22 posts tagged with "ConfigCat"

In this guide, you’ll learn how to connect your AI client to ConfigCat so you can list, create, and target feature flags using natural language with ConfigCat’s MCP server.

Feature flags help teams release features safely and quickly, but if left unmanaged, they can become stale and accumulate technical debt. To keep your codebase clean, you can use the Zombie Flags page, the Zombie Flags Report, and the Zombie Flags API. Let’s take a closer look at each of them.

Are you considering a switch from LaunchDarkly? Whether you're looking for more flexibility, cost-efficiency, or just a smoother developer experience, ConfigCat offers a refreshingly straightforward alternative. With a built-in import tool and transparent SDKs, moving your feature flags over is quicker than you might think. In this guide, we’ll walk you through the migration process - without breaking a sweat (or your codebase).

Before the open source movement, software programs were 'closed source,' meaning only software developers employed by the company could access and modify them. Outsiders were kept out through non-disclosure agreements and licenses. This exclusivity motivated the creation of the open-source movement, aiming to preserve the freedom to modify and distribute software through publicly accessible code. Today, many commercial companies actively participate in the open-source ecosystem, maintaining software that is open to the public for access and contributions. One such company supporting this effort is ConfigCat.

At ConfigCat, we've seen firsthand how feature flags help teams ship faster with less risk and build more resilient, user-friendly applications. We want more people to experience these benefits, so we've decided to officially support OpenFeature.

Our OpenFeature providers were previously developed and maintained by open-source contributors. Moving forward, we've opted to develop and maintain some providers in-house, while continuing to collaborate with open-source contributors for others.

In the upcoming sections, we'll explore how to integrate OpenFeature into a Python application that currently uses the ConfigCat Python SDK.

As the gaming industry continues to evolve, driven by technological advancement and an ever-growing demand for more immersive, engaging experiences, players no longer settle for static and predictable game worlds—they crave dynamic environments that respond and adapt to their actions in real-time.

This shift toward adaptive gaming revolutionizes development techniques, enabling developers to craft personalized gameplay as unique as the player behind the controller. At the heart of this transformation lies a powerful tool: feature flags.

We've been working on some updates to make the ConfigCat dashboard easier and more enjoyable for managing your feature flags. Let's take a quick look at these new features.

Instead of relying on assumptions to decide which variation of a piece of software is better, you can let your users guide the decision through a controlled experiment. A/B testing involves splitting your user base into separate groups, where each group experiences a unique variation of a product or feature. By measuring the performance of each variation, you can determine which one works better.

To conduct such a test, you need a tool that helps you split your users into groups and display the appropriate variation for each group. Feature flags are an ideal tool for this. Let's walk through the process of conducting such an experiment in an Elixir app.

Let's say you've heard about the benefits of using feature flags for gradual feature rollouts, and you're ready to adopt them in your organization. The next step would be deciding whether to "build or buy."

If you choose to develop your feature flagging tool, you'll need to figure out how to make it fetch, evaluate, and manage feature flags. If you want to use a third-party tool, you might have to learn and unlearn different APIs as you search for the right one.

Challenges like these inspired the creation of OpenFeature, a CNCF (Cloud Native Computing Foundation) project that aims to standardize feature flagging.

Experimentation is key to successful product development, helping businesses innovate and stay competitive by testing and refining ideas. User actions like page views, clicks, and scrolls provide valuable data about what works and what doesn't. To improve products, businesses need tools that make it easy to understand this data. Using feature flags with analytics tools is a great approach. ConfigCat and Mixpanel, when used together, help businesses roll out new features smoothly and gain important insights for making better decisions.