Description
An end-to-end example of deploying a machine learning product using Jupyter, Papermill, Tekton, GitOps and Kubeflow.
Summary
- The Problem Kubeflow is a fast-growing open source project that makes it easy to deploy and manage machine learning on Kubernetes.
- Reconciler + GitOps = CI/CD for ML With that background out of the way, let’s dive into how we built CI/CD for ML by combining the Reconciler and GitOps patterns.
- Importantly, all the steps in a Tekton task run on the same pod which allows data to be shared between steps using a pod volume.
- If a sync is needed the controller fires off a Tekton pipeline to perform the actual update.