If there's one thing we don't tolerate here at ConfigCat, that's terrible customer support. Our customers are important to us, and we try our best to provide all the help we can so that they get the best out of our services. In this article, we'll look at how we ensure that our customers have a hassle-free experience when using our service.
Can naming feature flags be hard?
Yes. Just like variables in programming, naming feature flags can get tricky if you don't follow a naming standard. When feature flags don't have good names, it can be difficult for people using them to remember what they do.
In this guide, we'll walk through feature flag naming conventions and best practices that help teams manage flags at scale.
Creating software products is a highly collaborative process nowadays. Developers, designers, product managers, marketers, and many others all work together to bring software to life and ensure a smooth experience for customers.
Though developers are responsible for building new features, the control of releasing these features might be better in the hands of people that are outside of engineering teams. We can give these people control with the help of feature flags.
A/B testing answers the question: "Which of these versions will bring me better results, A or B?". It allows you to test two variations of a page to see which has a more positive impact. This could mean increased sign-ups for a landing page, more purchases on an e-commerce store, or even smoother user processes in an app. It all depends on what you want to improve. How does A/B testing work though?
Scenario: You’ve thought up a small change for your app. You write and test the code, and everything looks good. As you’re about to push it into production, you stop and ask yourself, “Will the users like this?”
You start having doubts, that maybe the idea isn’t as good as you previously thought. Still, you continue to have a strong feeling that it’ll make your app better.
One solution to this dilemma is to gradually introduce the change to a portion of users and track its impact on them. This is called A/B testing, and it’s a simple, low-risk way of letting your users pick which variant yields better results.