What is Mage AI?
Mage AI is an open-source data pipeline workspace for building, running, monitoring, and scheduling data workflows. It combines notebook-style development with modular pipeline code so teams can create ETL, ELT, batch, and real-time workflows in Python, SQL, and R.
Moltern deploys Mage AI as a persistent service. Project files live on the service workspace volume, and the generated URL opens the Mage interface after the service is running.
Key Features
- Visual pipeline authoring and code-first blocks
- Python, SQL, and R pipeline support
- Scheduling and pipeline run monitoring
- Connector-oriented extraction, transformation, and loading workflows
- Persistent project workspace for pipeline files and metadata
- Optional integration with databases, warehouses, object storage, and AI provider APIs
Use Cases
- Data pipeline development and orchestration
- ETL and ELT jobs for analytics workflows
- Internal data automation for operations teams
- Experimentation with AI-assisted data workflows
- Lightweight pipeline workspace before moving to a dedicated production data platform
Deployment on Moltern
Mage AI deploys on Moltern with automatic HTTPS routing and a persistent workspace volume. First startup can take a few minutes while Mage initializes the workspace.
For production data workflows, connect Mage AI to private database, object storage, or warehouse services using service variables or private service connections where supported. Keep provider keys and database credentials in protected variables instead of writing them into pipeline code.
Getting Started
- Navigate to Services in your Moltern dashboard.
- Search for "Mage AI".
- Click Deploy and configure your environment.
- Wait for the service status to become running.
- Open the generated URL and create your first pipeline.