The Databricks REST API allows you to interact programmatically with your Databricks workspace. You can automate tasks, manage resources, and integrate Databricks with other systems.

Key features and use cases:

• Manage clusters: Start, stop, resize, and configure clusters.
• Work with notebooks: Create, update, run, and export notebooks.
• Manage libraries: Install, uninstall, and manage libraries.
• Schedule and run jobs: Submit, monitor, and manage jobs.
• Access workspace objects: Get information about and interact with objects like folders, files, and DBFS.
• Integrate with other tools: Use the API to build custom integrations with different tools and services in your data ecosystem.

Available Resources:

• API Reference Documentation: This is your go-to resource for detailed information about the available endpoints, request/response formats, authentication, and error handling. You can find it here: https://docs.databricks.com/en/reference/api.html.
• Azure Databricks REST API Reference: If you’re using Azure Databricks, this reference provides additional details and examples specific to the Azure environment: https://docs.databricks.com/api/azure
• Azure Databricks REST APIs (Microsoft): This resource from Microsoft provides an overview of the Azure Databricks REST APIs and how to use them: https://learn.microsoft.com/en-us/rest/api/databricks/

Additional Tips:

• Authentication: Most API requests require a personal access token or other supported authentication method.
• Libraries and SDKs: Databricks provides SDKs for Python, R, Java, and Go that can simplify working with the REST API.
• Rate limits: Be aware of the API rate limits to avoid exceeding them.