Kubeflow is an open source MLOps platform for efficient AI and ML from research through development to production. Based on fully supported, best-of-breed open source technologies including Kubeflow, MLFlow and Tensorflow, Charmed Kubeflow enables secure, repeatable and efficient implementation of AI/ML applications from conception to production. Fully extensible Python and R support to futureproof your investment.

With Canonical's Charmed Kubeflow, data labs and MLOps teams need only train their data scientists and data engineers once to work efficiently. Charmed Kubeflow offers a centralized, browser-based data lab MLOps platform, improving governance and enhancing productivity. The appliance allows you to quickly spin up a Charmed Kubeflow instance, on a single node Kubernetes cluster, such that you could experiment and get your ML jobs automated. It will take you up to 40 minutes to have it running, but once you are up, you get access to all the features and capabilities that the tool has. By using Canonical's solution, on top of the upstream project features, you will get access to more recent, supported versions of Kubernetes as well as security patching of the images, upgrades and updates suport.

Once the appliance is deployed, you can access the dashboard by following the instructions from below:

• In the terminal please run: kubectl get services -n kubeflow
• On your computer, go to Settings > Network > Network Proxy, and enable SOCKS proxy pointing to: 127.0.0.1:9999
• Head over to the http://10.64.140.43.nip.io/  to access the Dashboard. Use the credentials from the form.

Please note that internet connection is required in order to deploy the product. The following components are downloaded as part of the bundle: Notebook, Katib, KServe, Pipeline, Tensorboard. This AMI requires an ongoing internet connection, in order to have all components of the bundle correctly. The dashboard access needs network proxy changes. The bundle components are subject to changes at any update.