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.
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​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.
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​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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