AnaviNahar announces the public preview of Serverless workspaces in Azure Databricks, describing how this feature streamlines setup for analytics and AI projects by automating infrastructure management and governance.

Serverless Workspaces Are Now Available in Azure Databricks

Azure Databricks has launched public preview support for Serverless workspaces, making it easier for teams to deploy and manage large-scale data and AI projects on Azure. Serverless workspaces remove the complexity of manual infrastructure setup by providing:

Instant Workspace Creation: Fast creation with serverless compute and built-in default storage.
Automated Infrastructure: No need to configure VNets, clusters, or storage credentials.
Unity Catalog Integration: Automated catalog and governance setup for seamless user access control.
Managed Storage: Create managed catalogs, tables, and volumes without bringing external Azure Blob storage.
Serverless Compute: Workloads run without cluster provisioning, allowing data scientists and analysts to focus on their tasks.
Network Security: Define serverless egress policies and Private Link rules, eliminating the need for manual network components. Serverless Private Link documentation
Cost Management: Attribution tags and budget policies can be configured for spend analysis.

Feature Comparison

Serverless Workspaces: Best for rapid setup and projects where minimizing infrastructure management is key. Built-in governance, automated storage and compute, and easy scaling.
Classic Workspaces: Use when custom network design or direct resource management is required.

Security and Governance Highlights

Unity Catalog: Ensures existing governance and permissions are maintained across serverless workspaces.
Network Security: Serverless egress policies simplify outbound connectivity management.
Managed Access: Data access is limited and protected with multi-key projection; direct access to object storage is prevented.

Technical Constraints and Region Support

Serverless workspaces are available only in regions with serverless compute support. (See supported regions.)
Not all legacy APIs or workloads are supported; focus is on Python and SQL. Serverless limitations
Default storage billing is currently inactive; Azure will notify on future changes.

Getting Started

Learn how to deploy a serverless workspace and explore the simplified setup process here.

Summary Checklist

Create workspaces quickly for analytics/AI workloads
Governance and security inherited from Unity Catalog
Network and compute managed automatically
Bring your own data when needed
Built-in cost management with budget tags

References

If your team is looking to accelerate analytics, AI, or data science projects on Azure, Serverless workspaces provide simplified setup, secure data management, and clear budget controls.

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