STACKIT Workflows enables the orchestration of complex data pipelines and ML workflows. Compatible with Apache Airflow DAGs and integrated into the STACKIT data platform ecosystem (Dremio, Intake, AI Model Serving).
Features
- Apache Airflow Compatible: Existing DAGs can be adopted without changes
- Visual DAG Editor: Create and manage workflows via the STACKIT interface
- Trigger Types: Time-based, event-based, and manual
- Built-in Connectors: Pre-configured connectors for STACKIT services
- Fully Managed: No Airflow infrastructure operations required
Typical Use Cases
Data Pipeline Orchestration: Teams coordinate multi-stage ETL processes: data ingestion via Intake, transformation in Dremio, and delivery to BI tools.
ML Automation: ML pipelines are defined as DAGs: data preparation, model training with AI Model Experiments tracking, and deployment via AI Model Serving.
Benefits
- GDPR-compliant: All workflow executions in German data centers
- No Lock-in: Apache Airflow is an industry standard
- Complete Data Platform Stack: In combination with Dremio, Intake, and AI services
- Reproducible: Versioned DAGs and execution history
Integration with innFactory
As an official STACKIT partner, innFactory supports you in designing and implementing data pipelines: from DAG architecture and error handling to integration with the entire STACKIT data ecosystem.
Typical Use Cases
Orchestration of ETL/ELT data pipelines
ML workflow automation
Scheduled batch jobs
Data platform integration (Dremio, Intake)
