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Machine Learning on Kubernetes

You're reading from Machine Learning on Kubernetes A practical handbook for building and using a complete open source machine learning platform on Kubernetes

Product type Paperback

Published in Jun 2022

Publisher Packt

ISBN-13 9781803241807

Length 384 pages

Edition 1st Edition

Languages

Python

Tools

Kubernetes

Concepts

Machine Learning

Authors (2):

Ross Brigoli

Faisal Masood

View More author details

Table of Contents (16) Chapters

Preface

1. Part 1: The Challenges of Adopting ML and Understanding MLOps (What and Why)

2. Chapter 1: Challenges in Machine Learning FREE CHAPTER

3. Chapter 2: Understanding MLOps

4. Chapter 3: Exploring Kubernetes

5. Part 2: The Building Blocks of an MLOps Platform and How to Build One on Kubernetes

6. Chapter 4: The Anatomy of a Machine Learning Platform

7. Chapter 5: Data Engineering

8. Chapter 6: Machine Learning Engineering

9. Chapter 7: Model Deployment and Automation

10. Part 3: How to Use the MLOps Platform and Build a Full End-to-End Project Using the New Platform

11. Chapter 8: Building a Complete ML Project Using the Platform

12. Chapter 9: Building Your Data Pipeline

13. Chapter 10: Building, Deploying, and Monitoring Your Model

14. Chapter 11: Machine Learning on Kubernetes

15. Other Books You May Enjoy

Running on Kubernetes

Using the ODH operator, the ML platform truly unlocks the full potential of Kubernetes as the infrastructure layer of your ML platform. The Operator Lifecycle Management (OLM) framework enables the ODH operator to simplify the operation and maintenance of the ML platform. Almost all operational work is done in a Kubernetes-native way, and you can even spin up multiple ML platforms with a few clicks. Kubernetes and the OLM also allow you to implement the Platform as Code (PaC) approach, enabling you to implement GitOps practices.

The ML platform you've seen in this book works well with vanilla Kubernetes instances or any other flavors of Kubernetes or even a Kubernetes-based platform. In fact, the original ODH repository was mainly designed and built for Red Hat OpenShift.

Avoiding vendor lock-ins

Kubernetes protects you from vendor lock-ins. Because of the extra layer of containerization and container orchestration, all your workloads do not run...

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Authors (2)

Faisal Masood

Faisal Masood

Faisal Masood is a cloud transformation architect at AWS. Faisal's focus is to assist customers in refining and executing strategic business goals. Faisal main interests are evolutionary architectures, software development, ML lifecycle, CD and IaC. Faisal has over two decades of experience in software architecture and development.

See other products by Faisal Masood

Brigoli

Brigoli

Ross Brigoli is a consulting architect at Red Hat, where he focuses on designing and delivering solutions around microservices architecture, DevOps, and MLOps with Red Hat OpenShift for various industries. He has two decades of experience in software development and architecture.

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