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MLOps with Red Hat OpenShift

You're reading from MLOps with Red Hat OpenShift A cloud-native approach to machine learning operations

Product type Paperback

Published in Jan 2024

Publisher Packt

ISBN-13 9781805120230

Length 238 pages

Edition 1st Edition

Tools

MLOps

Concepts

Machine Learning

Authors (2):

Ross Brigoli

Faisal Masood

View More author details

Table of Contents (13) Chapters

Preface

1. Part 1: Introduction FREE CHAPTER

2. Chapter 1: Introduction to MLOps and OpenShift

3. Part 2: Provisioning and Configuration

4. Chapter 2: Provisioning an MLOps Platform in the Cloud

5. Chapter 3: Building Machine Learning Models with OpenShift

6. Part 3: Operating ML Workloads

7. Chapter 4: Managing a Model Training Workflow

8. Chapter 5: Deploying ML Models as a Service

9. Chapter 6: Operating ML Workloads

10. Chapter 7: Building a Face Detector Using the Red Hat ML Platform

11. Index

Why subscribe?

12. Other Books You May Enjoy

Optimizing cost for your ML platform

In this section, you will learn how to use different OpenShift capabilities with Red Hat Data Science to optimize the cost for your platform. While we will not dive deep into this topic, we will provide you with some basic concepts to continue optimizing your platform resources.

When you run any software on the Red Hat OpenShift platform, such as a Jupyter notebook, build pipelines, and model serving, all of it runs as containers on the platform. These containers run on the machines or worker nodes, which could be a VM in a cloud platform such as Amazon EC2. Let’s see how OpenShift provisions machines to run containers for your MLOps needs.

Machine management in OpenShift

Machine management is OpenShift’s capability to work with the cloud or on-premises infrastructure providers, such as Amazon Web Services (AWS) or VMware (VMW), and to provision and scale the machines for your workloads. OpenShift adapts to changing workloads...

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Authors (2)

Ross Brigoli

Ross 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.

See other products by Ross Brigoli

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

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