kubeflow-dashboard-operator: A Python repository from Canonical

Kubeflow Dashboard Operator - a component of the Charmed Kubeflow distribution from Canonical

This repository hosts the Kubeflow Dashboard operaotr (see CharmHub.

Upstream documentation can be found at https://www.kubeflow.org/docs/components/central-dash/overview/

Usage

The Kubeflow Dashboard Operator may be deployed using the Juju command line as follows

juju deploy kubeflow-dashboard --trust

The dashboard can't be deployed without the Kubeflow profiles service (otherwise the charm will stuck in waiting state). Please deploy the kubeflow-pipelines operator with

juju deploy kubeflow-pipelines --trust

And create a relation to dashboard:

juju relate kubeflow-profiles kubeflow-dashboard

Managing Dashboard Sidebar Links

Links in the dashboard can be managed through:

relating applications to this charm on the sidebar relation
adding sidebar links through the additional-sidebar-links config option.

Sidebar item ordering can be managed through the sidebar-link-order config option.

Adding Sidebar Links through the `sidebar` Relation

To relate an application to this charm, use the charm library for the KubeflowDashboardSidebarRequirer. See that file for usage instructions.

Adding Sidebar Links through the `additional-sidebar-links` Config

The additional-sidebar-links config allows for users to specify YAML or JSON input defining sidebar links. For example, you can define a file my_links.yaml:

- text: Some link
  link: /some-page
  type: item
  icon: book
- text: Some other link
  link: /some-other-page
  type: item
  icon: book

Where:

text: the text shown on the sidebar
link: the relative link within the platform (cannot be an external link - must be something that shares our gateway)
type: always item
icon: any icon from here

To pass this to Juju, do:

juju config kubeflow-dashboard additional-sidebar-links=@my_links.yaml

To edit existing links, export them to a file, edit the file, then import back to Juju:

juju config kubeflow-dashboard additional-sidebar-links > links_to_edit.yaml

# edit the file

juju config kubeflow-dashboard additional-sidebar-links=@links_to_edit.yaml

Define the Order of Sidebar Links

You can define the order of the sidebar links via a YAML or JSON list of strings in the sidebar-link-order config. For example:

juju config kubeflow-dashboard sidebar-link-order='["link1 text", "link2 text"]'

Where each string in the list is the text value that shows in the sidebar. The charm will order the sidebar links such that:

links that are included in sidebar-link-order, in the order from that configuration
any remaining links, in alphabetical order

Any link text that is defined in sidebar-link-order but not matching a sidebar item will be silently ignored, this way you can set defaults without needing to update them if links are removed.

Looking for a fully supported platform for MLOps?

Canonical Charmed Kubeflow is a state of the art, fully supported MLOps platform that helps data scientists collaborate on AI innovation on any cloud from concept to production, offered by Canonical - the publishers of Ubuntu.

Charmed Kubeflow is free to use: the solution can be deployed in any environment without constraints, paywall or restricted features. Data labs and MLOps teams only need to train their data scientists and engineers once to work consistently and efficiently on any cloud – or on-premise.

Charmed Kubeflow offers a centralised, browser-based MLOps platform that runs on any conformant Kubernetes – offering enhanced productivity, improved governance and reducing the risks associated with shadow IT.

Learn more about deploying and using Charmed Kubeflow at https://charmed-kubeflow.io.

Key features

Centralised, browser-based data science workspaces: familiar experience
Multi user: one environment for your whole data science team
NVIDIA GPU support: accelerate deep learning model training
Apache Spark integration: empower big data driven model training
Ideation to production: automate model training & deployment
AutoML: hyperparameter tuning, architecture search
Composable: edge deployment configurations available

What’s included in Charmed Kubeflow 1.4

LDAP Authentication
Jupyter Notebooks
Work with Python and R
Support for TensorFlow, Pytorch, MXNet, XGBoost
TFServing, Seldon-Core
Katib (autoML)
Apache Spark
Argo Workflows
Kubeflow Pipelines

Why engineers and data scientists choose Charmed Kubeflow

Maintenance: Charmed Kubeflow offers up to two years of maintenance on select releases
Optional 24/7 support available, contact us here for more information
Optional dedicated fully managed service available, contact us here for more information or learn more about Canonical’s Managed Apps service.
Portability: Charmed Kubeflow can be deployed on any conformant Kubernetes, on any cloud or on-premise

Documentation

Please see the official docs site for complete documentation of the Charmed Kubeflow distribution.

Bugs and feature requests

If you find a bug in our operator or want to request a specific feature, please file a bug here: https://github.com/canonical/dex-auth-operator/issues

License

Charmed Kubeflow is free software, distributed under the Apache Software License, version 2.0.

Contributing

Canonical welcomes contributions to Charmed Kubeflow. Please check out our contributor agreement if you're interested in contributing to the distribution.

Security

Security issues in Charmed Kubeflow can be reported through LaunchPad. Please do not file GitHub issues about security issues.

canonical/kubeflow-dashboard-operator