[Doc] Add deprecation notice to databricks_dbfs_file and databricks_mount (#4876)

nkvuong · alexott · web-flow · commit 6937d27446dd · 2025-07-25T11:07:10.000Z
## Changes - Add deprecation notice to `databricks_dbfs_file` and `databricks_mount` - Resolves #4865 ## Tests  - [x] relevant change in `docs/` folder - [x] has entry in `NEXT_CHANGELOG.md` file --------- Co-authored-by: Alex Ott <alexey.ott@databricks.com>
diff --git a/NEXT_CHANGELOG.md b/NEXT_CHANGELOG.md
@@ -19,6 +19,7 @@
 * Refreshed `databricks_job` documentation ([#4861](https://github.com/databricks/terraform-provider-databricks/pull/4861)).
 * Document `environment` block in `databricks_pipeline` ([#4878](https://github.com/databricks/terraform-provider-databricks/pull/4878)).
 * Updated documentation for `databricks_disable_legacy_dbfs_setting` resource ([#4870](https://github.com/databricks/terraform-provider-databricks/pull/4870)).
+* Add deprecation notice to `databricks_dbfs_file` and `databricks_mount` ([#4876](https://github.com/databricks/terraform-provider-databricks/pull/4876))
 
 ### Exporter
 
diff --git a/docs/guides/workspace-management.md b/docs/guides/workspace-management.md
@@ -201,10 +201,8 @@ resource "databricks_permissions" "pool" {
 
 Depending on your preferences and needs, you can
 
-* Manage JAR, Wheel & Egg libraries through [databricks_dbfs_file](../resources/dbfs_file.md).
-* List entries on DBFS with [databricks_dbfs_file_paths](../data-sources/dbfs_file_paths.md) data source.
-* Get contents of small files with [databricks_dbfs_file](../data-sources/dbfs_file.md) data source.
-* Mount your storage using [databricks_mount](../resources/mount.md) resource.
+* Create UC volumes using [databricks_volume](../resources/volume.md) resource.
+* Manage JAR & Wheel libraries through [databricks_workspace_file](../resources/workspace_file.md) or [databricks_file](../resources/file.md)
 
 ## Part 4: Advanced configuration
 
diff --git a/docs/resources/cluster.md b/docs/resources/cluster.md
@@ -156,27 +156,27 @@ To install libraries, one must specify each library in a separate configuration
 
 -> Please consider using [databricks_library](library.md) resource for a more flexible setup.
 
-Installing JAR artifacts on a cluster. Location can be anything, that is DBFS or mounted object store (s3, adls, ...)
+Installing JAR artifacts on a cluster. Location can be a workspace file, Unity Catalog volume or cloud object storage location (s3, ADLS, ...)
 
 ```hcl
 library {
-  jar = "dbfs:/FileStore/app-0.0.1.jar"
+  jar = "/Volumes/catalog/schema/volume/app-0.0.1.jar"
 }
 ```
 
-Installing Python EGG artifacts. Location can be anything, that is DBFS or mounted object store (s3, adls, ...)
+Installing Python EGG artifacts (Deprecated)
 
 ```hcl
 library {
   egg = "dbfs:/FileStore/foo.egg"
 }
 ```
 
-Installing Python Wheel artifacts. Location can be anything, that is DBFS or mounted object store (s3, adls, ...)
+Installing Python Wheel artifacts. Location can be a workspace file, Unity Catalog volume or cloud object storage location (s3, ADLS, ...)
 
 ```hcl
 library {
-  whl = "dbfs:/FileStore/baz.whl"
+  whl = "/Volumes/catalog/schema/volume/baz.whl"
 }
 ```
 
@@ -223,16 +223,6 @@ library {
 
 ### cluster_log_conf
 
-Example of pushing all cluster logs to DBFS:
-
-```hcl
-cluster_log_conf {
-  dbfs {
-    destination = "dbfs:/cluster-logs"
-  }
-}
-```
-
 Example of pushing all cluster logs to S3:
 
 ```hcl
@@ -268,7 +258,7 @@ There are a few more advanced attributes for S3 log delivery:
 
 To run a particular init script on all clusters within the same workspace, both automated/job and interactive/all-purpose cluster types, please consider the [databricks_global_init_script](global_init_script.md) resource.
 
-It is possible to specify up to 10 different cluster-scoped init scripts per cluster.  Init scripts support DBFS, cloud storage locations, and workspace files.
+It is possible to specify up to 10 different cluster-scoped init scripts per cluster.  Init scripts support volumes, cloud storage locations, and workspace files.
 
 Example of using a Databricks workspace file as init script:
 
@@ -290,16 +280,6 @@ init_scripts {
 }
 ```
 
-Example of taking init script from DBFS (deprecated):
-
-```hcl
-init_scripts {
-  dbfs {
-    destination = "dbfs:/init-scripts/install-elk.sh"
-  }
-}
-```
-
 Example of taking init script from S3:
 
 ```hcl
@@ -573,7 +553,6 @@ The following resources are often used in the same context:
 * [databricks_instance_profile](instance_profile.md) to manage AWS EC2 instance profiles that users can launch [databricks_cluster](cluster.md) and access data, like [databricks_mount](mount.md).
 * [databricks_job](job.md) to manage [Databricks Jobs](https://docs.databricks.com/jobs.html) to run non-interactive code in a [databricks_cluster](cluster.md).
 * [databricks_library](library.md) to install a [library](https://docs.databricks.com/libraries/index.html) on [databricks_cluster](cluster.md).
-* [databricks_mount](mount.md) to [mount your cloud storage](https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs) on `dbfs:/mnt/name`.
 * [databricks_node_type](../data-sources/node_type.md) data to get the smallest node type for [databricks_cluster](cluster.md) that fits search criteria, like amount of RAM or number of cores.
 * [databricks_pipeline](pipeline.md) to deploy [Lakeflow Declarative Pipelines](https://docs.databricks.com/aws/en/dlt).
 * [databricks_spark_version](../data-sources/spark_version.md) data to get [Databricks Runtime (DBR)](https://docs.databricks.com/runtime/dbr.html) version that could be used for `spark_version` parameter in [databricks_cluster](cluster.md) and other resources.
diff --git a/docs/resources/dbfs_file.md b/docs/resources/dbfs_file.md
@@ -3,6 +3,8 @@ subcategory: "Storage"
 ---
 # databricks_dbfs_file Resource
 
+-> Please switch to [databricks_file](file.md) or [databricks_workspace_file](workspace_file.md) to manage files. Databricks recommends against storing any production data or sensitive information in the DBFS root.
+
 This is a resource that lets you manage relatively small files on [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html). The best use cases are libraries for [databricks_cluster](cluster.md) or [databricks_job](job.md). You can also use [databricks_dbfs_file](../data-sources/dbfs_file.md) and [databricks_dbfs_file_paths](../data-sources/dbfs_file_paths.md) data sources.
 
 -> This resource can only be used with a workspace-level provider!
diff --git a/docs/resources/global_init_script.md b/docs/resources/global_init_script.md
@@ -77,6 +77,5 @@ The following resources are often used in the same context:
 * [End to end workspace management](../guides/workspace-management.md) guide.
 * [databricks_cluster](cluster.md) to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html).
 * [databricks_cluster_policy](cluster_policy.md) to create a [databricks_cluster](cluster.md) policy, which limits the ability to create clusters based on a set of rules.
-* [databricks_dbfs_file](dbfs_file.md) to manage relatively small files on [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
+* [databricks_workspace_file](workspace_file.md) to manage small files in Databricks workspace
 * [databricks_ip_access_list](ip_access_list.md) to allow access from [predefined IP ranges](https://docs.databricks.com/security/network/ip-access-list.html).
-* [databricks_mount](mount.md) to [mount your cloud storage](https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs) on `dbfs:/mnt/name`.
diff --git a/docs/resources/job.md b/docs/resources/job.md
@@ -258,7 +258,7 @@ The `power_bi_task` triggers a Power BI semantic model update.
 
 #### spark_python_task Configuration Block
 
-* `python_file` - (Required) The URI of the Python file to be executed. [databricks_dbfs_file](dbfs_file.md#path), cloud file URIs (e.g. `s3:/`, `abfss:/`, `gs:/`), workspace paths and remote repository are supported. For Python files stored in the Databricks workspace, the path must be absolute and begin with `/`. For files stored in a remote repository, the path must be relative. This field is required.
+* `python_file` - (Required) The URI of the Python file to be executed. Cloud file URIs (e.g. `s3:/`, `abfss:/`, `gs:/`), workspace paths and remote repository are supported. For Python files stored in the Databricks workspace, the path must be absolute and begin with `/`. For files stored in a remote repository, the path must be relative. This field is required.
 * `source` - (Optional) Location type of the Python file. When set to `WORKSPACE` or not specified, the file will be retrieved from the local Databricks workspace or cloud location (if the python_file has a URI format). When set to `GIT`, the Python file will be retrieved from a Git repository defined in `git_source`.
   * `WORKSPACE`: The Python file is located in a Databricks workspace or at a cloud filesystem URI.
   * `GIT`: The Python file is located in a remote Git repository.
@@ -632,12 +632,8 @@ The following resources are often used in the same context:
 * [databricks_cluster](cluster.md) to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html).
 * [databricks_cluster_policy](cluster_policy.md) to create a [databricks_cluster](cluster.md) policy, which limits the ability to create clusters based on a set of rules.
 * [databricks_current_user](../data-sources/current_user.md) data to retrieve information about [databricks_user](user.md) or [databricks_service_principal](service_principal.md), that is calling Databricks REST API.
-* [databricks_dbfs_file](../data-sources/dbfs_file.md) data to get file content from [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
-* [databricks_dbfs_file_paths](../data-sources/dbfs_file_paths.md) data to get list of file names from get file content from [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
-* [databricks_dbfs_file](dbfs_file.md) to manage relatively small files on [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
 * [databricks_global_init_script](global_init_script.md) to manage [global init scripts](https://docs.databricks.com/clusters/init-scripts.html#global-init-scripts), which are run on all [databricks_cluster](cluster.md#init_scripts) and [databricks_job](job.md#new_cluster).
 * [databricks_instance_pool](instance_pool.md) to manage [instance pools](https://docs.databricks.com/clusters/instance-pools/index.html) to reduce [cluster](cluster.md) start and auto-scaling times by maintaining a set of idle, ready-to-use instances.
-* [databricks_instance_profile](instance_profile.md) to manage AWS EC2 instance profiles that users can launch [databricks_cluster](cluster.md) and access data, like [databricks_mount](mount.md).
 * [databricks_jobs](../data-sources/jobs.md) data to get all jobs and their names from a workspace.
 * [databricks_library](library.md) to install a [library](https://docs.databricks.com/libraries/index.html) on [databricks_cluster](cluster.md).
 * [databricks_node_type](../data-sources/node_type.md) data to get the smallest node type for [databricks_cluster](cluster.md) that fits search criteria, like amount of RAM or number of cores.
diff --git a/docs/resources/library.md b/docs/resources/library.md
@@ -10,6 +10,7 @@ Installs a [library](https://docs.databricks.com/libraries/index.html) on [datab
 -> `databricks_library` resource would always start the associated cluster if it's not running, so make sure to have auto-termination configured. It's not possible to atomically change the version of the same library without cluster restart. Libraries are fully removed from the cluster only after restart.
 
 ## Plugin Framework Migration
+
 The library resource has been migrated from sdkv2 to plugin framework。 If you encounter any problem with this resource and suspect it is due to the migration, you can fallback to sdkv2 by setting the environment variable in the following way `export USE_SDK_V2_RESOURCES="databricks_library"`.
 
 ## Installing library on all clusters
@@ -32,14 +33,14 @@ resource "databricks_library" "cli" {
 ## Java/Scala JAR
 
 ```hcl
-resource "databricks_dbfs_file" "app" {
+resource "databricks_file" "app" {
   source = "${path.module}/app-0.0.1.jar"
-  path   = "/FileStore/app-0.0.1.jar"
+  path   = "/Volumes/catalog/schema/volume/app-0.0.1.jar"
 }
 
 resource "databricks_library" "app" {
   cluster_id = databricks_cluster.this.id
-  jar        = databricks_dbfs_file.app.dbfs_path
+  jar        = databricks_file.app.path
 }
 ```
 
@@ -61,14 +62,14 @@ resource "databricks_library" "deequ" {
 ## Python Wheel
 
 ```hcl
-resource "databricks_dbfs_file" "app" {
+resource "databricks_file" "app" {
   source = "${path.module}/baz.whl"
-  path   = "/FileStore/baz.whl"
+  path   = "/Volumes/catalog/schema/volume/baz.whl"
 }
 
 resource "databricks_library" "app" {
   cluster_id = databricks_cluster.this.id
-  whl        = databricks_dbfs_file.app.dbfs_path
+  whl        = databricks_file.app.path
 }
 ```
 
@@ -92,16 +93,14 @@ resource "databricks_library" "fbprophet" {
 
 Installing Python libraries listed in the `requirements.txt` file.  Only Workspace paths and Unity Catalog Volumes paths are supported.  Requires a cluster with DBR 15.0+.
 
-
 ```hcl
 resource "databricks_library" "libraries" {
   cluster_id   = databricks_cluster.this.id
   requirements = "/Workspace/path/to/requirements.txt"
 }
 ```
 
-
-## Python EGG
+## Python EGG (Deprecated)
 
 ```hcl
 resource "databricks_dbfs_file" "app" {
@@ -128,7 +127,6 @@ resource "databricks_library" "rkeops" {
 }
 ```
 
-
 ## Import
 
 !> Importing this resource is not currently supported.
@@ -141,11 +139,7 @@ The following resources are often used in the same context:
 * [databricks_clusters](../data-sources/clusters.md) data to retrieve a list of [databricks_cluster](cluster.md) ids.
 * [databricks_cluster](cluster.md) to create [Databricks Clusters](https://docs.databricks.com/clusters/index.html).
 * [databricks_cluster_policy](cluster_policy.md) to create a [databricks_cluster](cluster.md) policy, which limits the ability to create clusters based on a set of rules.
-* [databricks_dbfs_file](../data-sources/dbfs_file.md) data to get file content from [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
-* [databricks_dbfs_file_paths](../data-sources/dbfs_file_paths.md) data to get list of file names from get file content from [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
-* [databricks_dbfs_file](dbfs_file.md) to manage relatively small files on [Databricks File System (DBFS)](https://docs.databricks.com/data/databricks-file-system.html).
 * [databricks_global_init_script](global_init_script.md) to manage [global init scripts](https://docs.databricks.com/clusters/init-scripts.html#global-init-scripts), which are run on all [databricks_cluster](cluster.md#init_scripts) and [databricks_job](job.md#new_cluster).
 * [databricks_job](job.md) to manage [Databricks Jobs](https://docs.databricks.com/jobs.html) to run non-interactive code in a [databricks_cluster](cluster.md).
-* [databricks_mount](mount.md) to [mount your cloud storage](https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs) on `dbfs:/mnt/name`.
 * [databricks_pipeline](pipeline.md) to deploy [Lakeflow Declarative Pipelines](https://docs.databricks.com/aws/en/dlt).
 * [databricks_repo](repo.md) to manage [Databricks Repos](https://docs.databricks.com/repos.html).
diff --git a/docs/resources/mlflow_experiment.md b/docs/resources/mlflow_experiment.md
@@ -14,7 +14,7 @@ data "databricks_current_user" "me" {}
 
 resource "databricks_mlflow_experiment" "this" {
   name              = "${data.databricks_current_user.me.home}/Sample"
-  artifact_location = "dbfs:/tmp/my-experiment"
+  artifact_location = "s3://bucket/my-experiment"
 
   tags {
     key   = "key1"
@@ -23,7 +23,7 @@ resource "databricks_mlflow_experiment" "this" {
   tags {
     key   = "key2"
     value = "value2"
-  }  
+  }
 }
 ```
 
@@ -32,7 +32,7 @@ resource "databricks_mlflow_experiment" "this" {
 The following arguments are supported:
 
 * `name` - (Required) Name of MLflow experiment. It must be an absolute path within the Databricks workspace, e.g. `/Users/<some-username>/my-experiment`. For more information about changes to experiment naming conventions, see [mlflow docs](https://docs.databricks.com/applications/mlflow/experiments.html#experiment-migration).
-* `artifact_location` - Path to dbfs:/ or s3:// artifact location of the MLflow experiment.
+* `artifact_location` - Path to artifact location of the MLflow experiment.
 * `tags` - Tags for the MLflow experiment.
 
 ## Attribute Reference
diff --git a/docs/resources/mount.md b/docs/resources/mount.md
@@ -3,14 +3,16 @@ subcategory: "Storage"
 ---
 # databricks_mount Resource
 
-This resource will [mount your cloud storage](https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs) on `dbfs:/mnt/name`. Right now it supports mounting AWS S3, Azure (Blob Storage, ADLS Gen1 & Gen2), Google Cloud Storage.  It is important to understand that this will start up the [cluster](cluster.md) if the cluster is terminated. The read and refresh terraform command will require a cluster and may take some time to validate the mount.
+-> Please switch to [databricks_volume](volume.md). DBFS mounts are deprecated.
 
 -> This resource can only be used with a workspace-level provider!
 
 -> When `cluster_id` is not specified, it will create the smallest possible cluster in the default availability zone with name equal to or starting with `terraform-mount` for the shortest possible amount of time. To avoid mount failure due to potentially quota or capacity issues with the default cluster, we recommend specifying a cluster to use for mounting.
 
 -> CRUD operations on a databricks mount require a running cluster. Due to limitations of terraform and the databricks mounts APIs, if the cluster the mount was most recently created / updated using no longer exists AND the mount is destroyed as a part of a terraform apply, we mark it as deleted without cleaning it up from the workspace.
 
+This resource will [mount your cloud storage](https://docs.databricks.com/data/databricks-file-system.html#mount-object-storage-to-dbfs) on `dbfs:/mnt/name`. Right now it supports mounting AWS S3, Azure (Blob Storage, ADLS Gen1 & Gen2), Google Cloud Storage.  It is important to understand that this will start up the [cluster](cluster.md) if the cluster is terminated. The read and refresh terraform command will require a cluster and may take some time to validate the mount.
+
 This resource provides two ways of mounting a storage account:
 
 1. Use a storage-specific configuration block - this could be used for the most cases, as it will fill most of the necessary details. Currently we support following configuration blocks:
diff --git a/docs/resources/permissions.md b/docs/resources/permissions.md
@@ -525,7 +525,7 @@ data "databricks_current_user" "me" {}
 
 resource "databricks_mlflow_experiment" "this" {
   name              = "${data.databricks_current_user.me.home}/Sample"
-  artifact_location = "dbfs:/tmp/my-experiment"
+  artifact_location = "s3://bucket/my-experiment"
   description       = "My MLflow experiment description"
 }
 
@@ -863,7 +863,7 @@ resource "databricks_permissions" "query_usage" {
 
 ## SQL Alert (AlertV2) usage
 
-[Alert V2](https://docs.databricks.com/sql/user/security/access-control/alert-acl.html) which is the new version of SQL Alert have 4 possible permission levels: `CAN_READ`, `CAN_RUN`, `CAN_EDIT`, and `CAN_MANAGE`. 
+[Alert V2](https://docs.databricks.com/sql/user/security/access-control/alert-acl.html) which is the new version of SQL Alert have 4 possible permission levels: `CAN_READ`, `CAN_RUN`, `CAN_EDIT`, and `CAN_MANAGE`.
 
 ```hcl
 resource "databricks_group" "auto" {
@@ -889,7 +889,7 @@ resource "databricks_permissions" "app_usage" {
 }
 ```
 
-## SQL Alert (legacy) usage 
+## SQL Alert (legacy) usage
 
 [SQL alerts](https://docs.databricks.com/sql/user/security/access-control/alert-acl.html) have three possible permissions: `CAN_VIEW`, `CAN_RUN` and `CAN_MANAGE`:
 
@@ -1081,4 +1081,4 @@ resource "databricks_permissions" "model_usage" {
 Import command:
 ```bash
 terraform import databricks_permissions.model_usage /registered-models/<registered_model_id>
-```
+```
diff --git a/docs/resources/pipeline.md b/docs/resources/pipeline.md
