With the rapid growth of software development, managing and releasing new features has become an integral part of our workflows. By using a feature flagging tool, you and your team can remotely release new features and manage what features users can see.
This level of control lets you quickly experiment with new features and roll them back if they prove to be problematic.
Have you ever wanted to add a new feature to your iOS app with the option to roll it back quickly if things go wrong? Feature flags can help! With feature flags, you can deliver new features remotely with the click of a button without having to republish your app.
Will showing the number of book copies sold on my website encourage more people to buy it? To answer this question confidently, I can rely upon A/B testing for guidance. This method of testing allows us to evaluate two versions of a website or app by releasing them to different user segments to see which one performs better.
When deploying code, one of the best ways to ensure it's high quality, meets user or business requirements, and works as it should is by feature flagging it. Feature flags are a great way to control the release of new code or features in your software, as feature flags make it possible to test new code on specific users or a group of users before releasing them to everyone.
Feature flagging allows you and your team to easily experiment with new features or make changes to existing ones without deploying a new software version. Furthermore, feature flags make it possible for you and your team to seamlessly execute trunk-based development by facilitating continuous deployments and ensuring code integration reliability.
This guide will cover how we can use feature flags to introduce new features in a Svelte application.
The world population continues to grow, and so does the number of house pets. While we all hope most of them have a good quality of life, some don't have a home. To combat this, we can make an animal care app. In this blog post, the app's objective is to increase the pet adoption rate. We will change the color of our call-to-action button and measure the click-through rate of each button version using A/B testing.
The goal of software development workflows is geared toward releasing new features and updates, which can sometimes cause issues if not handled correctly. In my opinion, using feature flags has proven to be essential in situations like these. You can use them to easily deploy new features, and if there are bugs you can quickly turn a feature off, then turned it on again when they have been fixed without having to redeploy the app.
If you’ve been reading about feature flags then I’m sure you’re convinced of the power and value they provide. Since development is mostly a team effort, you may be wondering how to manage a feature flag within a team, regardless of size, so one developer’s work doesn’t affect another’s. Well, in this article, we discuss exactly this issue and offer two solutions, depending on the size of your team.
Let's say your team has developed a new feature update and is planning to release it to the public. There can be some uncertainty and risk because it is hard to predict how users will react to the change. Will the new update have a negative impact and drive users away from the app? The best way to know for sure is to adopt an A/B testing approach by releasing it to a subset of users to measure its impact prior to making a full deployment. This gives you enough room to uncover bugs and refine the feature without disrupting the experience for everyone.
When it comes to smooth deployment and roll-out of new features in software products, feature flags play a critical role. Across software development workflows like agile, they are becoming essential. I have found that using them drastically reduced the risk of adversely affecting user experience since they enable me to quickly disable a new feature if unintentional bugs are discovered.
Knowing up front whether a new feature will improve or worsen user experience can be a challenging decision. If we don't adopt the proper mechanisms and processes to test new features we stand a high risk of introducing new bugs. By incorporating A/B testing into our feature release workflow, we can minimize these situations by testing the new feature with a small sample of users before deploying it.
