welcome
Thank you for purchasing the MEAP for Real-World ML Systems on Kubernetes. We’ve written this book to guide you through the process of creating robust, scalable machine learning systems using Kubernetes, without requiring any prior Kubernetes knowledge.
As someone who has spent years architecting and deploying systems in production environments, I've often found myself wishing for a comprehensive resource that bridges the gap between machine learning and modern cloud-native infrastructure. This book is my attempt to fill that void, providing a practical, hands-on approach to building ML systems that can thrive in real-world production scenarios.
- Throughout this book, we'll cover a wide range of essential topics:
- Building an MLOps platform on Kubernetes
- Leveraging Kubernetes to scale data analytics
- Parallelizing machine learning training to accelerate model development
- Reliably serving ML models
- Implementing observability and security for ML applications running on Kubernetes
What sets this book apart is its practical focus. Every concept is taught through the lens of operating ML applications, making the material immediately applicable to your work. The blueprints provided are production-ready, allowing you to implement what you've learned with confidence.