Data Science Meets Devops: MLOps with Jupyter, Git, & Kubernetes

By Kubeflow - 2020-08-01

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.

 

Topics

  1. Backend (0.3)
  2. Management (0.12)
  3. NLP (0.1)

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