Workshop: Introduction to Kubeflow and Kubeflow Pipelines (Afternoon Session)

Location: Bayview A

Duration: 1:00pm - 4:00pm

Day of week: Thursday

Level: All


A laptop with a modern browser like Chrome.

Some familiarity with ML, Python, and Kubernetes may be useful, but is not required.

Kubeflow is an OSS machine learning stack that runs on Kubernetes. The Kubeflow project is dedicated to making deployments of ML workflows on Kubernetes simple, portable, and scalable. In this workshop, you will learn how to install and use Kubeflow, including Kubeflow Pipelines, to support an end-to-end ML workflow.  

During the workshop, you'll install Kubeflow from scratch, see how to use Kubeflow's multi-user Jupyter notebook servers and other core components, and build and run Kubeflow Pipelines that support full ML workflows, using both the Pipelines UI and its SDK.  In the process, we'll look at how you can use logging, metrics and visualizations, and metadata/artifact tracking, to support ML workflow evaluation and reproducibility.

Speaker: Amy Unruh

Staff Developer Relations Engineer @Google Cloud Platform

Amy Unruh is a Staff Developer Relations Engineer for the Google Cloud Platform, where she focuses on machine learning and data analytics, as well as other Cloud Platform technologies. Amy has an academic background in CS/AI, and has also worked at several startups, done industrial R&D, and published a book on App Engine.

Find Amy Unruh at

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