Introduction: Simplicity in Serverless
We’re excited to announce that Serverless Workspaces is now in public preview across all clouds. With Serverless Workspaces, it’s easier than ever to create new workspaces for your data and AI projects.
Setting up a new workspace has always been a balancing act. You need to consider cloud networking, where data should live, how to set up computing resources, and how to maintain consistent security across the entire environment. All of this must happen before any single analyst or data scientist can begin their work. This results in delays that slow down projects and leave administrators with more work.
Serverless Workstation That changed. Instead of days of planning and configuration, you can create a workspace in seconds. Teams get immediate access to serverless compute, pre-configured storage, and the same governance and controls they already use. This means less overhead and faster startup for new data and AI projects.
What are serverless workspaces?
Serverless Workspace shifts the heavy responsibility of infrastructure provisioning, monitoring and maintenance to Databricks. When you create a new workspace, Serverless Compute is immediately ready to run. Unity catalog and storage are automatically set up, supported default storageSo you maintain the same governance model while avoiding manual setup.
How is a serverless workspace different from a classic workspace?
As with classic workspaces, you first need to make cloud-level decisions: how to compute the network, where the data should land, and how to handle inbound and outbound connectivity. None of this work directly creates value for end users, but it is necessary before anyone can log in and create.
With Serverless Workspace, the basics are already in place. Databricks runs secure, managed infrastructure for compute and storage. Without the need to build and maintain built-in plumbing, you can still use Unity Catalog, SSO, or identity federation and your workspace settings.
Serverless Workspace Core Capabilities
Serverless workspaces include several built-in features that make them ready-to-use from day one:
- Default storage for secure, zero-configuration data access: Each workspace provides fully managed object storage. You can create Unity Catalog-managed catalogs, tables, and volumes without bringing your own cloud storage, supplying storage credentials, or configuring external locations in advance. Enterprise features like multi-key security and no direct access to object storage ensure you have the keys to your data.
- Serverless calculations available immediately: The workload cluster runs without provisioning. Databricks automatically allocates and manages the optimal amount of compute, allowing users to focus on writing code and analyzing data without worrying about cluster operations.
- Access to your existing Unity Catalog data estate: All your existing controlled data is available in the new workspace, where existing permissions allow access.
- Bring your own data if needed: You can connect to existing cloud storage via Unity Catalog credentials and to external locations, just like you do in a classic workspace. This way, you keep lineage and permissions consistent while avoiding duplicate IAM setup (AWS, gcp, Blue,
- Simplified Network Security: Instead of creating NAT gateways, firewalls, or private link endpoints yourself, you can define serverless egress policies and serverless private link rules (AWS, Blue) which applies to all serverless workloads in the scope.
- Cost Visibility and Guardrails: Budget policies let you set attribution tags on workloads and analyze spend in system billing tables (AWS, gcp, BlueThis means clear showbacks or chargebacks without relying on users constantly tagging jobs.
- Agile Workplace Rollout: Since the infrastructure is managed for you, new workspaces can be created and assigned to teams quickly, without waiting for custom networking or runtime upgrades.
Choosing between serverless and classic workspaces
Both options remain available. The right choice depends on your needs:
- choose serverless When you want the fastest path to a governed environment with minimal configuration and management.
- choose classic When you need a custom VPC design, strict network patterns, or features that are not yet supported by serverless compute. Some organizations also prefer to manage the underlying cloud resources directly.
Serverless Workspace Ideas
Some things to keep in mind when planning an adoption:
- Area Availability: Serverless workspaces are available only in regions that support serverless computing (AWS, gcp, Blue,
- Feature Surface: Serverless workspaces inherit serverless compute constraints (e.g., Python/SQL focus, unsupported legacy APIs). Validate critical workloads before bulk migrating the workplace (AWS, gcp, Blue,
- Billing is not yet enabled for default storage on Azure and GCP: In the meantime, Databricks will not charge for default storage usage. Databricks will notify customers 30 days before enabling billing for default storage usage on Azure and GCP.
For more information, see Limitations of Serverless Workstations (AWS, gcp, Blue) and default storage (AWS, gcp, Blue,
Conclusion: Cut the Setup, Keep Control
For organizations that need to quickly deploy environments or empower new teams without delay, eliminating upfront infrastructure creation is a real win. You maintain the reigns and control that matter, but without waiting.
Serverless Workspaces move Databricks from a “configure first, use later” model to a “use now, configure what you need” model. Default storage gives you immediate access to controlled data. Egress policies let you centralize outbound control. And Unity Catalog ensures that governance remains consistent across both classic and serverless environments.
Are you ready to experience the simplicity and speed of serverless workspaces? try to make New Serverless Workspace In your own account today! And if you don’t have an account, try express setup Make one in seconds!
