juju deploy kubeflow
|latest/stable||269||269||27 May 2021|
|latest/candidate||269||269||27 May 2021|
|latest/beta||269||269||27 May 2021|
|latest/edge||269||269||27 May 2021|
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Charmed Kubeflow is the full set Kubernetes operators to deliver the 30+ applications and services that make up the latest version of Kubeflow, for easy operations anywhere, from workstations to on-prem, to public cloud and edge.
A charm is a software package that includes an operator together with metadata that supports the integration of many operators in a coherent aggregated system. The individual charms that make up Charmed Kubeflow can be found under
This technology leverages the Juju Operator Lifecycle Manager to provide day-0 to day-2 operations of Kubeflow.
Visit charmed-kubeflow.io for more.
There are two possible paths, depending on your choice of Kubernetes:
- For any Kubernetes, follow the installation instructions.
- On MicroK8s, you simply have to enable the Kubeflow add-on.
Read the official documentation.
You can view pipelines from the Pipeline Dashboard available on the central
dashboard, or by going to
Pipelines are available either by the main dashboard, or from within notebooks via the fairing library.
Note that until https://github.com/kubeflow/pipelines/issues/1654 is resolved,
you will have to attach volumes to any locations that output artifacts are
written to, see the
attach_output_volume function in
pipline-samples/sequential.py for an example.
To submit a TensorFlow job to the dashboard, you can run this
kubectl create -n <NAMESPACE> -f path/to/job/definition.yaml
<NAMESPACE> matches the name of the Juju model that you're using,
path/to/job/definition.yaml should point to a
similar to the
mnist.yaml example found here.
Follow the official uninstall documentation.
For information on how to run the tests in this repo, see the tests README.