iterative · jorgeorpinel · Feb 20, 2023 · Oct 13, 2022 · Oct 14, 2022 · Oct 17, 2022
diff --git a/content/docs/install/linux.md b/content/docs/install/linux.md
@@ -29,10 +29,11 @@ Note that Python 3.8+ is needed to get the latest version of DVC.
 $ pip install dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `[s3]`,
-`[gdrive]`, `[gs]`, `[azure]`, `[ssh]`, `[hdfs]`, `[webdav]`, `[oss]`. Use
-`[all]` to include them all.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `[s3]`, `[gdrive]`, `[gs]`, `[azure]`, `[ssh]`,
+`[hdfs]`, `[webdav]`, `[oss]`. Use `[all]` to include them all.
+
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 <details id="example-pip-with-support-for-amazon-s3-storage">
 
@@ -65,9 +66,9 @@ $ conda install -c conda-forge mamba # installs much faster than conda
 $ mamba install -c conda-forge dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `dvc-s3`,
-`dvc-azure`, `dvc-gdrive`, `dvc-gs`, `dvc-oss`, `dvc-ssh`.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `dvc-s3`, `dvc-azure`, `dvc-gdrive`, `dvc-gs`,
+`dvc-oss`, `dvc-ssh`.
 
 <details id="example-conda-with-support-for-amazon-s3-storage">
 

diff --git a/content/docs/install/macos.md b/content/docs/install/macos.md
@@ -59,10 +59,11 @@ Note that Python 3.8+ is needed to get the latest version of DVC.
 $ pip install dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `[s3]`,
-`[gdrive]`, `[gs]`, `[azure]`, `[ssh]`, `[hdfs]`, `[webdav]`, `[oss]`. Use
-`[all]` to include them all.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `[s3]`, `[gdrive]`, `[gs]`, `[azure]`, `[ssh]`,
+`[hdfs]`, `[webdav]`, `[oss]`. Use `[all]` to include them all.
+
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 <details id="example-pip-with-support-for-amazon-s3-storage">
 
@@ -90,9 +91,9 @@ $ conda install -c conda-forge mamba # installs much faster than conda
 $ mamba install -c conda-forge dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `dvc-s3`,
-`dvc-azure`, `dvc-gdrive`, `dvc-gs`, `dvc-oss`, `dvc-ssh`.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `dvc-s3`, `dvc-azure`, `dvc-gdrive`, `dvc-gs`,
+`dvc-oss`, `dvc-ssh`.
 
 <details id="example-conda-with-support-for-amazon-s3-storage">
 

diff --git a/content/docs/install/windows.md b/content/docs/install/windows.md
@@ -42,9 +42,11 @@ $ conda install -c conda-forge mamba # installs much faster than conda
 $ mamba install -c conda-forge dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `dvc-s3`,
-`dvc-azure`, `dvc-gdrive`, `dvc-gs`, `dvc-oss`, `dvc-ssh`.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `dvc-s3`, `dvc-azure`, `dvc-gdrive`, `dvc-gs`,
+`dvc-oss`, `dvc-ssh`.
+
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 <details id="example-conda-with-support-for-amazon-s3-storage">
 
@@ -81,9 +83,9 @@ Note that Python 3.8+ is needed to get the latest version of DVC.
 $ pip install dvc
 ```
 
-Depending on the type of the [remote storage](/doc/command-reference/remote) you
-plan to use, you might need to install optional dependencies: `[s3]`, `[azure]`,
-`[gdrive]`, `[gs]`, `[oss]`, `[ssh]`. Use `[all]` to include them all.
+Depending on the type of the [remote storage] you plan to use, you might need to
+install optional dependencies: `[s3]`, `[azure]`, `[gdrive]`, `[gs]`, `[oss]`,
+`[ssh]`. Use `[all]` to include them all.
 
 <details id="example-pip-with-support-for-amazon-s3-storage">
 

diff --git a/content/docs/start/data-management/data-and-model-access.md b/content/docs/start/data-management/data-and-model-access.md
@@ -22,10 +22,12 @@ a specific version of a model? Or reuse datasets across different projects?
 <admon type="tip">
 
 These questions tend to come up when you browse the files that DVC saves to
-remote storage (e.g.
+[remote storage] (e.g.
 `s3://dvc-public/remote/get-started/fb/89904ef053f04d64eafcc3d70db673` 😱
 instead of the original file name such as `model.pkl` or `data.xml`).
 
+[remote storage]: /doc/user-guide/data-management/remote-storage
+
 </admon>
 
 Remember those `.dvc` files `dvc add` generates? Those files (and `dvc.lock`,
@@ -86,10 +88,15 @@ bring in changes from the data source later using `dvc update`.
 
 ### 💡 Expand to see what happens under the hood.
 
-> Note that the
-> [dataset registry](https://github.com/iterative/dataset-registry) repository
-> doesn't actually contain a `get-started/data.xml` file. Like `dvc get`,
-> `dvc import` downloads from [remote storage](/doc/command-reference/remote).
+<admon type="info">
+
+The [dataset registry] repository doesn't actually contain a
+`get-started/data.xml` file. Like `dvc get`, `dvc import` downloads from [remote
+storage].
+
+[dataset registry]: https://github.com/iterative/dataset-registry
+
+</admon>
 
 `.dvc` files created by `dvc import` have special fields, such as the data
 source `repo` and `path` (under `deps`):

diff --git a/content/docs/start/data-management/data-versioning.md b/content/docs/start/data-management/data-versioning.md
@@ -95,19 +95,28 @@ outs:
 ## Storing and sharing
 
 You can upload DVC-tracked data or model files with `dvc push`, so they're
-safely stored [remotely](/doc/command-reference/remote). This also means they
-can be retrieved on other environments later with `dvc pull`. First, we need to
-set up a remote storage location:
+safely stored [remotely]. This also means they can be retrieved on other
+environments later with `dvc pull`. First, we need to set up a remote storage
+location:
+
+[remotely]: /doc/user-guide/data-management/remote-storage
 
 ```cli
 $ dvc remote add -d storage s3://mybucket/dvcstore
 $ git add .dvc/config
 $ git commit -m "Configure remote storage"
 ```
 
-> DVC supports many remote storage types, including Amazon S3, SSH, Google
-> Drive, Azure Blob Storage, and HDFS. See `dvc remote add` for more details and
-> examples.
+<admon type="info">
+
+DVC supports many [remote storage types], including Amazon S3, SSH, Google
+Drive, Azure Blob Storage, and HDFS. See `dvc remote add` for more details and
+examples.
+
+[remote storage types]:
+  /doc/user-guide/data-management/remote-storage#supported-storage-types
+
+</admon>
 
 <details>
 

diff --git a/content/docs/studio/user-guide/projects-and-experiments/configure-a-project.md b/content/docs/studio/user-guide/projects-and-experiments/configure-a-project.md
@@ -54,10 +54,11 @@ you want to visualize in Iterative Studio.
 ### Data remotes (cloud/remote storage)
 
 The metrics and parameters that you want to include in the project may also be
-present in a [data remote](/doc/command-reference/remote#description) (cloud
-storage or another location outside the Git repo). If you want to include such
-data in your projects, then you will have to grant Iterative Studio access to
-the data remote.
+present in a [data remote] (cloud storage or another location outside the Git
+repo). If you want to include such data in your projects, then you will have to
+grant Iterative Studio access to the data remote.
+
+[data remote]: /doc/user-guide/data-management/remote-storage
 
 ## Configuring project settings
 
@@ -82,9 +83,8 @@ which you are trying to connect.
 
 ### Data remotes / cloud storage credentials
 
-If you need to provide credentials for
-[DVC data remotes](/doc/command-reference/remote#description), you will need to
-do it after your project has been created. First, create your project without
+If you need to provide credentials for a [data remote], you will need to do it
+after your project has been created. First, create your project without
 specifying the data remotes. Once your project is created, open its settings.
 Open the `Data remotes / cloud storage credentials` section. The data remotes
 that are used in your DVC repo will be listed.
@@ -93,8 +93,8 @@ that are used in your DVC repo will be listed.
 
 Now, click on `Add new credentials`. In the form that opens up, select the
 provider (Amazon S3, GCP, etc.). For details on what types of remote storage
-(protocols) are supported, refer to the DVC documentation on
-[supported storage types](/doc/command-reference/remote/add#supported-storage-types).
+(protocols) are supported, refer to the DVC documentation on [supported storage
+types].
 
 Depending on the provider, you will be asked for more details such as the
 credentials name, username, password etc. Note that for each supported storage
@@ -103,17 +103,19 @@ type, the required details may be different.
 ![](https://static.iterative.ai/img/studio/s3_remote_settings_v2.png)
 
 You will also have to ensure that the credentials you enter have the required
-permissions on the cloud / remote storage. In the DVC documentation on
-[supported storage types](/doc/command-reference/remote/add#supported-storage-types),
-expand the section for the storage type you want to add. There, you will find
-the details of the permissions that you need to grant to the account
-(credentials) that you are configuring on Iterative Studio.
+permissions on the cloud / remote storage. Refer to the [DVC Remote config
+parameters] for more details about this.
 
 Note that Iterative Studio uses the credentials only to read plots/metrics files
 if they are not saved into Git. It does not access any other data in your remote
 storage. And you do not need to provide the credentials if any DVC data remote
 in not used in your Git repository.
 
+[supported storage types]:
+  /doc/user-guide/data-management/remote-storage#supported-storage-types
+[dvc remote config parameters]:
+  /doc/command-reference/remote/modify#available-parameters-per-storage-type
+
 ### Mandatory columns
 
 ##### (Tracking scope)

diff --git a/content/docs/studio/user-guide/projects-and-experiments/live-metrics-and-plots.md b/content/docs/studio/user-guide/projects-and-experiments/live-metrics-and-plots.md
@@ -47,12 +47,11 @@ job:
     example below).
 
     ```yaml
-    ...
-      steps:
-        - name: Train model
-          env:
-            STUDIO_TOKEN: ${{ secrets.STUDIO_TOKEN }}
-    ...
+    ---
+    steps:
+      - name: Train model
+        env:
+          STUDIO_TOKEN: ${{ secrets.STUDIO_TOKEN }}
     ```
 
 2.  `STUDIO_REPO_URL`: If you are running the experiment locally, you do not

diff --git a/content/docs/use-cases/ci-cd-for-machine-learning.md b/content/docs/use-cases/ci-cd-for-machine-learning.md
@@ -52,11 +52,12 @@ configuration. Here are a few feature highlights:
 **Models, Data, and Metrics as Code**: DVC removes the need to create versioning
 databases, use special file/folder structures, or write bespoke interfacing
 code. Instead, DVC stores meta-information in Git ("codifying" data and ML
-models) while pushing the actual data content to
-[cloud storage](/doc/command-reference/remote). DVC also provides metrics-driven
-navigation in Git repositories --
-[tabulating and plotting](/doc/start/data-management/metrics-parameters-plots)
-model metrics changes across commits.
+models) while pushing the actual data content to [cloud storage]. DVC also
+provides metrics-driven navigation in Git repositories -- [tabulating and
+plotting] model metrics changes across commits.
+
+[cloud storage]: /doc/user-guide/data-management/remote-storage
+[tabulating and plotting]: /doc/start/data-management/metrics-parameters-plots
 
 **Low friction**: Our sister project CML provides
 [lightweight machine resource orchestration](https://cml.dev/doc/self-hosted-runners)

diff --git a/content/docs/use-cases/data-registry/index.md b/content/docs/use-cases/data-registry/index.md
@@ -33,7 +33,7 @@ cloud storage. Advantages:
 
 [ci/cd for your data and models lifecycle]:
   /doc/use-cases/ci-cd-for-machine-learning
-[remote storage]: /doc/command-reference/remote
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 👩‍💻 Intrigued? Try our [registry tutorial] to learn how DVC looks and feels
 firsthand.

diff --git a/content/docs/use-cases/model-registry.md b/content/docs/use-cases/model-registry.md
@@ -58,7 +58,7 @@ with software engineering methods such as continuous integration (CI/CD), which
 can sync with the state of the artifacts in your registry.
 
 [modeling process]: /doc/start/data-management/data-pipelines
-[remote storage]: /doc/command-reference/remote
+[remote storage]: /doc/user-guide/data-management/remote-storage
 [sharing]: /doc/start/data-management/data-and-model-access
 [via cml]: https://cml.dev/doc/cml-with-dvc
 [gitops]: https://www.gitops.tech/
diff --git a/content/docs/use-cases/versioning-data-and-models/index.md b/content/docs/use-cases/versioning-data-and-models/index.md
@@ -55,17 +55,21 @@ Benefits of our approach include:
   editing these in source code.
 
 - **Efficient data management**: Use a familiar and cost-effective storage
-  solution for your data and models (e.g. SFTP, S3, HDFS,
-  [etc.](/doc/command-reference/remote/add#supported-storage-types)) — free from
-  Git hosting
-  [constraints](https://docs.github.com/en/free-pro-team@latest/github/managing-large-files/what-is-my-disk-quota).
-  DVC [optimizes](/doc/user-guide/data-management/large-dataset-optimization)
-  storing and transferring large files.
+  solution for your data and models (e.g. SFTP, S3, HDFS, [etc.]) — free from
+  Git hosting [constraints]. DVC [optimizes] storing and transferring large
+  files.
+
+  [etc.]: /doc/user-guide/data-management/remote-storage#supported-storage-types
+  [constraints]:
+    https://docs.github.com/en/free-pro-team@latest/github/managing-large-files/what-is-my-disk-quota
+  [optimizes]: /doc/user-guide/data-management/large-dataset-optimization
 
 - **Collaboration**: Easily distribute your project development and share its
-  data [internally](/doc/user-guide/how-to/share-a-dvc-cache) and
-  [remotely](/doc/command-reference/remote), or
-  [reuse](/doc/start/data-management/data-and-model-access) it in other places.
+  data [internally] and [remotely], or [reuse] it in other places.
+
+  [remotely]: /doc/user-guide/data-management/remote-storage
+  [internally]: /doc/user-guide/how-to/share-a-dvc-cache
+  [reuse]: /doc/start/data-management/data-and-model-access
 
 - **Data compliance**: Review data modification attempts as Git
   [pull requests](https://www.dummies.com/web-design-development/what-are-github-pull-requests/).

diff --git a/content/docs/use-cases/versioning-data-and-models/tutorial.md b/content/docs/use-cases/versioning-data-and-models/tutorial.md
@@ -86,12 +86,18 @@ $ unzip -q data.zip
 $ rm -f data.zip
 ```
 
-> `dvc get` can download any file or directory tracked in a <abbr>DVC
-> repository</abbr> (and [stored remotely](/doc/command-reference/remote)). It's
-> like `wget`, but for DVC or Git repos. In this case we use our
-> [dataset registry](https://github.com/iterative/dataset-registry) repo as the
-> data source (refer to [Data Registry](/doc/use-cases/data-registry) for more
-> info.)
+<admon type="info">
+
+`dvc get` can download any file or directory tracked in a <abbr>DVC
+repository</abbr> (and stored [remotely]). It's like `wget`, but for DVC or Git
+repos. In this case we use our [dataset registry] repo as the data source (refer
+to [Data Registry] for more info.)
+
+[remotely]: /doc/user-guide/data-management/remote-storage
+[dataset registry]: https://github.com/iterative/dataset-registry
+[data registry]: /doc/use-cases/data-registry
+
+</admon>
 
 This command downloads and extracts our raw dataset, consisting of 1000 labeled
 images for training and 800 labeled images for validation. In total, it's a 43

diff --git a/content/docs/user-guide/data-management/importing-external-data.md b/content/docs/user-guide/data-management/importing-external-data.md
@@ -29,8 +29,13 @@ types/protocols:
 - HTTP
 - Local files and directories outside the <abbr>workspace</abbr>
 
-> Note that [remote storage](/doc/command-reference/remote) is a different
-> feature.
+<admon type="info">
+
+[Remote storage] is a different feature.
+
+[remote storage]: /doc/user-guide/data-management/remote-storage
+
+</admon>
 
 ## Examples
 
@@ -151,8 +156,8 @@ be managed independently. This is useful if the connection requires
 authentication, if multiple dependencies (or stages) reuse the same location, or
 if the URL is likely to change in the future.
 
-[DVC remotes](/doc/command-reference/remote) can do just this. You may use
-`dvc remote add` to define them, and then use a special URL with format
+[DVC remotes][remote storage] can do just this. You may use `dvc remote add` to
+define them, and then use a special URL with format
 `remote://{remote_name}/{path}` (remote alias) to define the external
 dependency.
 

diff --git a/content/docs/user-guide/data-management/managing-external-data.md b/content/docs/user-guide/data-management/managing-external-data.md
@@ -8,7 +8,7 @@
 
 [to-cache]: /doc/command-reference/add#example-transfer-to-an-external-cache
 [to-remote]: /doc/command-reference/add#example-transfer-to-remote-storage
-[remote storage]: /doc/command-reference/remote
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 There are cases when data is so large, or its processing is organized in such a
 way, that its impossible to handle it in the local machine disk. For example

diff --git a/content/docs/user-guide/data-management/remote-storage.md b/content/docs/user-guide/data-management/remote-storage.md
@@ -13,7 +13,7 @@ DVC remotes are similar to [Git remotes], but for <abbr>cached</abbr> data.
 
 </admon>
 
-This is somehow like GitHub or GitLab providing hosting for source code
+This is somewhat like GitHub or GitLab providing hosting for source code
 repositories. However, DVC does not provide or recommend a specific storage
 service. Instead, it adopts a bring-your-own-platform approach, supporting a
 wide variety of [storage types](#supported-storage-types).

diff --git a/content/docs/user-guide/experiment-management/sharing-experiments.md b/content/docs/user-guide/experiment-management/sharing-experiments.md
@@ -26,8 +26,9 @@ $ git push origin my-branch
 If you only need to share code and metadata like parameters and metrics, then
 pushing to Git is often enough. However, you may also have data, models, etc.
 that are tracked and <abbr>cached</abbr> by DVC. If you need to share these
-files, you can push them to [remote storage](/doc/command-reference/remote)
-(e.g. Amazon S3 or Google Drive).
+files, you can push them to [remote storage] (e.g. Amazon S3 or Google Drive).
+
+[remote storage]: /doc/user-guide/data-management/remote-storage
 
 ```cli
 $ dvc push