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

Understanding metrics

In general, when running any experiment, it is important to know what it is that is being measured to determine the success or failure of the test. There could be more than one metric being collected and analyzed, but for most experiments, there is just one. LaunchDarkly's implementation of experiments requires such a metric to determine the outcome of the investigation. The second screen of the Experiments dashboard shows all the metrics that have been set up for a project:

Figure 11.4 – The Metrics dashboard

Similar to the dashboards we have seen throughout this book, such as Feature flags and Users, there is the ability to search for metrics. This can be done by using their name or description. It is possible to filter the metrics and to sort the list by several attributes. The metrics themselves show how many flags have experiments set up (Flags) that use the metric, the type of event that the metric collects data on (Event...