KFServing - Model Monitoring with Apache Spark and Feature Store

Explore an open-source platform for serving and monitoring machine learning models at scale in this 29-minute talk from Databricks. Learn about KFServing, Kubeflow's model serving framework, and how it integrates with the Hopsworks Online Feature Store to enrich feature vectors. Discover the advantages of using Spark and Spark Streaming for continuous model monitoring, including data drift detection and performance analysis. Gain insights into implementing MLOps practices, automating repetitive tasks, and improving interoperability between tools. Watch a live demonstration of the platform in action and understand how to leverage these technologies for more effective model deployment and monitoring in production environments.

Intro
KFServing
Model Modeling
Online Monitoring
Data Validation
Data Validation Example
Demo
Questions