Feature Flag System

What is a feature flag system?

A feature flag system is a software development technique that allows you to control the visibility and accessibility of features within your application. It acts as a powerful tool for managing the release process, enabling gradual rollouts, targeted deployments, and experimentation.

At its core, a feature flag system consists of conditional statements wrapped around specific parts of your codebase. These flags can be toggled on or off, either at runtime or build time, to hide or expose certain functionalities without requiring a full redeployment.

In modern software development, feature flag systems have become increasingly important due to their ability to mitigate risks associated with releasing new features. By decoupling feature rollout from code deployment, you can safely introduce changes to a subset of users, monitor their impact, and make data-driven decisions before exposing the feature to your entire user base.

The key components of a feature flag system include:

  1. Flag management: A centralized interface for creating, updating, and retiring feature flags across your application.

  2. Targeting rules: Flexible configuration options to control which users or segments have access to specific features based on attributes like user ID, location, or device type.

  3. Integration methods: Various ways to integrate feature flags into your codebase, such as using conditional statements, dependency injection, or a dedicated client library.

By leveraging these components effectively, you can transform your development and deployment processes, enabling faster iteration, reduced risk, and improved collaboration between teams.

Core components of feature flag systems

Flag evaluation and decision logic

  • Flag evaluation determines the state of a flag for each user request. This involves processing targeting rules and segmentation criteria.

  • The decision logic uses the evaluated flag state to control feature visibility and behavior. It's typically implemented using conditional statements or polymorphic dispatch.

Client SDKs and API integrations

  • Client SDKs provide language-specific libraries for integrating feature flags into your application code. They handle flag evaluation and expose APIs for controlling feature behavior.

  • Server-side API integrations allow you to manage flags and retrieve flag states via HTTP endpoints. This is useful for languages without dedicated SDKs or for implementing custom evaluation logic.

Real-time flag updates and caching

  • Real-time flag updates ensure that changes to flag configurations take effect immediately across all clients. This is typically achieved through webhooks, server-sent events, or long-polling mechanisms.

  • Caching mechanisms help improve performance by storing evaluated flag states locally. This reduces the need for constant network communication with the feature flag system.

Analytics and experimentation capabilities

  • Analytics provide insights into how users interact with different feature variations. This includes metrics like engagement, conversion rates, and performance data.

  • Experimentation capabilities enable you to run A/B tests, multivariate tests, and other controlled experiments using feature flags. This helps you make data-driven decisions about feature rollouts and optimizations.

Access control and collaboration features

  • Access control mechanisms ensure that only authorized team members can modify flag configurations. This typically involves role-based permissions and audit logging.

  • Collaboration features facilitate teamwork and communication around feature flag management. Examples include change history, comments, and notifications for flag updates.

Integration with CI/CD pipelines

  • Continuous integration (CI) pipelines can incorporate feature flag checks to ensure that new code changes are properly flagged and tested. This helps catch issues early in the development process.

  • Continuous delivery (CD) workflows can leverage feature flags to enable progressive rollouts and reduce the risk of deployments. Flags can be gradually enabled for subsets of users before a full release.

Join the #1 experimentation community

Connect with like-minded product leaders, data scientists, and engineers to share the latest in product experimentation.

Try Statsig Today

Get started for free. Add your whole team!

Why the best build with us

OpenAI OpenAI
Brex Brex
Notion Notion
SoundCloud SoundCloud
Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
We use cookies to ensure you get the best experience on our website.
Privacy Policy