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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

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781805120230
Length 238 pages
Edition 1st Edition
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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 (13) Chapters Close

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 12. Other Books You May Enjoy

Installing Pachyderm

Because Pachyderm is a Kubernetes-native platform, it can also natively run on OpenShift. Pachyderm is available as a Kubernetes operator in OperatorHub.

The following steps will guide you through the operator installation of Pachyderm:

  1. In the OpenShift console, navigate to Operators -> OperatorHub.
  2. Search for Pachyderm. You should see Pachyderm shown as a tile, as shown in Figure 2.35:
Figure 2.35 – OperatorHub showing Pachyderm

Figure 2.35 – OperatorHub showing Pachyderm

  1. If you are presented with two options, as shown in Figure 2.35, choose the one tagged as Certified and then click the Install button. Certified operators are operators that are verified by Red Hat to run in OpenShift.
  2. Use the default options in the Install Operator screen, as shown in Figure 2.36, and then click Install:
Figure 2.36 – Install Operator dialog of Pachyderm

Figure 2.36 – Install Operator dialog of Pachyderm

  1. Once the installation is complete, Pachyderm should be...
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