Training Operator
- Kubeflow Charmers
| Channel | Revision | Published | Runs on |
|---|---|---|---|
| latest/candidate | 622 | 01 Apr 2025 | |
| latest/beta | 605 | 10 Mar 2025 | |
| latest/edge | 622 | 27 Mar 2025 | |
| 1.9/stable | 623 | 07 Apr 2025 | |
| 1.9/candidate | 623 | 02 Apr 2025 | |
| 1.9/edge | 623 | 01 Apr 2025 | |
| 1.8/stable | 545 | 11 Oct 2024 | |
| 1.8/edge | 598 | 21 Feb 2025 | |
| 1.7/stable | 347 | 23 Feb 2024 | |
| 1.7/edge | 516 | 28 Aug 2024 | |
| 1.6/stable | 305 | 09 Oct 2023 | |
| 1.6/beta | 190 | 28 Mar 2023 | |
| 1.6/edge | 305 | 25 Sep 2023 |
juju deploy training-operator --channel 1.9/stable
Deploy Kubernetes operators easily with Juju, the Universal Operator Lifecycle Manager. Need a Kubernetes cluster? Install MicroK8s to create a full CNCF-certified Kubernetes system in under 60 seconds.
Platform:
training-operator is a Kubernetes charm that’s part of the Kubeflow bundle.
This charm automates the deployment of Kubeflow’s Training Operator. This makes it easier to perform distributed and non-distributed model training using TensorFlow, PyTorch, and other frameworks.
Project and community
Training Operator is a member of the Ubuntu family. It’s an open source project that warmly welcomes community projects, contributions, suggestions, fixes and constructive feedback.
Thinking about using Training Operator for your next project? Get in touch!