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Deployment

How to Deploy Data Workspace to a production cloud environment

• Deploying to AWS
• Deploying the frontend
• Deploying to other platforms

Data Ingestion

The high level view of how data gets ingested into Data Workspace

Architecture

How the main component of Data Workspace work together

• Application lifecycle
• Comparison with JupyterHub

Architecture decision record

The Architecture Decision Record for Data Workspace

• 0001: Custom proxy
• 0002: Asyncio in proxy

Contributing

Contributions to Data Workspace are welcome, such as reporting issues, requesting features, making documentation changes, or submitting code changes.

Development

Run the frontend of Data Workspace locally to develop features or evaluate if it’s suitable for your use case

• AWS S3 LocalStack
• Database migrations
• Fixing vulnerabilities
• Maintenance mode
• Remote debugging
• Enhanced tables
• Running tests
• Updating dependencies
• Updating your database