92 posts tagged with "feature flags"

If you’ve ever wished your feature flag values worked more like enums, this update is for you.

Over the past years, we kept hearing the same request in different forms:

• “Can we have enum-like values for feature flags?”
• “Can we avoid people mistyping values?”
• “Can we define JSON values once and just select it?”
• “Can we separate flag definitions from rollouts?”

This usually came up when teams started using multivariate feature flags or working with more complex JSON feature flags.

Free-form values are flexible. But when feature flags become operational tools, toggled by Customer Success, Sustainment teams, or junior teammates, flexibility without guardrails becomes a risk.

So we built Predefined variations.

Shipping fast is part of startup life. Breaking production doesn't have to be.

Early-stage SaaS teams face a unique challenge: they need to ship new features quickly, experiment often, and release continuously without risking production stability. Speed drives growth, but uncontrolled releases can lead to outages, technical debt, and lost user trust. That's why feature flags have become a core part of modern startup release management.

The ConfigCat Startup Program was created to help startups build with the right foundations from the beginning. It gives early-stage teams access to a production-ready feature flag service with startup-friendly pricing, so they can release safely while everything is still under construction.

At ConfigCat, we use the best feature flag provider in the world. Plot twist: it's ConfigCat. We're basically in a committed relationship with ourselves. Some call it narcissism; we call it quality control.

In this article, we'll share real-world feature flag examples from production, explain how we use our own system inside ConfigCat, and confess the biggest feature flag mistake we've ever made (so you don't have to repeat it).

In this step-by-step guide, you’ll learn how to automate your Statsig feature flags migration with AI-powered Model Context Protocol (MCP) servers. Instead of writing custom scripts or manually recreating each flag, you can use natural language commands to transfer your entire configuration reducing migration time by up to 80%.

Most teams agree that reliability is learned in production, but the real challenge is learning without affecting the customer experience. After all, even well-designed systems fail in subtle ways: a single slow dependency can cascade into bottlenecks, or an overloaded database connection can push response times beyond what users will tolerate. We can wait for incidents to expose these cracks, or simulate them on our own with the help of feature flags.

Chaos engineering with feature flags offers a more controlled alternative. Instead of waiting for failures to happen, teams can deliberately inject small, realistic faults into production, limit their blast radius, and observe how systems behave under stress without risking a full-scale incident.

In this article, we'll look at how feature flags work, how they fit naturally into chaos engineering practices, and how chaos-enabled feature flags can help test production resilience through controlled failures.

Feature flags save lives (okay, at least your weekends). They let you release features safely, test ideas with real users, and roll back when things break.

LaunchDarkly is the biggest name in the game, but it's not always the best fit. Maybe you need simple pricing, zero data collection, or an open-source option you can self-host. The good news: there are amazing Launchdarkly alternatives out there.

Here are the 8 best feature flag tools in 2025 to help you ship faster, safer, and stress-free.

Releasing new features in a mobile app can feel like walking a tightrope, especially when updates require going through lengthy App Store and Google Play review processes, and users still need to download the new build. That's where feature flags come in. They are software development tools that give developers the power to toggle features remotely, test new functionality safely, and control rollouts without shipping a new app version.

This guide shows you how to use feature flags in Flutter (Dart) with ConfigCat, focusing on best practices, manual polling, offline support, and real-world examples.

Software development can be challenging, but deploying and managing new features shouldn't be. With feature flags, you can rest assured that your updates and new features are delivered safely with minimal risk. In this guide, I'll show you how to integrate a feature flag into a NestJS application.

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.

The feature flagging and experimentation space is heating up fast. OpenAI’s acquisition of Statsig shows just how important feature flag management has become and signals that the industry is moving toward AI-assisted, data-driven systems that optimize every release automatically.

This isn’t just another headline in the AI news cycle. It’s a sign of where software delivery is heading: toward AI-assisted, data-heavy development workflows where every release is measured, analyzed, and optimized.

For some teams, that’s the dream. For others, it’s just another layer of complexity standing between them and shipping code.