Integrating Feast Online Feature Store with KFServing

Explore the integration of Feast Online Feature Store with KFServing in this informative conference talk presented by Ted Chang and Chin Huang from IBM. Delve into the importance of feature stores in machine learning workflows and discover various feature store solutions. Learn about Feast's history, infrastructure, and its deployment in Kubernetes clusters. Gain insights into KFServing, its stack, supported frameworks, and storage options. Understand the concept of KFServing Inference Service and transformers, with a focus on KFServing with Feast Transformer. Watch a demonstration showcasing the practical implementation of these technologies. Conclude with a summary of key takeaways and explore other related talks from the Open Source Summit North America.

Intro
Agenda
Why Feature Store
Feature Stores Solutions
Feast History
Feast Infrastructure
Adopters and Contributors to Feast
Feast Deployment in Kubernetes Cluster
KFServing Introduction
KFServing Stack
Supported Frameworks and Storage
KFServing Inference Service
Transformers
KFServing with Feast Transformer
Demo
Summary
Open Source Summit North America Talks