Unleash the potential of feature flags
Feature flags have a multitude of applications beyond merely enabling or disabling features. They serve as a potent instrument capable of enhancing your entire development and operational workflows.
Avoid long-lived branches
Build incrementally
Working in small batches has been repeatedly demonstrated as a best practice in software development. Deploying frequent changes that can be reviewed by teammates, product managers, designers, and other stakeholders offers significant benefits. It enables rapid iteration, allowing for quick course corrections if needed and avoiding large merge conflicts. Furthermore, in the event of a failed deployment, the impact is minimal, as only a small portion of the system is affected.
Leveraging feature flags allows code to be deployed to production without being visible to users, restricting visibility to the internal team or organization. Over time, these features can be gradually rolled out to more individuals, both inside and outside the organization.
Faster rollbacks
Reduce deployment risks
When deploying a potentially impactful change that carries a risk of failure, there are two approaches: either deploy it and roll it back if it fails, which typically takes several minutes and disrupts the service, or deploy it behind a feature flag, enable it for a small portion of the traffic an increment that percentage smoothly. By using a feature flag, if any issues arise, disabling the flag is nearly instantaneous, resulting in minimal impact that does not disrupt the service or the deployment of other changes. This approach allows for swift mitigation and ensures a smoother development and deployment process.
A/B testing
Make data driven decissions
In the process of developing digital products, it often becomes necessary to test and compare various variants of the UI/UX. A widely employed technique for this purpose is A/B testing, which enables data-driven decision-making. Feature flags provide a straightforward and efficient approach to implementing A/B testing. By utilizing a feature flag, the choice of variant can be determined dynamically, allowing for the collection of valuable data on user behavior and preferences. This approach empowers product teams to make informed choices, refine their designs, and enhance the user experience based on concrete insights obtained through A/B testing with feature flags.
Optimize with confidence
Performance optimization with production workloads
When it comes to optimizing your application, such as improving a SQL query, the behavior in production can often differ significantly from the development environment. By leveraging feature flags, you can execute the updated version of your code for a small portion of the incoming requests and analyze the outcomes. This approach enables you to test your modifications using real data.
By measuring relevant metrics and comparing the results, you can ensure that both versions of the code produce identical outcomes. This evaluation process helps determine whether the new version is genuinely faster or more efficient in all scenarios. Feature flags provide a controlled and incremental way to validate performance enhancements and make data-driven decisions about deploying the optimized code to a wider audience.
Mitigate incidents
Implement graceful degradation
Not all parts of a codebase are equally critical. When an incident occurs, it is often possible to gracefully degrade the service by selectively disabling or modifying specific features. This approach ensures smooth operation and minimal impact on users. For example you may decide to disable background jobs that are heavy on the database, or disable a feature that is not critical to the core functionality of the application.
Beta testing
Give early access to specific users
Finally, the most common use case of feature flags: selectively introduce new features exclusively to a small group of beta testers, allowing for controlled testing and feedback before a wider release. This approach enables you to gather valuable feedback from early adopters and refine the feature before releasing it to the general public.
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