Building and Running AI, ML, and Data Science Workloads in Containers

When: Wednesday, September 10th, 2025 | 12pm - 1pm EDT

Schedule: 1-Hour Free Webinar

Where: Online - Live Training

If we want to run AI, ML, or Data Science workloads in containers (for local development or production on Kubernetes), we need to build container images. Doing that with a Dockerfile is fairly straightforward, but is it the best method?

In this talk, we’ll take a well-known speech-to-text model (Whisper) and show how to install its code and dependencies in a container. We’ll test various methods and compare the outcomes in terms of image size and build time. We’ll also show how to switch versions DRY-style (without maintaining multiple Dockerfiles!), how to leverage newer techniques like BuildKit cache mounts, and we’ll discuss other issues like the use of Alpine with Python, progressive image loading, and model loading.

Our specific example will focus on a Python app using packages like PyTorch, but the techniques that we will show can be generalized to other packages and even to other languages.

About Jérôme Petazzoni:

Ardan Labs Lead Kubernetes & Docker Instructor

Jérôme was part of the team that built, scaled, and operated the dotCloud PAAS, before that company became Docker. He loves to share what he knows, which led him to give hundreds of talks and demos on containers, Docker, and Kubernetes.