Picture this: You’ve added a new feature to your software, linked it to a feature flag, and deployed it to production. Now, you’d like to enable this feature for a subset of your users to get their feedback before you take the leap and roll it out to everyone.

But who gets to see this new feature first? How do you choose the first user segment? How do you use feature flag rules to target them?

Good to know: Feature flags let you launch new features and change your software configuration without (re)deploying code.

Let’s look at some typical real-world examples of how you can do canary releases using ConfigCat.

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.

Unless you’ve been living under a rock for the past two years, chances are you’re well-acquainted with today’s hybrid work environment and the tools that come with the territory. Platforms such as Jira, Trello and Slack are well established as tools that enable high-level remote collaboration and task management. ConfigCat provides straightforward integrations with Jira, Trello, and Slack that allow for higher visibility and easier, more convenient feature flag management. In this blog, I’ll go through these feature flag devices one by one, outlining their functionality and how to integrate them.

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.

Softwares and libraries often evolve to include new features, security patches, bug fixes, and refactorings. When software evolves, it may introduce breaking changes (BCs) in its API, breaking the previous contract or compatibility with its clients.

Semantic Versioning (SemVer) is a specification for assigning version numbers to software to communicate the degree of change between software releases and updates. However, it turned out the world was missing a proper semantic version library for C++, so we implemented one.

Java is one of the most widely used programming languages. Whether you've used it, know someone who has, studied it in university, or despise it, it's no surprise that many software products are developed in Java. So, keep reading if you want to learn how to quickly enable features in Java, with no redeployment and no fuss.

Being so busy in between releasing new features and achieving significant milestones, we tend to forget how much we've got done up until that point. As such, our active customers have enjoyed our product, but they also continue to find greater value in it as their subscriptions grow.

We're proudly announcing our 16th SDK release! ConfigCat's C++ SDK is now generally available. This SDK is a native C++ implementation of ConfigCat's feature flag management service. It is designed to be lightweight, easy to use, and easy to integrate into your C++ projects.

• Check out the ConfigCat C++ SDK on GitHub.
• Read the ConfigCat C++ SDK Docs and Guides.

When you take your software products offline to add new features, users can become frustrated, especially if their livelihood depends on it. With a new feature, there is always the risk of introducing unanticipated bugs. By incorporating feature flagging into our software release workflow, we can prevent and even lessen these situations.

The ability to make good decisions is often the leading factor in the success of a business. Yet, it is becoming increasingly difficult for companies to decide on what ideas to develop and content to optimize for users with certainty that it will perform as predicted.

Feature flagging is a vital technique that enables businesses to perform controlled A/B test experiments to gauge and analyze the impact of their decisions. A/B testing can effectively improve a business's overall performance and boost conversion rates by comparing and contrasting multiple implementations based on their performance with real users.