Deploying ML Models with Kubernetes
A hands-on introduction to serving machine learning models in production - Alexey Grigorev
This is the third workshop in our ML series on ML model deployment.
Building on the FastAPI service created in Part 1, we’ll now show how to deploy that service using Kubernetes, the industry standard for managing containerized applications in production.
Led by Alexey Grigorev, this workshop focuses on infrastructure, orchestration, and scaling.
What You'll Learn
How to containerize a model and preprocessing step as microservices
How to use Docker Compose to test your setup locally
How to deploy your services to Kubernetes
How to connect everything together into a working ML system
The basics of using EKS (Elastic Kubernetes Service) for managed deployments
It will be a live demo with practical tips and a chance to ask your questions. This workshop gives you a real feel for how ML models are deployed in real-world environments.
Thinking About ML Zoomcamp?
This workshop reflects the updated content of Module 5 in the ML Zoomcamp, giving you a taste of modern ML deployment practices you'll explore in the course.
ML Zoomcamp is our free 4-month course that takes you from beginner to advanced ML engineer. It covers the fundamentals of ML, from regression and classification to deployment and deep learning.
The new cohort of the ML Zoomcamp starts on September 15, 2025. You can join it by registering here.
About the Speaker
Alexey Grigorev is the Founder of DataTalks.Club and creator of the Zoomcamp series.
Alexey is a seasoned software and ML engineer with over 10 years in engineering and 6+ years in machine learning. He has deployed large-scale ML systems at companies like OLX Group and Simplaex, authored several technical books including Machine Learning Bookcamp, and is a Kaggle Master with a 1st place finish in the NIPS'17 Criteo Challenge.
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