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 |
| 1.10/stable | 436 | 07 Apr 2025 |
| 1.10/candidate | 434 | 02 Apr 2025 |
| 1.10/beta | 433 | 24 Mar 2025 |
| 1.9/stable | 432 | 03 Dec 2024 |
| 1.9/beta | 420 | 19 Jul 2024 |
| 1.9/edge | 431 | 03 Dec 2024 |
| 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 1.10/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:
The following guides cover common tasks and use cases for using Charmed Kubeflow (CKF).
This content is intended for end users.
Set up scheduling depending on your use case:
Learn how to customize the link configuration of the Kubeflow Central Dashboard:
Use PodDefaults to configure Kubernetes Pods:
Leverage NVIDIA with CKF:
- Use NVIDIA GPUs
- Deploy NVIDIA NIMs
- Launch NVIDIA NGC notebooks
- Serve a model using Triton Inference Server
Deploy KServe, Knative, and Istio charms on their own using the Autoscaling model serving:
Find out how to perform inference using programmatic access tokens: