LaunchDarkly is now available on the Vercel Marketplace
LaunchDarkly has been added to the Vercel Marketplace, enabling developers to integrate feature flags into projects directly through Vercel’s Flags SDK.
LaunchDarkly is now listed on the Vercel Marketplace, allowing developers to implement feature flags without additional setup. The integration simplifies the process by enabling users to install the service via the Vercel CLI using a single command. This removes the need for manual configuration, streamlining the adoption of feature management within Vercel-hosted projects. The marketplace listing provides a direct path to integrating LaunchDarkly’s capabilities into existing workflows.
To begin using LaunchDarkly, developers must install the @flags-sdk/launchdarkly adapter and declare flags within their project. The adapter requires environment variables such as LAUNCHDARKLY_CLIENT_SIDE_ID and LAUNCHDARKLY_PROJECT_SLUG, which can be pulled locally using the Vercel CLI. These variables link the project to the LaunchDarkly dashboard, where flags are configured. The setup ensures that feature flags are properly synchronized between the development environment and the LaunchDarkly platform.
Flags are declared in a file such as flags.ts using the Flags SDK, with each flag key matching an existing flag in LaunchDarkly. The ldAdapter.variation() function evaluates flags server-side, allowing developers to conditionally render features based on flag states. An identify function constructs the LDContext from cookies or headers, avoiding unnecessary network calls. This approach enables real-time feature toggling without client-side overhead.
The integration supports server-side evaluation of flags within Vercel’s Server Components or route handlers. Developers can gate new features behind a single flag, ensuring controlled rollouts. The LaunchDarkly adapter and documentation are available through the Vercel Marketplace, providing step-by-step guidance for implementation. This release enhances Vercel’s feature management ecosystem by offering a native solution for feature flagging.