Kubeflow

  • Kubeflow Charmers | bundle
  • Cloud
Channel Revision Published
latest/candidate 294 24 Jan 2022
latest/beta 430 30 Aug 2024
latest/edge 423 26 Jul 2024
1.9/stable 432 03 Dec 2024
1.9/beta 420 19 Jul 2024
1.9/edge 431 03 Dec 2024
1.10/beta 433 24 Mar 2025
1.8/stable 414 22 Nov 2023
1.8/beta 411 22 Nov 2023
1.8/edge 413 22 Nov 2023
1.7/stable 409 27 Oct 2023
1.7/beta 408 27 Oct 2023
1.7/edge 407 27 Oct 2023
juju deploy kubeflow --channel 1.9/stable
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Charms in the Kubeflow bundle

admission-webhook Admission Webhook
argo-controller Argo Controller
dex-auth Dex Auth
envoy Envoy
istio-gateway Istio Gateway
istio-pilot Istio Pilot
jupyter-controller Jupyter Controller
jupyter-ui Jupyter Ui
katib-controller Katib Controller
mysql-k8s Mysql K8S
katib-db-manager Katib Db Manager
katib-ui Katib Ui
kfp-api Kfp Api
mysql-k8s Mysql K8S
kfp-metadata-writer Kfp Metadata Writer
kfp-persistence Kfp Persistence
kfp-profile-controller Kfp Profile Controller
kfp-schedwf Kfp Schedwf
kfp-ui Kfp Ui
kfp-viewer Kfp Viewer
kfp-viz Kfp Viz
knative-eventing Knative Eventing
knative-operator Knative Operator
knative-serving Knative Serving
kserve-controller Kserve Controller
kubeflow-dashboard Kubeflow Dashboard
kubeflow-profiles Kubeflow Profiles
kubeflow-roles Kubeflow Roles
kubeflow-volumes Kubeflow Volumes
metacontroller-operator Metacontroller Operator
minio Minio
mlmd Mlmd
oidc-gatekeeper Oidc Gatekeeper
pvcviewer-operator Pvcviewer Operator
tensorboard-controller Tensorboard Controller
tensorboards-web-app Tensorboards Web App
training-operator Training Operator

Charmed Kubeflow (CKF) is an open-source, end-to-end, production-ready MLOps platform on top of cloud-native technologies.

It translates Machine Learning (ML) steps into complete workflows, including training, tuning, and shipping of ML models. It enables automation of workflows, increases quality of models, and simplifies deployment of ML workloads into production in a reliable way.

CKF meets the need of building ML applications in a structured and consistent manner while contributing to higher productivity and better collaboration within teams.

It is intended for data scientists and ML engineers, providing an advanced toolkit to organise and scale their work.

In this documentation
Tutorial
Get started - a hands-on introduction to CKF for newcomers
How-to guides
Step-by-step guides covering key operations and common tasks with CKF
Explanation
Discussion and clarification of key topics		 Reference
Technical information, including specifications, APIs, settings and configuration

Project and community

Charmed Kubeflow is a member of the Ubuntu family. It’s an open-source project that welcomes community contributions, suggestions, fixes and constructive feedback.

Help improve this document in the forum (guidelines). Last updated a month ago.