DatabricksClient

Name: DatabricksClient API
Brand: Databricks Management
Availability: InStock

★ Only Publicly Available OpenAPI DocumentAnalyticsData Pipelinesoauth27 EndpointsREST

For Agents

Provision and manage Azure Databricks workspaces through 7 ARM operations on the Microsoft.Databricks resource provider, covering create, list, update, and delete with SKU and managed resource group configuration.

Connect the DatabricksClient to your agent

Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the DatabricksClient, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.

Install Jentic One Beta (Self-Hosted)

Jentic One Host machine

# On the machine that will host your Jentic One instance:
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh

Agent machine

# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL https://raw.githubusercontent.com/jentic/jentic-one/main/tools/install.sh | sh
jentic register       # connects your agent to your Jentic One instance

Jentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.

Capabilities

What an agent can do with DatabricksClient API.

Create new Databricks workspaces with a chosen SKU (standard, premium, trial) in any supported region

List Databricks workspaces in a subscription or scoped to a resource group

Retrieve a workspace's full configuration including managed resource group ID and provisioning state

Update tags and SKU on an existing Databricks workspace

GET STARTED

Start building with DatabricksClient API

Explore with Jentic

View OpenAPI Document

Jentic publishes the only available OpenAPI document for DatabricksClient, keeping it validated and agent-ready.

Jentic publishes the only available OpenAPI specification for DatabricksClient, keeping it validated and agent-ready. The Azure Resource Manager API for Databricks exposes 7 operations across 4 paths to provision, list, update, and delete Azure Databricks workspaces. A workspace is the top-level Databricks tenant on Azure that holds clusters, notebooks, jobs, and data; this management API handles its lifecycle including SKU and managed resource group configuration. Use it to stand up new Databricks environments for analytics teams, list existing workspaces by subscription or resource group, and decommission them when projects end.

Use Cases

Patterns agents use DatabricksClient API for, with concrete tasks.

★ Provision Analytics Workspaces on Demand

Create Databricks workspaces from CI or platform automation to give new data teams an isolated analytics environment. The Workspaces_CreateOrUpdate endpoint accepts the SKU, location, and managed resource group name; Azure provisions a managed resource group containing the underlying VM scale set, network, and storage. Provisioning typically completes in 10-15 minutes and the workspace URL is returned in the response.

Create a Databricks workspace named 'analytics-prod' in resource group 'rg-analytics' with premium SKU in westeurope and tag costCenter=data-platform

Workspace Inventory and Cost Reporting

List every Databricks workspace in a subscription to feed a cost dashboard. The Workspaces_ListBySubscription and Workspaces_ListByResourceGroup endpoints return SKU, location, tags, and managed resource group, which combine with the Cost Management API for spend per workspace. This is the standard pattern for a centralised data platform team running dozens of workspaces.

List all Databricks workspaces in subscription /subscriptions/{id}, sort by SKU, and report each workspace's location and tags

Workspace Decommissioning

Delete Databricks workspaces when projects close or teams disband. Workspaces_Delete removes the workspace and triggers cleanup of its managed resource group, releasing all underlying compute and storage. The operation is asynchronous; poll the returned status URL for completion. Pair with Cost Management to confirm spend stops shortly after.

Delete the Databricks workspace 'analytics-old' in resource group 'rg-analytics' and poll until the operation completes

AI Agent Data Platform Operations

An AI agent supporting a data platform team can manage Databricks workspaces through Jentic. The agent searches by intent ('create azure databricks workspace'), Jentic returns the Workspaces_CreateOrUpdate operation with its schema, and the agent executes the call with managed Azure credentials. The same flow handles updates, listing, and deletion across the platform's full footprint of workspaces.

Search Jentic for 'create an Azure Databricks workspace', load the Workspaces_CreateOrUpdate schema, and execute it with the user-supplied workspace name, SKU, and location

Key Endpoints

7 endpoints — jentic publishes the only available openapi specification for databricksclient, keeping it validated and agent-ready.

METHOD

PATH

DESCRIPTION

GET

/subscriptions/{subscriptionId}/providers/Microsoft.Databricks/workspaces

List Databricks workspaces in a subscription

GET

/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces

List Databricks workspaces in a resource group

DELETE

/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}

Delete a Databricks workspace

GET

/providers/Microsoft.Databricks/operations

List Microsoft.Databricks operations

GET

/subscriptions/{subscriptionId}/providers/Microsoft.Databricks/workspaces

List Databricks workspaces in a subscription

GET

/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces

List Databricks workspaces in a resource group

DELETE

/subscriptions/{subscriptionId}/resourceGroups/{resourceGroupName}/providers/Microsoft.Databricks/workspaces/{workspaceName}

Delete a Databricks workspace

GET

/providers/Microsoft.Databricks/operations

List Microsoft.Databricks operations

Why though Jentic?

Three things that make agents converge on Jentic-routed access.

Credential isolation

Azure service principal credentials are encrypted in the Jentic vault. Agents receive scoped ARM bearer tokens at execution time; the underlying client secret never enters the agent context.

Intent-based discovery

Agents search by intent ('create an Azure Databricks workspace' or 'list databricks workspaces') and Jentic returns the matching ARM operation directly from the 7 available.

Time to first call

Direct ARM integration: half a day for AAD app registration, MSAL token handling, and async polling. Through Jentic: under 15 minutes — search, load schema, execute.

Related APIs

Alternatives and complements available in the Jentic catalogue.

Complementary

Data Factory Management

Orchestrate Databricks notebooks as part of a wider ETL pipeline.

Use Data Factory when an agent needs to schedule and chain Databricks notebook runs with other data operations.

Alternative

HDInsight Management

Open-source Hadoop, Spark, and Kafka clusters on Azure instead of managed Databricks.

Choose HDInsight when teams need full control of an open-source big-data stack; choose Databricks for the managed Spark + Delta Lake environment.

Complementary

Storage Management

Provision Azure Storage and ADLS Gen2 accounts that Databricks reads and writes.

Use Storage Management to create the storage account that backs a Databricks workspace's data lake.

FAQs

Specific to using DatabricksClient API through Jentic.

Why is there no official OpenAPI spec for DatabricksClient?

Microsoft Azure does not publish an OpenAPI specification. Jentic generates and maintains this spec so that AI agents and developers can call DatabricksClient via structured tooling. It is validated against the live API and kept up to date. Get started at https://app.jentic.com/sign-up.

What authentication does the Azure Databricks management API use?

It uses Azure Active Directory OAuth 2.0 against https://management.azure.com/ with the user_impersonation scope. The caller needs Contributor or a custom role with Microsoft.Databricks/workspaces/* permissions on the resource group. Jentic stores service principal credentials encrypted and issues short-lived bearer tokens at execution time.

Can I create premium-SKU workspaces with this API?

Yes. The Workspaces_CreateOrUpdate body accepts a sku.name field with values 'standard', 'premium', or 'trial'. Premium enables features like role-based access control, secret management, and JDBC/ODBC endpoint access controls.

What are the rate limits for the Databricks management API?

Azure Resource Manager applies subscription-level read and write throttling (around 1,200 requests per hour). Long-running operations such as workspace creation and deletion return 202 Accepted with an Azure-AsyncOperation header you poll for completion.

How do I create a workspace through Jentic?

Run pip install jentic and search for 'create azure databricks workspace'. Jentic returns the Workspaces_CreateOrUpdate operation; load its schema and execute it with the subscriptionId, resourceGroupName, workspaceName, and a body specifying location, sku, and managedResourceGroupId.

Does this API run notebooks or manage clusters inside the workspace?

No. This is the ARM management plane only — it provisions the workspace itself. Cluster, job, and notebook operations use the Databricks REST API at https://{region}.azuredatabricks.net/ with personal access tokens or Azure AD tokens for the workspace.