Redbird AI automates the flow between your orchestration layer and data warehouse. Stop writing custom operators, manually tracking pipeline metrics in BigQuery, or building one-off scripts to sync orchestration metadata with warehouse operations.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Capture every pipeline run's duration, status, retries, and task-level performance metrics in structured BigQuery tables. Build real-time dashboards and SLAs on orchestration health without custom logging code. Query historical trends to optimize resource allocation and identify bottleneck tasks.
Monitor BigQuery table metadata for schema modifications, column additions, or constraint changes. Automatically launch Airflow DAGs that run validation checks, update downstream dependencies, and notify stakeholders. Prevent breaking changes from cascading through your pipeline without manual oversight.
When Airflow tasks fail, automatically write complete error logs, stack traces, and task context to BigQuery. Query failure patterns across pipelines, identify recurring issues, and generate root cause reports. Eliminate scattered log files and centralize debugging data in your analytical backbone.
Monitor BigQuery table size and partition metrics continuously. Trigger Airflow workflows to archive cold partitions, optimize clustering, or migrate tables to long-term storage when thresholds are met. Automate warehouse hygiene without manual capacity planning or scheduled guesswork.
Track every update to Airflow variables, connections, and configuration across your orchestration environment. Write changes to BigQuery with timestamps, user attribution, and before/after values. Maintain compliance-ready audit logs and debug production issues by correlating config changes with pipeline behavior.
Query BigQuery tables for gaps in time-series data, missing date partitions, or unexpected null counts. Automatically launch targeted Airflow backfill DAGs with correct date ranges and dependencies. Heal data gaps proactively without waiting for downstream reports to break.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Airflow and BigQuery 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 execution context alongside BigQuery's table schemas, partition layouts, and query patterns—no custom operators required.
Redbird maps Airflow task IDs, DAG runs, and XCom values to BigQuery table structures, partition specs, and column types automatically. Our AI understands when a failed task should trigger a warehouse rollback, which pipeline metrics belong in which analytical tables, and how to route orchestration events to the right datasets. Skip the custom PythonOperators and brittle BigQueryHook scripts—Redbird handles the translation layer between orchestration and analytics.
faster than building custom Airflow-BigQuery operators and logging infrastructure
Redbird can pull from Airflow and BigQuery 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 BigQuery.
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 BigQuery, or from BigQuery 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 BigQuery warehouse operation—Redbird handles the orchestration.
Trigger workflows when any pipeline finishes, capturing final state and duration metrics.
React immediately when individual tasks fail, before the entire DAG completes.
Capture configuration changes across your orchestration environment for audit trails.
Launch targeted workflows with date ranges, table names, or execution context passed dynamically.
Modify pipeline configuration programmatically without manual Airflow UI edits.
Reset failed tasks or mark success to unblock downstream dependencies automatically.
Detect schema evolution events to trigger validation and downstream pipeline updates.
Monitor partition growth and react when tables need archiving or optimization.
Capture BigQuery job failures and resource contention events for automated triage.
Insert pipeline metrics, logs, or event data into BigQuery with correct schemas and partitions.
Execute analytical queries with dynamic filters and extract results for downstream logic.
Modify warehouse structures programmatically as pipeline requirements evolve.
Connect Airflow and BigQuery in minutes. Stop maintaining custom operators and start automating the flow between orchestration and analytics with AI that understands both systems.