Activate and manage your feature flags

Kameleoon Feature Management & Experimentation capabilities make it possible to activate feature flags and run feature experiments on web and mobile applications.  Before you can start implementing feature flags and experiments in your code, you will have to install and set up a Kameleoon SDK (client-side or server-side). Refer to the developer documentation available for […]

This guide will help you create a new feature flag. What is feature management and feature experimentation? Access the Feature flag creation page On the side menu of the App, click on Feature flags to access the dedicated dashboard. Then click on the New feature flag button. Name your feature flag and choose the project […]

To learn how to create a new feature flag, please read our article on the subject. Access the Feature flags Dashboard To access the Feature flags Dashboard from the App, use the left side menu > Activate > Feature flags. Structure of the Feature flags Dashboard The dashboard is automatically organized by environment. By default, the […]

Approval workflows introduce a request-and-review mechanism for feature flag changes. Team members can request changes, and designated approvers can review and approve (or reject) these requests before they are applied. Approval workflows allows you to better control what changes are applied and which are not. Once approval settings are setup, flag changes made by certain […]

Your feature flag dashboard can help in managing technical debt in your codebase and proactively cleanup obsolete or stale flags. Flag creation When creating a new flag, you can define whether it’s a temporary or permanent type of flag. This distinction is crucial for managing technical debt effectively to keep track of their health and […]

You can define feature variables (Boolean, Number, String, JSON, JavaScript, or CSS) to remotely update the content of your feature flags in your chosen environment. There is no limit on the number of feature variables you can create. Creating feature variables are not necessary, but highly recommended before you create feature variations. There is no […]

You can create multiple Variations of your feature to choose which variant is delivered to each user evaluated by the flag.  How to create feature variations? Any variables you created in the Variables page can be customized for each individual variation you create, meaning you don’t need to hard-code any values in your code. Navigate […]

Kameleoon Environments are used to organize and align with distinct, segregated platforms or spaces within your technical architecture where your application(s) are deployed, tested, and run from. Once set up, environments offer a controlled and systematic approach to development, deployments and QA across multiple environments.  When you create a new project, Kameleoon will automatically create […]

The Rollout planner consists of several blocks. A. A header in the top left indicating the name of the flag, the associated sitecode (you can copy and paste it directly from here) and the feature key. Click the name to edit the flag’s details. B. A Setup menu to create and manage your feature variables […]

What are Rollout Rules?  You can leverage the Rollout Planner to be as selective and precise with your releases and tests as you want. Anything that is inside of a feature flag can be toggled on whenever you choose and for whoever you choose. Rollout rules are a sequence of actions that can be scheduled […]

Targeted Delivery is the simplest way to turn on a feature variation for some or all of your audience. You can use multiple Targeted Delivery rules to implement advanced rollout strategies that suit your needs. Use Targeted Delivery rules to gain rollout flexibility based on user attributes such as geographical region, demographical data, operating system […]

Progressive (or gradual) rollouts let you spread big or critical feature releases over a period of time by gradually rolling it out to an increasing audience over a period of time. You can customize the feature variation you want to roll out, the audience you want to target, as well as the interval and increment […]

With Experiments, you can create several variations of your features and test them using the Experiment rule to determine which one yields the best metrics or delivers the best UX. You can use variations and experiments together to quickly and continuously test and optimize your features.  To create a feature experiment, add a new rule […]

You can leverage the potential of Multi-Armed Bandit (MAB) optimizations in Kameleoon to achieve quick wins while maintaining significant lifts in performance. This article will discuss the implications and use cases of MAB algorithms for you to better determine when to choose MAB optimizations for your feature experimentation. Once you’ve set up your experiment (or […]

This feature allows you to manually redistribute traffic of your user segment towards the chosen variation(s) for any active rule. By reshuffling, you initiate a complete rebucketing process, which means that users may be exposed to different variations than before. This help document will guide you through the steps of using this feature and explain […]

For any type of rule that you add, the first step you see is a Targeting section that allows you to select an existing segment or create a new one.  Start by selecting one of the 3 targeting conditions available: Target all visitors: Includes your entire user base. Chosen by default. Target a segment: You […]

Optionally, you can schedule when a rule should activate or reactivate at a specific date and time. Selecting either start or end dates will show a calendar view for you to customize the date and the timezone for when you’d like to plan this rule to take effect or turn off. Note: Keep in mind […]

You can turn your feature flags ON or OFF. Choosing a default variation At the end of your rollout rules queue is a drop-down list that defines which variation will be delivered to users by default that are not targeted by any rule while your flag is on.  Example 1: If you want to roll […]

Automatic Rollbacks is a useful safeguard for your feature flags that allow you to proactively manage feature releases. This functionality allows you to set up custom rollback conditions, or ‘triggers’ which monitor your features’ performance to automatically turn off the respective rule or flag.  This guide will walk you through the process of setting up […]

The Activity Log is available for each feature flag you create and can be very useful for your product or engineering teams to monitor and troubleshoot their feature releases. This guide will cover how to use audit logs effectively to help your team keep track of flag changes and maintain transparency. Once you have created a […]

Goals are essentially the KPIs that are relevant to your product or feature which you can track for your features to measure performance of your release or experiments. When selected for a feature flag, goals can then be used across all of its environments (development, staging and production) and will be tracked for all delivery […]

The Rollout Planner page has a dedicated section to keep track of all feature experiments created under a feature flag. Once you have added at least one rule, navigate to the Reporting section on the left menu and at the bottom, click on Results. Once here, you will see two tabs: 1) Overview: This view […]

Managing third-party analytics tools for your feature flags is very simple once you have set up your integration already. Note: Integrations for third-party tools are only compatible with Web SDKS and currently not available for Mobile SDKs. To start, create a new flag or open an existing one. Then, in the left-side menu, navigate to […]

Are feature flags all you need to experiment? Feature experiments using feature flags is a proven way to enable a powerful and data-driven approach for all teams to test hypotheses and validate assumptions before fully releasing new features to all users.  By gradually rolling out experiments to targeted user segments, teams can gather valuable insights […]

If you want to QA a feature experiment or simply rollout a feature variation to an internal group of users, using a whitelist of users, combined with a targeted delivery rule is one of the easiest ways to achieve this goal.  For example, imagine that you want to release a new feature with 2 possible […]