Community

You are viewing documentation for Kubeflow 0.3

This is a static snapshot from the time of the Kubeflow 0.3 release.
For up-to-date information, see the latest version.

In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, education, socio-economic status, nationality, personal appearance, race, religion, or sexual identity and orientation.

The Kubeflow community is guided by our Code of Conduct, which we encourage everybody to read before participating.

Community discussions

There are many ways to contribute! Join one of our communication channels, attend a community meeting, get to know the community, discuss updates, suggest exciting new integrations.

Community meetings

Meeting calendar (iCal version).

Meeting notes.

If your group has a regular meeting, talk to @ewilderj about getting it added to the calendar.

Kubeflow community call

The project team holds a weekly community call on Tuesdays. This call alternates weekly between US East/EMEA and US West/APAC friendly times. Joining the kubeflow-discuss mailing list will automatically send you calendar invitations for the meetings, or you can subscribe to the community meeting calendar above.

Agenda, notes, and a reminder of the next call are sent to the kubeflow-discuss mailing list.

Forums and mailing groups

Summary:

Topic Mailing list Slack
General discussion kubeflow-discuss #general
TF Operator (Github) tf-operator #tf-operator
Community meeting chat n/a #community

Slack server: kubeflow.slack.com

Who should consider contributing to Kubeflow?

  • Folks who want to add support for other ML frameworks (e.g. PyTorch, XGBoost, scikit-learn, etc…)
  • Folks who want to bring more Kubernetes magic to ML (e.g. ISTIO integration for prediction)
  • Folks who want to make Kubeflow a richer ML platform (e.g. support for ML pipelines, hyperparameter tuning)
  • Folks who want to tune Kubeflow for their particular Kubernetes distribution or Cloud
  • Folks who want to write tutorials or blog posts showing how to use Kubeflow to solve ML problems

For details on contributing please look at the contributor’s guide.