Table of Contents

Key takeaway

Feature flags, also known as feature toggles, are a software development technique that allows developers to toggle features on and off at runtime without deploying new code. This article explores how feature flags can help teams release new features incrementally, manage risk during deployments, and gather feedback from users in real-time.


Feature flags, also known as feature toggles or feature switches, are a software development technique that allows developers to enable or disable certain features in an application or system. They provide a way to control the release and deployment of new features, allowing for gradual rollouts, A/B testing, and targeted feature releases.

At its core, a feature flag is a conditional statement that determines whether a particular feature should be enabled or disabled. This condition can be based on various factors such as user roles, user preferences, environment variables, or even specific dates and times.

Importance of feature flags to the modern software delivery lifecycle

Feature flags play a crucial role in the modern software delivery lifecycle, offering significant importance and benefits to development teams. They provide a flexible and controlled approach to feature releases, allowing for continuous delivery, risk mitigation, and experimentation.

One of the key reasons why feature flags are important is their ability to enable continuous delivery. By decoupling feature releases from code deployments, developers can release new features independently and frequently. This ensures a faster time-to-market and allows for iterative development and feedback-driven improvements.

Feature flags also play a vital role in risk mitigation. By gradually rolling out features to a subset of users or specific user segments, developers can monitor performance, gather feedback, and address any issues before a full-scale release. This controlled approach minimizes the impact of potential bugs or usability problems on a wider user base.

Feature flags also enable personalized experiences for users. By toggling features based on user roles, preferences, or other conditions, developers can tailor the application to meet individual needs. This personalization enhances user satisfaction, engagement, and retention.

Additionally, feature flags support dark launches, where features are deployed but not yet visible to end-users. This allows developers to test and validate new features in production environments without impacting the user experience. It also enables seamless activation of features once they are fully ready, avoiding any disruption to users.

Overall, feature flags are essential to the modern software delivery lifecycle as they enable continuous delivery, mitigate risks, support experimentation, personalize user experiences, provide operational control, and facilitate seamless feature activation. By leveraging feature flags effectively, development teams can deliver high-quality software that meets user needs while maintaining agility and flexibility in the development process.

Using feature flags for A/B testing

Using feature flags for A/B testing is a powerful technique that allows developers to compare different variations of a feature with different user groups. This approach helps gather valuable insights into user preferences, behavior, and engagement metrics, enabling data-driven decision-making and optimization of the user experience.

Feature flags provide the necessary infrastructure to control the visibility and availability of different feature variations. By toggling these flags, developers can selectively enable or disable specific features for different user segments, creating distinct groups for A/B testing.

The process begins by defining the variations to be tested. These variations can include changes in design, functionality, user interface elements, or any other aspect of the feature. Each variation is associated with a feature flag that determines its visibility to users.

Once the variations and corresponding feature flags are set up, developers can assign users to different groups using targeting criteria such as demographics, user roles, or random assignment. Users in each group will experience a specific variation of the feature based on the assigned feature flag.

During the A/B testing phase, developers collect and analyze relevant metrics to evaluate the performance of each variation. Metrics may include user engagement, conversion rates, click-through rates, or any other key performance indicators (KPIs) that align with the goals of the test.

By comparing the metrics across the different variations, developers can identify which version performs better and delivers the desired outcomes. This data-driven approach helps inform decisions about which variation should be implemented permanently or further optimized.

As you can see, feature flags enable controlled experimentation without impacting the entire user base. Developers can test new ideas, iterate quickly, and make informed decisions based on real user data. This iterative process helps optimize the user experience, increase user satisfaction, and drive product improvement.

Feature flags vs configuration files

Feature flags and configuration files are two commonly used techniques in software development to manage the behavior and settings of an application. While they serve similar purposes, there are distinct differences between them.

Feature flags are a powerful mechanism that allows developers to enable or disable specific features or functionality within an application. By using feature flags, developers can control the release of new features, experiment with different variations, and gradually roll out changes to users. This approach provides flexibility and reduces the risk associated with deploying new code.

On the other hand, configuration files are static files that contain settings and parameters for an application. These files typically include values such as database connection strings, API keys, and other environment-specific configurations. Configuration files are usually read during the application startup process and provide a way to customize the behavior of the application without modifying the code. They are often used to define global settings that apply to the entire application or specific modules.

One key difference between feature flags and configuration files is their level of granularity. Feature flags allow for fine-grained control over individual features, enabling developers to selectively enable or disable specific functionality. This level of control is particularly useful when dealing with complex applications with multiple features that may need to be toggled independently. On the other hand, configuration files typically provide broader settings that apply to the entire application or specific modules.

Another difference lies in the management and deployment process. Feature flags are typically managed through a centralized system or service that allows for easy toggling and monitoring of feature states. This centralized control enables teams to make changes without requiring code deployments. Configuration files, on the other hand, are often managed as part of the application's codebase and require code changes and deployments to update.

Both feature flags and configuration files have their strengths and use cases. Feature flags excel in scenarios where dynamic control and experimentation are required, allowing for gradual feature rollouts and A/B testing. Configuration files, on the other hand, are well-suited for static settings that apply to the entire application or specific modules.

Feature flags and continuous delivery

Feature flags and continuous delivery are two powerful practices in software development that work hand in hand to enable faster and more efficient release cycles. While they serve different purposes, their combination can greatly enhance the development and deployment process.

To level set, continuous delivery is a software development practice that aims to automate the entire release process, from code commit to production deployment. It focuses on building a robust and reliable pipeline that enables frequent and reliable software releases. Continuous delivery ensures that every change made to the codebase is automatically built, tested, and deployed to a staging environment. This allows for rapid feedback and early detection of issues, reducing the time and effort required for bug fixing and troubleshooting. With continuous delivery, teams can deliver new features and updates to users quickly and consistently.

When combined, feature flags and continuous delivery create a powerful synergy. Feature flags enable developers to safely introduce new features into the codebase without disrupting the existing functionality. They allow for controlled rollouts, enabling teams to monitor the impact of new features and gather user feedback before making them available to all users. Continuous delivery ensures that these feature flag changes are seamlessly integrated into the release process. The automated pipeline takes care of building, testing, and deploying the code with the feature flags in place, ensuring that the new features are delivered to users efficiently and reliably.

The combination of feature flags and continuous delivery also promotes a culture of experimentation and learning. Developers can easily toggle feature flags on and off, allowing for quick iterations and adjustments based on user feedback and data analysis. This iterative approach enables teams to continuously improve their software and deliver value to users more effectively.

How Harness helps with feature flags

The reality is that most organizations build their own feature flag solutions. After all, on the surface, it’s pretty basic functionality to build. And that’s what gets them – their pace of innovation outpaces their basic feature flag solution. That’s where Harness Feature Flags comes in.

Harness Feature Flags is a new approach to feature flagging that empowers developers to release features with high velocity and low risk by utilizing automated feature flag pipelines, machine learning-based verification, and a developer-first GitOps experience.

We designed Harness Feature Flags with developers in mind. We want to meet developers where they are by storing and managing flag configurations in Git as simple YAML files for easy versioning and audit across any preferred environments.

Because developers really are the arbiters of feature flags at an organization, it makes sense to make it easy for them to get started and tie right into their existing workflows.

Rather than have another tool to use, everything should be doable with code. Of course, for those who like adding a UI to the mix, Harness has just the thing.

Developers can build flexible pipelines piecing together flag changes with notifications, timing, approval, and more. They can standardize release processes using reusable feature flag pipeline templates. Feature flag pipelines can be created using the visual pipeline builder and step library, and also by using config-as-code. By using feature flag pipelines, developers can automate feature rollouts and reduce the time to go from commit to production. If you use other Harness modules like CI or CD, you can also extend those same pipelines into feature flags to further simplify software deployment.

Harness Feature Flags also makes use of the same machine learning built into the Harness platform to automate progressive delivery. Automating progressive delivery with machine learning-based feature verification is a big part of the ease of use of Feature Flags. Harness can pull in all of the monitoring metrics that you use to automate feature or service verification and kick off remediation processes in case of any abnormalities. With feature flags, usually that’s as simple as turning it off.

On the other hand, if you want to automate feature rollout across subsets of your user base, Harness can also use those same verifications to progressively deliver the feature. In this way, developers get the same level of control with feature flags as they’re used to with their deployments. In the end, simplifying the developer workflow is what it’s all about. You can learn more about Harness Feature Flags here.

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