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DevOps Culture and Practice with OpenShift

You're reading from   DevOps Culture and Practice with OpenShift Deliver continuous business value through people, processes, and technology

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Product type Paperback
Published in Aug 2021
Publisher Packt
ISBN-13 9781800202368
Length 812 pages
Edition 1st Edition
Concepts
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Authors (5):
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Noel O’Connor Noel O’Connor
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Noel O’Connor
Mike Hepburn Mike Hepburn
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Mike Hepburn
Ilaria Doria Ilaria Doria
Author Profile Icon Ilaria Doria
Ilaria Doria
Donal Spring Donal Spring
Author Profile Icon Donal Spring
Donal Spring
Tim Beattie Tim Beattie
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Tim Beattie
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Toc

Table of Contents (30) Chapters Close

Preface Acknowledgements Section 1: Practices Make Perfect FREE CHAPTER
1. Introduction — Start with Why 2. Introducing DevOps and Some Tools 3. The Journey Ahead Section 2: Establishing the Foundation
4. Open Culture 5. Open Environment and Open Leadership 6. Open Technical Practices – Beginnings, Starting Right 7. Open Technical Practices — The Midpoint Section 3: Discover It
8. Discovering the Why and Who 9. Discovering the How 10. Setting Outcomes Section 4: Prioritize It
11. The Options Pivot Section 5: Deliver It
12. Doing Delivery 13. Measure and Learn Section 6: Build It, Run It, Own It
14. Build It 15. Run It 16. Own It Section 7: Improve It, Sustain It
17. Improve It 18. Sustain It Index
Appendix A – OpenShift Sizing Requirements for Exercises 1. Appendix B – Additional Learning Resources

The Not Safe For Families (NSFF) Component

As we mentioned earlier, one of the major issues that we faced when running the first generation of PetBattle was online trolls uploading inappropriate images to the system. This added to the operational overhead of running the platform because the PetBattle founders would have to search MongoDB for the offending images and remove them by hand—very tedious!

Ever innovating, the team decided to try and come up with an automated solution to this problem. One approach we decided to investigate was to use artificial intelligence (AI) to perform image classification on the uploaded images and incorporate this into the platform.

The field of AI in itself is a fascinating area of expertise that we won't even slightly go into here, other than to say that we are using a pre-trained image classification model served by the open source TensorFlow machine learning platform.

Great, but how do we go about running this on OpenShift?

...
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