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Accelerate DevOps with GitHub

Accelerate DevOps with GitHub

By : Michael Kaufmann
5 (11)
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Accelerate DevOps with GitHub

Accelerate DevOps with GitHub

5 (11)
By: Michael Kaufmann

Overview of this book

This practical guide to DevOps uses GitHub as the DevOps platform and shows how you can leverage the power of GitHub for collaboration, lean management, and secure and fast software delivery. The chapters provide simple solutions to common problems, thereby helping teams that are already on their DevOps journey to further advance into DevOps and speed up their software delivery performance. From finding the right metrics to measure your success to learning from other teams’ success stories without merely copying what they’ve done, this book has it all in one place. As you advance, you’ll find out how you can leverage the power of GitHub to accelerate your value delivery – by making work visible with GitHub Projects, measuring the right metrics with GitHub Insights, using solid and proven engineering practices with GitHub Actions and Advanced Security, and moving to event-based and loosely coupled software architecture. By the end of this GitHub book, you'll have understood what factors influence software delivery performance and how you can measure your capabilities, thus realizing where you stand in your journey and how you can move forward.
Table of Contents (31 chapters)
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1
Part 1: Lean Management and Collaboration
7
Part 2: Engineering DevOps Practices
14
Part 3: Release with Confidence
19
Part 4: Software Architecture
22
Part 5: Lean Product Management
25
Part 6: GitHub for your Enterprise

Experimentation with Feature Flags

Experimentation and A/B testing cannot only be done using Feature Flags. You can also develop containers in different branches and use Kubernetes to run different versions in production; however, this will increase your complexity in Git and does not scale well. You don't have the context for the users either, so gathering the data to prove or diminish your hypothesis is much harder. Most of the solutions for Feature Flags have built-in support for experiments, so this is the fastest way to get started.

To experiment, you define a hypothesis, conduct an experiment, and then learn from the results. An experiment can be defined as follows (see Figure 10.4):

  • Hypothesis: We believe {customer segment}, wants {product/feature} because {value prop}.
  • Experiment: To prove or disprove the preceding, the team will conduct an experiment.
  • Learning: The experiment will prove the hypothesis by impacting the following metrics.
...
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