Vercel Feature Flags: Edge Config and LaunchDarkly (2026)

Edge Config and LaunchDarkly are two distinct approaches to feature flagging, and understanding their core differences is key to choosing the right tool for your needs.

Here’s Vercel’s Edge Config in action, showing how it’s used to toggle a feature based on user attributes.

// vercel.json
{
  "features": {
    "experimentalApi": true
  }
}

// api/my-feature.js
import { getConfig } from '@vercel/edge-config';

export default async function handler(req, res) {
  const config = await getConfig();
  const isFeatureEnabled = config.myFeatureEnabled;

  if (isFeatureEnabled) {
    res.status(200).json({ message: 'Feature is enabled!' });
  } else {
    res.status(200).json({ message: 'Feature is disabled.' });
  }
}

This simple example illustrates how getConfig() fetches your feature flag state directly from Vercel’s global Edge Network. Changes made in the Vercel dashboard are propagated globally in seconds, meaning your feature flags are available at the edge, close to your users, for low latency. This is Vercel’s primary mechanism for feature flagging within its own platform.

LaunchDarkly, on the other hand, is a dedicated, third-party feature flagging platform. It offers a much broader set of features beyond simple on/off toggles, including sophisticated targeting rules, percentage rollouts, A/B testing capabilities, and detailed analytics.

Imagine you’re using LaunchDarkly with your Next.js application.

// pages/_app.js
import { LaunchDarklyProvider } from '@launchdarkly/react-sdk';

function MyApp({ Component, pageProps }) {
  const ldConfig = {
    // Replace with your actual SDK key
    clientSideID: 'YOUR_LAUNCHDARKLY_SDK_KEY',
    // You can also configure user attributes here for targeting
    user: {
      key: 'user123',
      email: 'user@example.com',
      // other custom attributes
    },
  };

  return (
    <LaunchDarklyProvider config={ldConfig}>
      <Component {...pageProps} />
    </LaunchDarklyProvider>
  );
}

export default MyApp;

// components/MyFeature.js
import { useFlags } from '@launchdarkly/react-sdk';

function MyFeature() {
  const { myNewFeature } = useFlags();

  if (myNewFeature) {
    return <div>This is the new, exciting feature!</div>;
  } else {
    return <div>This is the old behavior.</div>;
  }
}

export default MyFeature;

Here, useFlags() from the LaunchDarkly React SDK hooks into your application, providing the myNewFeature flag state. LaunchDarkly’s power comes from its ability to manage complex rollout strategies. You can target specific user segments (e.g., internal employees, beta testers), roll out a feature to 10% of your users, then 50%, and finally 100%, all without redeploying your code. This granular control is crucial for safe, iterative releases and for conducting experiments.

The core problem both solve is decoupling feature releases from code deployments. Traditionally, to release a new feature, you’d merge code, deploy, and the feature would be live. This is risky. Feature flags allow you to deploy code with new features disabled by default. Then, you can turn them on remotely, in production, through a dashboard. This gives you immediate control to turn features off if something goes wrong, or to gradually expose them to users.

Vercel’s Edge Config is optimized for Vercel’s platform, providing low-latency, globally distributed configuration. It’s excellent for simpler use cases, like toggling features based on environment variables or basic A/B tests where the configuration is managed within Vercel. Its strength is its tight integration and speed.

LaunchDarkly is a more comprehensive, platform-agnostic solution. It offers a richer feature set for managing complex rollout strategies, advanced targeting, experimentation, and provides detailed audit logs and analytics. It’s ideal for larger teams, complex applications, and when you need fine-grained control over who sees what, and when.

A key differentiator in how LaunchDarkly handles flag evaluation is its SDKs’ ability to perform complex targeting logic client-side or server-side based on user attributes. It doesn’t just fetch a boolean value; it evaluates rules against the provided user context. For example, you can have a flag that’s on for users in "California" but off for users in "New York," and then on for 20% of all users in "Texas." The SDK evaluates these conditions in real-time against the user object passed to it.

The next logical step is to explore how to integrate these flags with your CI/CD pipelines for automated testing and deployment workflows.