Customer-managed keys for encryption
This article provides an overview of customer-managed keys for encryption.
This feature requires the Enterprise pricing tier.
To configure customer-managed keys for encryption, see Configure customer-managed keys for encryption.
Customer-managed keys for encryption overview
Some services and data support adding a customer-managed key to help protect and control access to encrypted data. You can use the key management service in your cloud to maintain a customer-managed encryption key.
Databricks has two customer-managed key use cases that involve different types of data and locations:
- Managed services: Data in the Databricks control plane (notebooks, secrets, and Databricks SQL query data).
- Workspace storage: Your workspace storage bucket (which contains DBFS root) and the EBS volumes of compute resources in the classic compute plane.
Unity Catalog also supports the ability to read from and write to S3 buckets with KMS encryption enabled. See Create a storage credential for connecting to AWS S3
To configure customer-managed keys for workspace storage, see Configure customer-managed keys for encryption.
Customer-managed keys for managed services
Managed services data in the Databricks control plane is encrypted at rest. You can add a customer-managed key for managed services to help protect and control access to the following types of encrypted data:
- Notebook source in the Databricks control plane.
- Notebook results for notebooks run interactively (not as jobs) that are stored in the control plane. By default, larger results are also stored in your workspace root bucket. You can configure Databricks to store all interactive notebook results in your cloud account.
- Secrets stored in Databricks secrets.
- AI/BI dashboards.
- Databricks SQL queries and query history.
- Personal access tokens (PAT) or other credentials used to set up Git integration with Databricks Git folders.
- Vector Search indexes and metadata.
To configure customer-managed keys for managed services, see Configure customer-managed keys for encryption.
Only AI/BI dashboards created after November 1, 2024 are encrypted and compatible with customer-managed keys.
Customer-managed keys for workspace storage
You can add a customer-managed key for workspace storage to protect and control access to the following types of encrypted data:
- Your workspace storage bucket: If you add a workspace storage encryption key, Databricks encrypts the data on the Amazon S3 bucket in your AWS account that you specified when you set up your workspace, which is known as the workspace storage bucket. This bucket contains DBFS root, which includes the FileStore area, MLflow Models, and DLT data in your DBFS root (not DBFS mounts). The bucket also includes workspace system data, which includes job results, Databricks SQL results, notebook revisions, and other workspace data. For more information, see Create an S3 bucket for workspace deployment.
- Your cluster’s EBS volumes (optional): For Databricks Runtime cluster nodes and other compute resources in the classic compute plane, you can optionally use the key to encrypt the VM’s remote EBS volumes.
This feature affects your DBFS root but is not used for encrypting data on any additional DBFS mounts. For S3 DBFS mounts, you can use other approaches to writing encrypted data with your keys. For more information, see Encrypt data in S3 buckets. Mounts are a legacy access pattern. Databricks recommends using Unity Catalog for managing all data access. See Connect to cloud object storage and services using Unity Catalog.
Compare customer-managed keys use cases
The following table lists which customer-managed key features are used for which types of data.
Type of data | Location | Which customer-managed key feature to use |
|---|---|---|
AI/BI dashboards | Control plane | Managed services |
Notebook source and metadata | Control plane | Managed services |
Personal access tokens (PAT) or other credentials used for Git integration with Databricks Git folders | Control plane | Managed services |
Secrets stored by the secret manager APIs | Control plane | Managed services |
Databricks SQL queries and query history | Control plane | Managed services |
Serverless compute plane | Managed services | |
The remote EBS volumes for Databricks Runtime cluster nodes and other compute resources. | Classic compute plane in your AWS account. The customer managed keys for remote EBS volumes applies only to compute resources in the classic compute plane in your AWS account. See Serverless compute and customer-managed keys. | Workspace storage |
DBFS root in your workspace storage bucket in your AWS account. This also includes the FileStore area. | Workspace storage | |
Job results | Workspace storage bucket in your AWS account | Workspace storage |
Databricks SQL query results | Workspace storage bucket in your AWS account | Workspace storage |
Workspace storage bucket in your AWS account | Workspace storage | |
If you use a DBFS path in your DBFS root, this is stored in the workspace storage bucket in your AWS account. This does not apply to DBFS paths that represent mount points to other data sources. | Workspace storage | |
By default, when you run a notebook interactively (rather than as a job) results are stored in the control plane for performance with some large results stored in your workspace storage bucket in your AWS account. You can choose to configure Databricks to store all interactive notebook results in your AWS account. | For partial results in the control plane, use a customer-managed key for managed services. For results in the workspace storage bucket, which you can configure for all result storage, use a customer-managed key for workspace storage. |
Serverless compute and customer-managed keys
Databricks SQL Serverless supports:
- Customer-managed keys for managed services for Databricks SQL queries and query history.
- Customer-managed keys for your workspace storage bucket including DBFS root storage for Databricks SQL results.
Serverless SQL warehouses do not use customer-managed keys for EBS storage encryption on compute nodes, which is an optional part of configuring customer-managed keys for workspace storage. Disks for serverless compute resources are short-lived and tied to the lifecycle of the serverless workload. When compute resources are stopped or scaled down, the VMs and their storage are destroyed.
Model Serving
Resources for Model Serving, a serverless compute feature, are generally in two categories:
- Resources that you create for the model are stored in your workspace’s DBFS root in your workspace’s S3 bucket. This includes the model’s artifacts and version metadata. Both the workspace model registry and MLflow use this storage. You can configure this storage to use customer-managed keys.
- Resources that Databricks creates directly on your behalf include the model image and ephemeral serverless compute storage. These are encrypted with Databricks-managed keys and do not support customer-managed keys.
Customer-managed keys for EBS storage, which is an optional part of the customer-managed workspace storage feature, does not apply to serverless compute resources. Disks for serverless compute resources are short-lived and tied to the lifecycle of the serverless workload. When compute resources are stopped or scaled down, the VMs and their storage are destroyed.