Automate the flow between your data pipelines and your codebase. Stop manually tracking which DAG versions are deployed, creating tickets for pipeline failures, or copying pipeline metrics into developer tools.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Trigger Airflow DAG deployments automatically when pull requests merge to main or release branches. Redbird validates DAG syntax, updates Airflow connections, and logs deployment metadata back to the commit.
When Airflow tasks fail after retry attempts, automatically create GitHub issues with full error logs, task context, and links to the Airflow UI. Assign issues based on DAG ownership mappings in your repository.
Keep README files and wiki pages updated with current DAG schedules, dependencies, SLA configurations, and recent run statistics. Redbird parses Airflow metadata and commits formatted markdown documentation automatically.
After critical data migration or backfill jobs complete successfully in Airflow, automatically create GitHub release tags with pipeline outputs, row counts, and execution duration for audit trails.
Trigger Airflow data validation DAGs when code changes are merged that affect data models or transformations. Surface data quality metrics and schema validation results back to the GitHub commit status.
Capture detailed execution logs, XCom data, and task instance metadata from production Airflow runs and store them as versioned artifacts in GitHub. Link logs to the exact DAG commit hash that produced them.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Airflow and GitHub with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands Airflow's DAG structures, task dependencies, and XCom patterns alongside GitHub's repository hierarchy, commit graphs, and CI/CD workflows.
Redbird maps Airflow DAG IDs, task instances, and run states to GitHub branches, commits, and pull requests without custom scripting. Our AI understands Airflow's task context dictionaries, connection configurations, and variable stores, then intelligently syncs them with GitHub Actions workflows, repository secrets, and deployment environments. Redbird automatically parses Python DAG files to extract ownership tags, schedules, and dependencies for documentation and issue routing.
faster than building custom Airflow webhooks and GitHub API scripts
Redbird can pull from Airflow and GitHub simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Airflow or GitHub.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Airflow into GitHub, or from GitHub back into Airflow. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from any Airflow pipeline event or GitHub repository activity — no code required.
When an Airflow DAG run fails after exhausting retry logic or exceeds SLA thresholds.
When a specific Airflow task completes successfully, with access to XCom values and run context.
When an Airflow DAG or task misses its configured service level agreement deadline.
Start an Airflow DAG execution with custom configuration parameters and logical date.
Set or modify Airflow Variables used for pipeline configuration and feature flags.
Enable or disable Airflow DAG scheduling programmatically based on external conditions.
When a pull request merges to specified branches like main, develop, or release branches.
When new commits are pushed to monitored branches or paths containing DAG files.
When a new GitHub release is created or published with version tags and release notes.
Open a GitHub issue with labels, assignees, milestones, and formatted error context.
Commit changes to documentation files, configuration, or metadata in the repository.
Post success or failure status checks to commits with links to Airflow pipeline results.
Join data and engineering teams who use Redbird to sync Airflow pipelines with GitHub repositories. Deploy DAGs faster, track failures better, and keep your data infrastructure documented.