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

What Did We Learn?

In Chapter 13, Measure and Learn, we explored the techniques that we use to measure and learn from the increments of the products we deliver in a Delivery Loop by measuring the following:

  • Feedback from Showcase and Retrospective events
  • Learning from user testing
  • Capturing the results of experiments run
  • Service delivery and operational performance
  • Service level agreements, service level indicators, and service level objectives
  • Security
  • Performance
  • Culture
  • Application metrics
  • Infrastructure platform and resource usage

This learning is very important and should drive conversations, inferences, and conclusions about what was learned. This is why visualizing these metrics is so powerful. Instantly, we can all see what the current measure is, what the measure was before the last iteration of the Delivery Loop, and what the target measure is to achieve the desired outcome and impact.

If the conversation suggests we are...