kubeflow lite #40
Kubeflow Operators
Introduction
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 charms/
.
This technology leverages the Juju Operator Lifecycle Manager to provide day-0 to day-2 operations of Kubeflow.
Visit charmed-kubeflow.io for more.
Install
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.
Documentation
Read the official documentation.
Usage details
Argo UI
You can view pipelines from the Pipeline Dashboard available on the central
dashboard, or by going to /argo/
.
Pipelines
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.
TensorFlow Jobs
To submit a TensorFlow job to the dashboard, you can run this kubectl
command:
kubectl create -n <NAMESPACE> -f path/to/job/definition.yaml
Where <NAMESPACE>
matches the name of the Juju model that you're using,
and path/to/job/definition.yaml
should point to a TFJob
definition
similar to the mnist.yaml
example found here.
TensorFlow Serving
Uninstall
Follow the official uninstall documentation.
Tests
For information on how to run the tests in this repo, see the tests README.