Skip to:

Feature flags

Feature flags for real-time control in production.

Define behavior, target precisely, and control what ships in real time, on the leading platform—that just works.

bottom color image

#1 in Feature Management for 3 years running.

Trusted by developers. Proven in production.

See why customers love us

Why LaunchDarkly.

Scale is hard. AI makes it harder. We’re built for both.

Basic flags work early. At scale, they lack the features, reliability, and guardrails that teams need to move faster and stay safer. At AI speed, it’s chaos. That’s when you need LaunchDarkly.

Learn more

Scale

50T+

Flag evaluations per day

< 200ms

Global change propagation

99.99%

Enterprise uptime SLA

Safety

Granular RBAC and Audit logs

Controlled change exposure

Automated issue remediation

Sanity

Flag every change with AI

Automate flag cleanup and remove flag debt

Plug-and-play SDKs and integrations

How it works.

  • Wrap your features in a flag. Configure logic, preview targeting, and help safely prepare changes for release.

Wrap your features in a flag. Configure logic, preview targeting, and help safely prepare changes for release.

We fit right in.

Whatever your stack,
we’ve got you covered.

  • 25+ SDKs across frontend, backend, and mobile.
  • Works with tools like Claude Code, Cursor, terminal, and your IDE.
  • Integrates with your CI/CD and observability tools.

From agent to first flag in under 2 minutes.

Drop this prompt into your favorite coding assistant and get up and running with AI in seconds.

Browse MCP setup
Onboard me to LaunchDarkly. Start by installing the onboarding skill: `npx skills add launchdarkly/agent-skills --skill onboarding -y`. source-launchdarkly
From agent to first flag in under 2 minutes.

Works across your entire workflow.

  • GitHubGitHub
  • GitlabGitlab
  • VercelVercel
  • DatadogDatadog
  • ElasticElastic
  • CloudflareCloudflare
  • SegmentSegment
  • SentrySentry
  • VS CodeVS Code
  • CursorCursor
  • ClaudeClaude
Target

Take control in production.

Own what ships, when, and to whom in real time—including dynamic and AI-driven behavior.

Target rollouts by user, team, or cohort.

Accordion Item Arrow

Serve the right features to the right users at the right time, based on any attribute you define.

Make changes without redeploying.

Accordion Item Arrow

Flip features on or off instantly with sub-200ms propagation across all environments.

Control behavior in any stack or environment.

Accordion Item Arrow

Integrate flags directly into backend, frontend, mobile, or edge services using 25+ native SDKs.

Control rollout and limit risk.

Accordion Item Arrow

Use progressive rollouts to validate changes, simulate impact before launch, and instantly shut down features with kill switches if something breaks.

Test and validate in production.

Accordion Item Arrow

Simulate flag states, preview targeting rules, and confidently test changes before scaling to all users.

Integrate into your workflow.

Accordion Item Arrow

Work where you code with MCP, Git, CLI, API, or UI—and connect to CI/CD pipelines and 80+ integrations to automate and standardize releases.

De-risk

Ship confidently. Recover instantly.

De-risk every release and recover instantly when needed—even as systems and behavior change in real time.

Scale

Ship faster, no matter how big you grow.

Make teams feel safer and more self-sufficient so they can move faster—while maintaining control across systems.

Scale and standardize releases.

Accordion Item Arrow

Launch quickly, expand confidently, and standardize rollouts across teams with templates, pipelines, and reusable patterns.

Keep systems clean and maintainable.

Accordion Item Arrow

Track flag usage, set TTLs, and automatically clean up stale flags to help reduce tech debt over time.

Govern and operate with confidence.

Accordion Item Arrow

Use RBAC, approvals, and audit logs to control access—and deploy in any environment, including behind your firewall.

LaunchDarkly gave the business teams the confidence that experiments could be run reliably and the data could be trusted.

Alan Chang

Product Management Director

Improvement in site performance

15%