Machine Learning Pipelines for Kubeflow
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chore(deps): bump brace-expansion from 1.1.11 to 1.1.12 in /frontend (#11972)
Bumps [brace-expansion](https://github.com/juliangruber/brace-expansion) from 1.1.11 to 1.1.12.
- [Release notes](https://github.com/juliangruber/brace-expansion/releases)
- [Commits](https://github.com/juliangruber/brace-expansion/compare/1.1.11...v1.1.12)

---
updated-dependencies:
- dependency-name: brace-expansion
  dependency-version: 1.1.12
  dependency-type: indirect
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2025-06-13 12:52:52 +00:00
.github fix(test): Fix the frontend sample test (#11968) 2025-06-10 19:47:49 +00:00
api chore: pipeline api spec minor release (#11939) 2025-05-29 14:35:20 +00:00
backend fix(backend): Fix the pipeline samples (#11967) 2025-06-10 17:41:49 +00:00
components chore(deps): bump requests from 2.18.4 to 2.32.4 in /components/contrib/arena/docker (#11963) 2025-06-10 16:31:50 +00:00
docs chore: Nest sdk docs (#11945) 2025-05-30 20:36:20 +00:00
frontend chore(deps): bump brace-expansion from 1.1.11 to 1.1.12 in /frontend (#11972) 2025-06-13 12:52:52 +00:00
hack docs(KEP): Propose a new pipeline run workspace feature (#11875) 2025-05-16 17:41:23 +00:00
images chore: update release notes (#11827) 2025-04-15 22:00:22 +00:00
kubernetes_platform feat(backend): add the option to enable/disable cache globally (#11831) 2025-05-08 12:45:40 +00:00
manifests feat(backend): Use native k8s probes for api-server and visualization (#11960) 2025-06-06 19:07:17 +00:00
proposals docs(KEP): Propose a new pipeline run workspace feature (#11875) 2025-05-16 17:41:23 +00:00
proxy chore: update all owners files (#11886) 2025-05-02 14:47:04 +00:00
samples feat(backend/sdk): support PipelineTaskFinalStatus input (#11953) 2025-06-06 19:01:16 +00:00
sdk feat(backend/sdk): support PipelineTaskFinalStatus input (#11953) 2025-06-06 19:01:16 +00:00
test chore(deps): bump brace-expansion in /test/frontend-integration-test (#11971) 2025-06-11 22:37:51 +00:00
third_party chore: update all owners files (#11886) 2025-05-02 14:47:04 +00:00
tools feat(backend/frontend): Add the name field for pipelines and pipeline versions (#11952) 2025-06-06 15:01:16 +00:00
.dockerignore chore: Added Dockerfiles to .dockerignore (#11408) 2024-11-26 19:32:52 +00:00
.gitattributes Support filtering on storage state (#629) 2019-01-11 11:01:01 -08:00
.gitignore feat(backend): Add types for KFP Kubernete Native API (#11672) 2025-03-07 13:57:55 +00:00
.golangci.yaml chore: Enable go fmt as a lint check for Go code (#11830) 2025-05-19 14:31:37 +00:00
.isort.cfg chore: add the missing `.isort.cfg` file (#8045) 2022-07-19 16:56:48 +00:00
.pre-commit-config.yaml chore: Enable go fmt as a lint check for Go code (#11830) 2025-05-19 14:31:37 +00:00
.pylintrc chore(sdk): make kfp v2 hermetic (#7428) 2022-03-18 03:00:40 +00:00
.readthedocs.yml chore: Nest sdk docs (#11945) 2025-05-30 20:36:20 +00:00
.style.yapf chore: consistent yapf style config for the entire repo (#6963) 2021-11-30 20:38:30 +00:00
ADOPTERS.md chore: add c1 to ADOPTERS.md (#11954) 2025-06-03 13:53:14 +00:00
AUTHORS chore: set up AUTHORS file. Fixes #5470 (#5766) 2021-06-01 02:49:05 -07:00
CHANGELOG.md chore: bump master to release 2.5 (#11872) 2025-04-29 18:24:02 +00:00
CONTRIBUTING.md chore: add adr template/docs (#11437) 2024-12-05 21:50:00 +00:00
LICENSE Initial commit of the kubeflow/pipeline project. 2018-11-02 14:02:31 -07:00
Makefile [chore][backend] Add workflow to validate affected generated files (#11539) 2025-02-12 22:12:31 +00:00
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README.md chore: Adding Devin's DeepWiki to README (#11948) 2025-06-02 15:54:23 +00:00
RELEASE.md update release doc paths & make script executable (#11871) 2025-04-28 21:51:01 +00:00
ROADMAP.md chore: Update ROADMAP.md (#7752) 2022-05-18 17:48:26 +00:00
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developer_guide.md chore(backend): upgrade mysql to 8.4 (#11917) 2025-05-16 17:59:24 +00:00
go.mod chore(sdk): update go toolchain patch (#11845) 2025-04-21 22:14:30 +00:00
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mypy.ini chore(sdk): clean up v2 CLI (#7558) 2022-04-20 10:40:38 -06:00
package-lock.json chore(release): set up conventional commit changelog tool. Part of #3920 (#4033) 2020-06-23 03:51:40 -07:00
package.json chore(release): set up conventional commit changelog tool. Part of #3920 (#4033) 2020-06-23 03:51:40 -07:00
pytest.ini chore(sdk): remove kfp.deprecated from sdk, legacy samples, and legacy tests (#11366) 2024-11-12 17:26:18 +00:00

README.md

Kubeflow Pipelines

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Overview of the Kubeflow pipelines service

Kubeflow is a machine learning (ML) toolkit that is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable.

Kubeflow pipelines are reusable end-to-end ML workflows built using the Kubeflow Pipelines SDK.

The Kubeflow pipelines service has the following goals:

  • End to end orchestration: enabling and simplifying the orchestration of end to end machine learning pipelines
  • Easy experimentation: making it easy for you to try numerous ideas and techniques, and manage your various trials/experiments.
  • Easy re-use: enabling you to re-use components and pipelines to quickly cobble together end to end solutions, without having to re-build each time.

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.

Documentation

Get started with your first pipeline and read further information in the Kubeflow Pipelines overview.

See the various ways you can use the Kubeflow Pipelines SDK.

See the Kubeflow Pipelines API doc for API specification.

Consult the Python SDK reference docs when writing pipelines using the Python SDK.

Deep Wiki

Check out our AI Powered repo documentation on DeepWiki.

⚠️ Please note, this is AI generated and may not have completely accurate information.

Contributing to Kubeflow Pipelines

Before you start contributing to Kubeflow Pipelines, read the guidelines in How to Contribute. To learn how to build and deploy Kubeflow Pipelines from source code, read the developer guide.

Kubeflow Pipelines Community

Community Meeting

The Kubeflow Pipelines Community Meeting occurs every other Wed 10-11AM (PST).

Calendar Invite

Direct Meeting Link

Meeting notes

Slack

We also have a slack channel (#kubeflow-pipelines) on the Cloud Native Computing Foundation Slack workspace. You can find more details at https://www.kubeflow.org/docs/about/community/#kubeflow-slack-channels

Architecture

Details about the KFP Architecture can be found at Architecture.md

Blog posts

Acknowledgments

Kubeflow pipelines uses Argo Workflows by default under the hood to orchestrate Kubernetes resources. The Argo community has been very supportive and we are very grateful.