You're reading from The Machine Learning Solutions Architect Handbook Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI

Product type Paperback

Published in Apr 2024

Publisher Packt

ISBN-13 9781805122500

Length 602 pages

Edition 2nd Edition

Languages

Python

Tools

MLOps

Concepts

Machine Learning

Author (1):

David Ping

View More author details

Table of Contents (19) Chapters

Preface

1. Navigating the ML Lifecycle with ML Solutions Architecture FREE CHAPTER

2. Exploring ML Business Use Cases

3. Exploring ML Algorithms

4. Data Management for ML

5. Exploring Open-Source ML Libraries

6. Kubernetes Container Orchestration Infrastructure Management

7. Open-Source ML Platforms

8. Building a Data Science Environment Using AWS ML Services

9. Designing an Enterprise ML Architecture with AWS ML Services

10. Advanced ML Engineering

11. Building ML Solutions with AWS AI Services

12. AI Risk Management

13. Bias, Explainability, Privacy, and Adversarial Attacks

14. Charting the Course of Your ML Journey

15. Navigating the Generative AI Project Lifecycle

16. Designing Generative AI Platforms and Solutions

17. Other Books You May Enjoy

18. Index

Introduction to containers

To understand Kubernetes, we first need to understand containers as they are the core building blocks of Kubernetes. A container is a form of operating system virtualization and is a very popular computing platform for software deployment and running modern software based on microservices architecture. A container allows you to package and run computer software with isolated dependencies. Compared to server virtualization, such as Amazon EC2 or VMware virtual machines, containers are more lightweight and portable, as they share the same operating system and do not contain operating system images in each container. Each container has its own filesystem, shares of computing resources, and process space for the custom applications running inside it.

The concept of containerization technology traced back to the 1970s with the chroot system and Unix Version 7. However, container technology did not gain much attention in the software development community...