The Easiest Way to Run Google Vertex AI Pipelines

Machine learning teams don’t need Kubernetes today

New to ML pipelines? Having trouble maintaining and managing your Kubeflow instance on Kubernetes? Perhaps your ML team is small, and you’re wasting too much time implementing ML pipelines. Or you want to focus on your ML solutions rather than infrastructure tasks.

Let me introduce you Google Vertex AI Pipeline, a serverless product to run Kubeflow or TFX pipelines.

This article covers the steps needed to implement a reliable, reproducible and automated machine learning pipeline with Google Vertex AI.

Google Vertex AI and Kubeflow: An Introduction

Let’s start with a quick introduction to ML Pipelines. Do feel free to skip this section if you are already familiar with these topics.

ML Pipelines are there to connect the various steps of your ML solution. Kubeflow is a machine learning toolkit that provides a pipeline solution called Kubeflow Pipelines, built atop Kubernetes. Google introduced Vertex AI Pipelines because maintaining Kubernetes can be challenging and time-intensive. It’s a serverless product to run pipelines, so your machine learning team…