Connect Airflow and
Google Cloud Storage with AI

Redbird AI automates the flow between your orchestration layer and cloud storage. Stop writing custom operators, managing GCS hooks, and manually syncing pipeline artifacts. Let AI handle data staging, file monitoring, and bucket operations across your workflows.

No code required
Live in minutes
SOC 2 Type II

What you can automate today

Redbird gives your team ready-to-run workflows — just connect your accounts and go.

Automatically archive completed pipeline outputs to GCS cold storage buckets

When Airflow DAG runs complete successfully, Redbird automatically transfers output files to designated GCS archive buckets and applies lifecycle policies. Eliminates manual cleanup tasks and ensures compliance with data retention requirements without cluttering active storage.

Trigger downstream DAGs when new data files land in GCS buckets

Redbird monitors specified GCS buckets and automatically triggers corresponding Airflow DAGs when new files arrive. No need to poll buckets or configure Cloud Functions—your pipelines start processing immediately when source data is available.

Stage intermediate data to GCS between pipeline transformation steps automatically

As your Airflow tasks complete each transformation stage, Redbird writes intermediate results to GCS with proper naming conventions and partitioning. Enables checkpoint recovery and makes pipeline debugging easier without custom file management code in every DAG.

Send alerts when pipeline failure logs are written to GCS error buckets

When Airflow tasks fail and write error artifacts to GCS, Redbird captures those events and routes notifications with file metadata to your team. Provides immediate visibility into pipeline issues with context from actual failure logs and stack traces.

Sync DAG execution metadata and performance stats to GCS for long-term analysis

Redbird captures detailed Airflow execution logs, task durations, and resource utilization metrics, then writes structured summaries to GCS. Creates a historical record for pipeline performance analysis and capacity planning without overloading your Airflow metadata database.

Enrich pipeline runs with file metadata from GCS source data

Before DAG execution begins, Redbird retrieves file sizes, row counts, and schema information from GCS objects and injects that context into Airflow XComs. Enables dynamic task configuration and smart pipeline branching based on actual input characteristics.

Live in four steps

No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.

01

Connect your accounts

Authorize Airflow and Google Cloud Storage with OAuth or API credentials. Redbird never stores your data — it just passes through.

02

Describe what you want

Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.

03

Review and activate

Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.

04

Let it run — and iterate

Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.

Built for data-driven teams

Redbird understands Airflow's DAG structure and task dependencies alongside GCS bucket hierarchies, object lifecycle stages, and storage classes—enabling intelligent automation across your entire pipeline infrastructure.

AI that understands orchestration and object storage together

Redbird's AI maps Airflow task outputs to GCS bucket paths, understands XCom patterns and file staging conventions, and recognizes when DAG states should trigger storage operations. It reads GCS object metadata, storage classes, and lifecycle policies to make intelligent decisions about data movement. The system learns your naming conventions, partition schemes, and knows which pipeline artifacts belong in nearline vs coldline storage without hardcoded rules.

DAG run states & task outputs
GCS bucket policies & storage classes
XCom values & file metadata
Pipeline checkpoints & artifacts
10×

faster than building custom GCS operators and file management logic for every DAG

No custom hooks, no boto3 scripts, no storage polling infrastructure

Auto-generated reports

Redbird can pull from Airflow and Google Cloud Storage simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.

Trigger-based alerts

Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Airflow or Google Cloud Storage.

Enterprise-grade security

SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.

Bidirectional sync

Push data from Airflow into Google Cloud Storage, or from Google Cloud Storage back into Airflow. Resolve conflicts with configurable merge rules.

Full audit trail

Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.

Triggers & actions for every team

Start automations from any Airflow DAG event or GCS bucket operation—Redbird connects your orchestration and storage layers in real time.

Airflow
Triggers & Actions
Trigger

DAG run completes successfully

Fires when an Airflow DAG finishes all tasks without failures.

Trigger

Task fails after retries exhausted

Triggers when an Airflow task reaches maximum retry attempts and fails.

Trigger

XCom value pushed by task

Activates when a specific task writes data to Airflow's XCom key-value store.

Action

Start DAG run with config parameters

Triggers a new DAG execution with custom configuration from external events.

Action

Update task state or mark success

Programmatically changes task status in Airflow metadata database.

Action

Clear task instances for rerun

Resets specific task states to allow re-execution without full DAG restart.

Google Cloud Storage
Triggers & Actions
Trigger

New object uploaded to bucket

Fires when files are written to specified GCS buckets or path prefixes.

Trigger

Object storage class changes

Triggers when GCS lifecycle policies move objects between storage tiers.

Trigger

Bucket quota threshold exceeded

Activates when storage usage crosses configured size or object count limits.

Action

Upload file or dataset to bucket

Writes data objects to GCS with specified metadata and storage class.

Action

Move objects between buckets or paths

Transfers or renames GCS objects based on pipeline stage or retention rules.

Action

Apply lifecycle policy to bucket objects

Sets retention rules and automatic archival schedules for stored data.

Airflow
+
Google Cloud Storage

Ready to connect your stack?

Stop building custom storage operators for every pipeline. Redbird connects Airflow and Google Cloud Storage so your team can focus on data transformations, not infrastructure glue code.

Get started → Book a demo