: OpenAPI
    url: openapi/kubeflow-pipelineversions-api-openapi.yml
  - type: Documentation
    url: https://www.kubeflow.org/docs/components/pipelines/v2/reference/api/kubeflow-pipeline-api-spec/
  - type: GitHubRepository
    url: https://github.com/kubeflow/pipelines
  - type: Documentation
    url: https://kserve.github.io/website/modelserving/v1beta1/
  - type: GitHubRepository
    url: https://github.com/kserve/kserve
common:
- type: MCPServer
  name: Kubeflow MCP Server
  url: https://github.com/kubeflow/mcp-server
- type: MCPDocumentation
  name: Kubeflow MCP Server Documentation
  url: https://github.com/kubeflow/mcp-server/blob/main/README.md
- type: IssueTracker
  url: https://github.com/google/ml-metadata/issues
- type: Releases
  url: https://github.com/google/ml-metadata/releases
- type: CodeOfConduct
  url: https://github.com/google/.github/blob/master/CODE_OF_CONDUCT.md
- type: ContributionGuide
  url: https://github.com/google/ml-metadata/blob/master/CONTRIBUTING.md
- type: License
  name: Apache-2.0
  url: https://github.com/google/ml-metadata/blob/master/LICENSE
- type: AgenticAccess
  url: agentic-access/kubeflow-agentic-access.yml
- type: DomainSecurity
  url: security/kubeflow-domain-security.yml
- type: Authentication
  url: authentication/kubeflow-authentication.yml
- type: LinkedIn
  url: https://www.linkedin.com/company/kubeflow
- type: Website
  url: https://www.kubeflow.org
- type: Documentation
  url: https://www.kubeflow.org/docs/
- type: GettingStarted
  url: https://www.kubeflow.org/docs/started/
- type: Blog
  url: https://blog.kubeflow.org/
- type: GitHubOrg
  url: https://github.com/kubeflow
- type: Community
  url: https://www.kubeflow.org/docs/about/community/
maintainers:
- FN: Kin Lane
  email: kin@apievangelist.com

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