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DevOps Culture and Practice with OpenShift

DevOps Culture and Practice with OpenShift

By : Tim Beattie, Mike Hepburn, Noel O'Connor, Donal Spring, Ilaria Doria
4.4 (7)
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DevOps Culture and Practice with OpenShift

DevOps Culture and Practice with OpenShift

4.4 (7)
By: Tim Beattie, Mike Hepburn, Noel O'Connor, Donal Spring, Ilaria Doria

Overview of this book

DevOps Culture and Practice with OpenShift features many different real-world practices - some people-related, some process-related, some technology-related - to facilitate successful DevOps, and in turn OpenShift, adoption within your organization. It introduces many DevOps concepts and tools to connect culture and practice through a continuous loop of discovery, pivots, and delivery underpinned by a foundation of collaboration and software engineering. Containers and container-centric application lifecycle management are now an industry standard, and OpenShift has a leading position in a flourishing market of enterprise Kubernetes-based product offerings. DevOps Culture and Practice with OpenShift provides a roadmap for building empowered product teams within your organization. This guide brings together lean, agile, design thinking, DevOps, culture, facilitation, and hands-on technical enablement all in one book. Through a combination of real-world stories, a practical case study, facilitation guides, and technical implementation details, DevOps Culture and Practice with OpenShift provides tools and techniques to build a DevOps culture within your organization on Red Hat's OpenShift Container Platform.
Table of Contents (30 chapters)
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Free Chapter
2
Section 1: Practices Make Perfect
6
Section 2: Establishing the Foundation
11
Section 3: Discover It
15
Section 4: Prioritize It
17
Section 5: Deliver It
20
Section 6: Build It, Run It, Own It
24
Section 7: Improve It, Sustain It
27
Index
Appendix B – Additional Learning Resources

Testing Testing Testing!

Up to this point, we've spoken about some of the tools we can use to move application code from ideas through compilation and into deployment. But how do we know the stuff we've built is actually working as we expect it to? If we create a pipeline that just compiles code and moves it to production – is it done? No, there are testing quality steps and gates that we need to introduce into our software pipelines!

The Test Automation Pyramid

How do we know our feature works as we expect it to? We should test it and see! It is not always clear how we should test our feature, nor is it clear when we have done too much or not enough testing. Should we create test instructions and manually test the feature? Should we test the feature in isolation? Should we test all its constituent parts or just the whole thing? What is a definition of a unit test exactly?

Let's face it, testing is complicated. We are going to advocate for creating not...

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