Book Image

Feature Management with LaunchDarkly

By : Michael Gillett
Book Image

Feature Management with LaunchDarkly

By: Michael Gillett

Overview of this book

Over the past few years, DevOps has become the de facto approach for designing, building, and delivering software. Feature management is now extending the DevOps methodology to allow applications to change on demand and run experiments to validate the success of new features. If you want to make feature management happen, LaunchDarkly is the tool for you. This book explains how feature management is key to building modern software systems. Starting with the basics of LaunchDarkly and configuring simple feature flags to turn features on and off, you'll learn how simple functionality can be applied in more powerful ways with percentage-based rollouts, experimentation, and switches. You'll see how feature management can change the way teams work and how large projects, including migrations, are planned. Finally, you'll discover various uses of every part of the tool to gain mastery of LaunchDarkly. This includes tips and tricks for experimentation, identifying groups and segments of users, and investigating and debugging issues with specific users and feature flag evaluations. By the end of the book, you'll have gained a comprehensive understanding of LaunchDarkly, along with knowledge of the adoption of trunk-based development workflows and methods, multi-variant testing, and managing infrastructure changes and migrations.
Table of Contents (18 chapters)
1
Section 1: The Basics
5
Section 2:Getting the Most out of Feature Management
11
Section 3: Mastering LaunchDarkly

Combining ring and percentage rollouts

Before we finish this chapter, I want to discuss of using both ring and percentage rollouts as it provides more opportunities for testing and validating the effectiveness of new features. The most common combination of these two strategies is to start with a ring rollout process, where QA engineers or stakeholders can sign off that the feature is in a position to be presented to real customers. Once that happens, the feature can then be targeted at customers using the percentage rollout.

The following screenshot shows how a feature flag could be configured to target specific users within either a QA or Stakeholders segment, while also serving all other customers with a 50/50 chance of having the feature enabled. The two segments would have specific users added to them (likely to be people within the company) rather than targeting the feature based on the customer's attributes:

Figure 4.16 – Combining the ring...