# Connect LaunchDarkly to GitHub > Tie feature flag changes to code deployments, pull requests, and repository events so your development and release management actually stay in sync. **Canonical page:** https://tray.ai/connectors/launchdarkly-github-integrations/ **LaunchDarkly connector:** https://tray.ai/connectors/launchdarkly-integrations/ **LaunchDarkly documentation:** https://tray.ai/documentation/connectors/service/launchdarkly **GitHub connector:** https://tray.ai/connectors/github-integrations/ **GitHub documentation:** https://tray.ai/documentation/connectors/service/github ## Overview LaunchDarkly controls what's live. GitHub manages the code that got it there. When these two systems don't talk to each other, teams lose track of which flags correspond to which code changes — and that gap creates release risk and a lot of manual overhead. Connecting LaunchDarkly with GitHub through tray.ai automates the handoff between feature flag management and source control, giving you traceable release workflows without the coordination tax. Engineering and DevOps teams use LaunchDarkly to roll out features safely and GitHub to drive every commit, pull request, and deployment pipeline. Without a tight connection between them, developers have to manually track which flags are referenced in a PR, flag owners get no signal when related code merges, and incidents caused by a flag change go unlinked to the originating commit. Connecting LaunchDarkly and GitHub with tray.ai lets teams automatically toggle flags when PRs merge, post flag status as GitHub commit statuses, open issues when flag evaluations go sideways, and keep an end-to-end audit trail across both platforms. The result is faster, safer releases with less manual coordination and far less configuration drift. ## Use cases ### Automatically Enable Feature Flags on PR Merge When a pull request targeting a release branch merges in GitHub, tray.ai can automatically enable the corresponding LaunchDarkly feature flag in a target environment. No more manually flipping flags after deployment — features go live exactly when the code does. - Eliminate human error from forgetting to enable flags post-merge - Cut time-to-feature-availability for end users - Enforce a consistent, repeatable release process across all engineering teams ### Create GitHub Issues When Feature Flags Are Going Stale Long-lived feature flags pile up technical debt fast. tray.ai can monitor LaunchDarkly for flags that have exceeded an age threshold or are permanently enabled, then open a GitHub issue assigned to the flag's owner with remediation guidance. Teams stay on top of flag hygiene without running manual audits. - Get ahead of feature flag technical debt before it becomes a problem - Route flag cleanup tasks directly into existing engineering workflows - Keep flag counts manageable so the codebase stays maintainable ### Post Feature Flag Status as GitHub Commit Statuses tray.ai can listen for flag change events in LaunchDarkly and update the corresponding GitHub commit status to reflect whether the associated feature is enabled, in rollout, or disabled. Any developer reviewing a commit gets instant context on the live flag state tied to that code. - Full traceability between flag states and specific code commits - Flag context visible directly inside the GitHub pull request review workflow - Faster incident investigation by linking flag changes to commits right away ### Roll Back LaunchDarkly Flags When a GitHub Deployment Fails When a GitHub Actions deployment workflow fails or a deployment environment reports an unhealthy status, tray.ai can immediately disable or roll back the associated LaunchDarkly feature flag to protect users. This automated safety net cuts mean time to recovery without requiring on-call engineers to step in manually. - Minimize user impact during failed deployments through instant flag rollback - Cut MTTR by automating recovery steps that would otherwise be manual - Reduce on-call burden by handling common rollback scenarios automatically ### Sync GitHub Repository Tags to LaunchDarkly Flag Metadata When a new release tag is created in GitHub, tray.ai can update the metadata on related LaunchDarkly feature flags to associate them with that release version. You end up with a living record of which flags shipped with which release — useful for audits and retrospectives alike. - Accurate release-to-flag mapping without manual data entry - Simpler compliance audits with automatically maintained flag provenance records - Faster post-release retrospectives with complete flag and release history ### Notify Teams in GitHub Discussions When Flag Targeting Rules Change When LaunchDarkly targeting rules change significantly — say, expanding a flag rollout to 100% of users or modifying segment targeting — tray.ai can automatically post a comment or discussion in the relevant GitHub repository. Engineering, QA, and product stakeholders stay in the loop without watching LaunchDarkly directly. - Cross-functional teams stay informed of flag changes in a platform they already use - Automatic paper trail of targeting rule changes tied to the codebase - Less miscommunication between product, QA, and engineering during rollouts ### Archive LaunchDarkly Flags When Feature Code Is Deleted from GitHub When a branch or file containing a feature flag reference is deleted from GitHub, tray.ai can trigger an archival or deprecation workflow in LaunchDarkly for the corresponding flag. Both systems stay in sync, and orphaned flags stop cluttering your flag management dashboard. - Prevent orphaned feature flags from persisting after code removal - Keep the LaunchDarkly dashboard clean and usable for everyone - Reduce security surface area by ensuring removed features are fully disabled ## Templates ### Merge PR → Enable LaunchDarkly Feature Flag Monitors GitHub for merged pull requests matching a naming convention or label, automatically enables the corresponding LaunchDarkly feature flag in the specified environment, and posts a confirmation comment back to the PR. Connectors used: GitHub, LaunchDarkly ### LaunchDarkly Flag Rollback on GitHub Deployment Failure Listens for failed deployment status events in GitHub, automatically finds and disables the associated LaunchDarkly feature flag, then opens a GitHub issue documenting the incident and the rollback action taken. Connectors used: GitHub, LaunchDarkly ### Stale Flag Detector → GitHub Issue Creator Runs on a schedule to query LaunchDarkly for feature flags that have exceeded a configurable staleness threshold, then opens a labeled GitHub issue in the relevant repository and assigns it to the flag's maintainer for cleanup. Connectors used: LaunchDarkly, GitHub ### GitHub Release Tag → Update LaunchDarkly Flag Metadata When a new release tag is pushed to GitHub, this template automatically updates the version metadata on all LaunchDarkly flags associated with that release, keeping release-to-flag traceability accurate across both platforms. Connectors used: GitHub, LaunchDarkly ### LaunchDarkly Flag Change → GitHub Commit Status Update Listens for feature flag change events in LaunchDarkly and maps those changes back to the associated GitHub commit, updating the commit status to reflect the current flag state so developers always have flag context inside GitHub. Connectors used: LaunchDarkly, GitHub ### Scheduled LaunchDarkly Flag Audit Report to GitHub Generates a periodic audit report of all active LaunchDarkly feature flags and their targeting rules, then commits the report as a markdown file to a designated GitHub repository for version-controlled compliance documentation. Connectors used: LaunchDarkly, GitHub ## Challenges Tray.ai solves ### Mapping Feature Flag Keys to Pull Requests Reliably Feature flag keys in LaunchDarkly and PR identifiers in GitHub follow different naming conventions, and there's no native shared identifier between them. Without a solid mapping strategy, automation breaks or relies on brittle string parsing. **How Tray.ai helps:** tray.ai's data mapper and conditional logic operators let teams define custom mapping rules — extracting flag keys from PR descriptions, branch names, or custom labels — without writing bespoke code. The mapping logic lives in the workflow and can be updated without engineering effort. ### Handling Environment-Specific Flag State Across Multiple GitHub Environments GitHub deployment environments (staging, production, canary) map to different LaunchDarkly environments, and toggling the right flag in the right environment is easy to misconfigure when done manually. **How Tray.ai helps:** tray.ai workflows support branching logic and environment variable substitution, so a single workflow template can dynamically resolve the correct LaunchDarkly environment based on the GitHub deployment target. You configure the mappings once and they apply consistently on every run. ### Managing High-Volume Flag Change Events Without Noise Active LaunchDarkly projects can generate dozens of flag change events per day. Reacting to every one of them would flood GitHub with issues, comments, and status updates — which quickly trains engineers to ignore them. **How Tray.ai helps:** tray.ai supports event filtering, deduplication logic, and configurable throttling within workflows. Teams decide which flag types, environments, or change magnitudes warrant a GitHub action, so only meaningful events trigger downstream activity. ### Maintaining Audit Trails Across Two Separate Audit Logs LaunchDarkly has its own audit log and GitHub has repository event logs, but there's no unified view linking flag changes to their originating commits and pull requests. That gap makes compliance and incident investigation harder than it needs to be. **How Tray.ai helps:** tray.ai workflows automatically write cross-system event metadata to both platforms as they run — posting LaunchDarkly change details as GitHub commit statuses or PR comments — so you get a distributed but traceable audit record. You can also route this data to a warehouse for unified reporting. ### Keeping Integrations Resilient When API Rate Limits Are Hit Both the GitHub API and the LaunchDarkly API enforce rate limits, and high-frequency workflows triggered by webhooks can exhaust those limits during peak CI/CD activity, causing missed events or incomplete automation. **How Tray.ai helps:** tray.ai's workflow engine has built-in retry logic, exponential backoff, and error handling branches that deal gracefully with rate limit responses from both GitHub and LaunchDarkly. Failed steps retry automatically, and you can configure alert notifications for persistent failures that need a human to look at them. ## Learn more - Intelligent Integration: https://tray.ai/platform/intelligent-ipaas/ - Merlin Agent Builder: https://tray.ai/platform/merlin-agent-builder/ - Agent Gateway for MCP: https://tray.ai/platform/agent-gateway/ - Book a demo: https://tray.ai/contact/