Kevin Dubois & Cedric Clyburn
Bootable AI Containers with Podman Desktop
#1about 3 minutes
Introducing bootable containers and the CNCF donation
An overview of the session's agenda and the announcement of Red Hat's container tools, including bootable containers, being donated to the CNCF.
#2about 4 minutes
Solving OS management challenges with bootable containers
Bootable containers apply the immutable, standardized principles of application containers to entire operating systems to prevent configuration drift.
#3about 3 minutes
The workflow for deploying and updating bootable systems
A container file is used to build a bootable image, which is then converted to a disk image for deployment and can be updated by pulling a new version from a registry.
#4about 4 minutes
Building a bootable OS image with a container file
The `bootc` tool manages updates and rollbacks, while a container file defines the OS layers, packages, and applications, and you can even build a custom base image.
#5about 3 minutes
Why bootable containers are ideal for AI and ML stacks
Packaging AI/ML stacks as bootable containers solves dependency issues and allows models to run closer to the hardware for faster inference.
#6about 2 minutes
Simplifying the build process with Podman Desktop
Podman Desktop and its extensions provide a user-friendly interface to build a bootable container image and export it to various disk formats.
#7about 5 minutes
Demo: Developing a local AI code assistant application
A demonstration of building and running a Python-based AI code generation application as a standard container using the Podman Desktop AI Lab extension.
#8about 7 minutes
Demo: Packaging the AI app as a bootable container
The AI application is packaged into a bootable CentOS Stream image using a container file that includes the model, server, and systemd services.
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