Lakebase Autoscaling API guide

info

Lakebase Autoscaling is available in the following regions: us-east-1, us-east-2, eu-central-1, eu-west-1, eu-west-2, ap-south-1, ap-southeast-1, ap-southeast-2.

Lakebase Autoscaling is the latest version of Lakebase with autoscaling compute, scale-to-zero, branching, and instant restore. For feature comparison with Lakebase Provisioned, see choosing between versions.

This page provides an overview of the Lakebase Autoscaling API, including authentication, available endpoints, and common patterns for working with the REST API, Databricks CLI, Databricks SDKs (Python, Java, Go), and Terraform.

For the complete API reference, see the Postgres API documentation.

important

The Lakebase Postgres API is in Beta. API endpoints, parameters, and behaviors are subject to change.

Authentication

The Lakebase Autoscaling API uses workspace-level OAuth authentication for managing project infrastructure (creating projects, configuring settings, etc.).

note

Two types of connectivity: This API is for platform management (creating projects, branches, computes). For database access (connecting to query data):

• SQL clients (psql, pgAdmin, DBeaver): Use LakeBase OAuth tokens or Postgres passwords. See Authentication.
• Data API (RESTful HTTP): Use LakeBase OAuth tokens. See Data API.
• Programming language drivers (psycopg, SQLAlchemy, JDBC): Use LakeBase OAuth tokens or Postgres passwords. See Quickstart.

For a complete explanation of these two authentication layers, see Authentication architecture.

Set up authentication

Authenticate using the Databricks CLI:

Bash

databricks auth login --host https://your-workspace.cloud.databricks.com

Follow the browser prompts to log in. The CLI caches your OAuth token at ~/.databricks/token-cache.json.

Then choose your access method:

Python SDK

The SDK uses unified authentication and automatically handles OAuth tokens:

Python

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

Java SDK

The SDK uses unified authentication and automatically handles OAuth tokens:

Java

import com.databricks.sdk.WorkspaceClient;

WorkspaceClient w = new WorkspaceClient();

CLI

Commands automatically use the cached token:

Bash

databricks postgres list-projects

curl

Generate a token for direct API calls:

Bash

export DATABRICKS_TOKEN=$(databricks auth token | jq -r .access_token)

curl -X GET "https://your-workspace.cloud.databricks.com/api/2.0/postgres/projects" \
  -H "Authorization: Bearer ${DATABRICKS_TOKEN}"

OAuth tokens expire after one hour. Regenerate as needed.

For more details, see Authorize user access to Databricks with OAuth.

Available endpoints (Beta)

All endpoints use the base path /api/2.0/postgres/.

Projects

Operation	Method	Endpoint	Documentation
Create project	POST	/projects	Create a project
Update project	PATCH	/projects/{project_id}	General settings
Delete project	DELETE	/projects/{project_id}	Delete a project
Get project	GET	/projects/{project_id}	Get project details
List projects	GET	/projects	List projects

Branches

Operation	Method	Endpoint	Documentation
Create branch	POST	/projects/{project_id}/branches	Create a branch
Update branch	PATCH	/projects/{project_id}/branches/{branch_id}	Update branch settings
Delete branch	DELETE	/projects/{project_id}/branches/{branch_id}	Delete a branch
Get branch	GET	/projects/{project_id}/branches/{branch_id}	View branches
List branches	GET	/projects/{project_id}/branches	List branches

Endpoints (Computes and Read Replicas)

Operation	Method	Endpoint	Documentation
Create endpoint	POST	/projects/{project_id}/branches/{branch_id}/endpoints	Create a compute / Create a read replica
Update endpoint	PATCH	/projects/{project_id}/branches/{branch_id}/endpoints/{endpoint_id}	Edit a compute / Edit a read replica
Delete endpoint	DELETE	/projects/{project_id}/branches/{branch_id}/endpoints/{endpoint_id}	Delete a compute / Delete a read replica
Get endpoint	GET	/projects/{project_id}/branches/{branch_id}/endpoints/{endpoint_id}	View computes
List endpoints	GET	/projects/{project_id}/branches/{branch_id}/endpoints	View computes

Database Credentials

Operation	Method	Endpoint	Documentation
Generate database credential	POST	/credentials	OAuth token authentication

Operations

Operation	Method	Endpoint	Documentation
Get operation	GET	/projects/{project_id}/operations/{operation_id}	See example below

Get operation

Check the status of a long-running operation by its resource name.

Python SDK

Python

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

# Start an operation (example: create project)
operation = w.postgres.create_project(...)
print(f"Operation started: {operation.name}")

# Wait for completion
result = operation.wait()
print(f"Operation completed: {result.name}")

Java SDK

Java

import com.databricks.sdk.WorkspaceClient;
import com.databricks.sdk.service.postgres.*;

WorkspaceClient w = new WorkspaceClient();

// Start an operation (example: create project)
CreateProjectOperation operation = w.postgres().createProject(...);
System.out.println("Operation started: " + operation.getName());

// Wait for completion
Project result = operation.waitForCompletion();
System.out.println("Operation completed: " + result.getName());

CLI

The CLI automatically waits for operations to complete by default. Use --no-wait to skip polling:

Bash

# Create project without waiting
databricks postgres create-project --no-wait ...

# Later, check the operation status
databricks postgres get-operation projects/my-project/operations/abc123

curl

Bash

# Get operation status
curl -X GET "$WORKSPACE/api/2.0/postgres/projects/my-project/operations/abc123" \
  -H "Authorization: Bearer ${DATABRICKS_TOKEN}" | jq

Response format:

JSON

{
  "name": "projects/my-project/operations/abc123",
  "done": true,
  "response": {
    "@type": "type.googleapis.com/databricks.postgres.v1.Project",
    "name": "projects/my-project",
    ...
  }
}

Fields:

• done: false while in progress, true when complete
• response: Contains the result when done is true
• error: Contains error details if operation failed

Common patterns

Resource naming

Resources follow a hierarchical naming pattern where child resources are scoped to their parent.

Projects use this format:

projects/{project_id}

Child resources like operations are nested under their parent project:

projects/{project_id}/operations/{operation_id}

This means you need the parent project ID to access operations or other child resources.

Resource IDs:

When creating resources, you must provide a resource ID (like my-app) for the project_id, branch_id, or endpoint_id parameter. This ID becomes part of the resource path in API calls (such as projects/my-app/branches/development).

You can optionally provide a display_name to give your resource a more descriptive label. If you don't specify a display name, the system uses your resource ID as the display name.

Finding resources in the UI

To locate a project in the Lakebase UI, look for its display name in the projects list. If you didn't provide a custom display name when creating the project, search for your project_id (such as "my-app").

note

Resource IDs cannot be changed after creation.

Requirements:

• Must be 1-63 characters long
• Lowercase letters, digits, and hyphens only
• Cannot start or end with a hyphen
• Examples: my-app, analytics-db, customer-123

Long-running operations (LROs)

Create, update, and delete operations return a databricks.longrunning.Operation object that provides a completion status.

Example operation response:

JSON

{
  "name": "projects/my-project/operations/abc123",
  "done": false
}

Poll for completion using GetOperation:

Python SDK

Python

from databricks.sdk import WorkspaceClient

w = WorkspaceClient()

# Start an operation
operation = w.postgres.create_project(...)

# Wait for completion
result = operation.wait()
print(f"Operation completed: {result.name}")

Java SDK

Java

import com.databricks.sdk.WorkspaceClient;
import com.databricks.sdk.service.postgres.*;

WorkspaceClient w = new WorkspaceClient();

// Start an operation
CreateProjectOperation operation = w.postgres().createProject(...);

// Wait for completion
Project result = operation.waitForCompletion();
System.out.println("Operation completed: " + result.getName());

CLI

The CLI automatically waits for operations to complete by default. Use --no-wait to return immediately:

Bash

databricks postgres create-project --no-wait ...

curl

Bash

# Poll the operation
curl "$WORKSPACE/api/2.0/postgres/projects/my-project/operations/abc123" \
  -H "Authorization: Bearer ${DATABRICKS_TOKEN}" | jq '.done'

Poll every few seconds until done is true.

Update masks

Update operations require an update_mask parameter specifying which fields to modify. This prevents accidentally overwriting unrelated fields.

Format differences:

Method	Format	Example
REST API	Query parameter	?update_mask=spec.display_name
Python SDK	FieldMask object	update_mask=FieldMask(field_mask=["spec.display_name"])
CLI	Positional argument	update-project NAME spec.display_name

Additional resources

SDKs and infrastructure-as-code

• Databricks CLI documentation
• Python SDK documentation
• Java SDK documentation
• Go SDK documentation
• Terraform provider documentation
• Get started with Terraform for Lakebase