September 27-30, 2021
Seattle, Washington, USA + Virtual
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Monday, September 27 • 11:15am - 12:05pm
(VIRTUAL) Integrating Feast Online Feature Store with KFServing - Ted Chang & Chin Huang, IBM

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Having access to a consistent set of dataset features during different phases of the ML lifecycle is becoming critical. Companies that build and deploy machine learning models may need to manage hundreds of features, and they may even require using the latest features for real time prediction. Feast (Feature Store) attempts to tackle these problems by providing a standard interface and store for retrieving features needed for distributed model training and serving. In this talk, attendees will learn how to build a production ready feature store on Kubernetes by using Feast which will be used to serve the data to the model. Additionally, attendees will see how Feast can be used with KFServing, a serverless model inferencing engine, to retrieve stored features in real time. In this talk, we hope to share how users can get started with using Feast on Kubernetes for their ML needs. Here, we set up an end-to-end demo using Feast and  KFserving transformer on Kubernetes to demonstrate how online features can be served to the KFserving for real time inferencing.

avatar for Ted Chang

Ted Chang

Software Engineer, IBM
Ted Chang is software engineer in the IBM Cognitive Open Technologies Group focusing on software development in the machine learning space. He has worked on various open source projects from OpenStack, Kubernetes, and TensorFlow. Lately, he has been focusing on MLOps such as Kubeflow... Read More →
avatar for Chin Huang

Chin Huang

IBM, Software Engineer
Chin Huang is a senior software developer in the IBM Cognitive OpenTech Group. He's been active in the open source community for over six years, including OpenStack, Node.js, JanusGraph, and recently focused ONNX and Kubeflow. He is currently the owner of the ONNX to Tensorflow converter... Read More →

Monday September 27, 2021 11:15am - 12:05pm PDT
MeetingPlay Platform + Virtual Learning Lab