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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

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Product type Paperback
Published in Jun 2022
Publisher Packt
ISBN-13 9781803241807
Length 384 pages
Edition 1st Edition
Languages
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Authors (2):
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Ross Brigoli Ross Brigoli
Author Profile Icon Ross Brigoli
Ross Brigoli
Faisal Masood Faisal Masood
Author Profile Icon Faisal Masood
Faisal Masood
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Toc

Table of Contents (16) Chapters Close

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

Understanding Operators

In traditional information technology (IT) organizations, specialized and dedicated teams were required to maintain applications and other software components such as databases, caches, and messaging components. Those teams were continuously observing the software ecosystem and doing specific things such as taking backups for databases, upgrading and patching newer versions of software components, and more.

Operators are like system administrators or engineers, continuously monitoring applications running on the Kubernetes environment and performing operational tasks associated with the specific component. In other words, an Operator is an automated software manager that manages the installation and life cycle of applications on Kubernetes.

Put simply, instead of you creating and updating Kubernetes Objects (Deployment, Ingress, and so on), the Operator takes this responsibility based on the configuration you provide. The configuration that directs the...

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