Book Image

DevOps Culture and Practice with OpenShift

By : Tim Beattie, Mike Hepburn, Noel O'Connor, Donal Spring, Ilaria Doria
Book Image

DevOps Culture and Practice with OpenShift

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)
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

Conclusion

In this chapter, we focused on how we are going to deliver the outcomes set in the previous section.

Figure 11.36: Adding practices to navigate us through Options

We explored the User Story Mapping and Value Slicing practices and how we take all of the information captured in Discovery practices and push it through these tools. We also showed how using some helpful practices to look at the same information with slightly different lenses –Impact versus Effort Prioritization and How/Now/Wow Prioritization – can help improve Value Slicing. Where proposed feature areas would benefit from a deeper dive to understand the value, we recommended the Design Sprint as an option.

We showed how these practices drive the initial Product Backlog prioritized by value and how this produces a living, breathing artifact that will be subject to continuous Product Backlog Refinement as we gather more learning, feedback, and metrics for our delivery...