Demo of Kubernetes at the Edge for AI Model Deployments - Myriam Gutierrez & Jacqueline Koehler
Channel: CNCF [Cloud Native Computing Foundation]
Date: 2024-03-27

Don't miss out! Join us at our next Flagship Conference: KubeCon + CloudNativeCon North America in Salt Lake City from November 12 - 15, 2024. Connect with our current graduated, incubating, and sandbox projects as the community gathers to further the education and advancement of cloud native computing. Learn more at https://kubecon.io

Demo of Kubernetes at the Edge for AI Model Deployments - Myriam Fentanes Gutierrez & Jacqueline Koehler, Red Hat

As a Machine Learning Operations (MLOps) Engineer focused on AI at the edge, you will be faced with many unique challenges and decisions. You may have many questions such as: How do I handle distributed architectures across hybrid environments? How do I manage all the data being produced at the edge and getting that data to the core hub for useful insights? What do I do with my old devices running critical analytics? How do I manage my far edge deployments that are disconnected?

There are multiple options to solve the above issues and the best option heavily depends on the industry and use case. Our goal is to help you with answering all of these questions so you can decide how to select the best deployment patterns for your AI at the edge. Using Kubernetes and Open Data Hub, we will show a live demo using MLOps pipelines, Open Cluster Management, and OpenTelemitry to deploy a model to the edge and gather, store, and forward key metrics to the central hub.