Move to studio.datachain.ai (#5338)

* Move studio.dvc.ai to studio.datachain.ai

* Move studio.iterative.ai to studio.datachain.ai

Author: 0x2b3bfa0

config/link-check/excluded-links.yml

@@ -11,4 +11,4 @@
 - 'https://studio.example.com'
 - 'https://twitter.com/DVCorg'
 - 'https://api.hsforms.com/submissions/v3/integration/submit/'
-- 'https://studio.iterative.ai/api/*'
+- 'https://studio.datachain.ai/api/*'

content/docs/command-reference/exp/push.md

@@ -41,7 +41,7 @@ to see experiments in the remote.
 This command will also try to `dvc push` all <abbr>cached</abbr> data associated
 with the experiments to [remote storage], unless `--no-cache` is used.
 
-If the [DVC Studio](https://studio.iterative.ai)
+If the [DVC Studio](https://studio.datachain.ai)
 [access token](/doc/studio/user-guide/experiments/live-metrics-and-plots#set-up-an-access-token)
 is set, DVC will notify DVC Studio about new experiments, and display a DVC
 Studio project URL to view experiments.

content/docs/command-reference/studio/index.md

@@ -1,6 +1,6 @@
 # studio
 
-A set of commands to authenticate DVC with [Studio](https://studio.iterative.ai)
+A set of commands to authenticate DVC with [Studio](https://studio.datachain.ai)
 and save a
 [client access token](/doc/studio/user-guide/account-management#client-access-tokens)
 to global [DVC configuration]: [login](/doc/command-reference/studio/login), [logout](/doc/command-reference/studio/logout),

content/docs/command-reference/studio/login.md

@@ -21,7 +21,7 @@ and assigns a random name as the token name.
 ## Options
 
 - `-H <hostname>`, `--hostname <hostname>` - the hostname of the Studio instance
-  to authenticate with. Defaults to `https://studio.iterative.ai`.
+  to authenticate with. Defaults to `https://studio.datachain.ai`.
 
 - `-s <scopes>`, `--scopes <scopes>` - comma separated values of
   [scopes](/doc/studio/user-guide/account-management#client-access-tokens) for

content/docs/dvclive/index.md

@@ -172,4 +172,4 @@ See how to [setup a pipeline] to work with DVCLive.
 [run experiments]: /doc/user-guide/experiment-management/running-experiments
 [setup a pipeline]: /doc/dvclive/how-it-works#setup-to-run-with-dvc
 [access is enabled]: /doc/start/experiments/experiment-tracking#sharing
-[dvc studio]: https://studio.iterative.ai
+[dvc studio]: https://studio.datachain.ai

content/docs/dvclive/live/log_image.md

@@ -92,7 +92,7 @@ with Live() as live:
       live.next_step()
 ```
 
-In [DVC Studio](https://studio.iterative.ai/) and the
+In [DVC Studio](https://studio.datachain.ai/) and the
 [DVC Extension for VSCode](https://marketplace.visualstudio.com/items?itemName=Iterative.dvc),
 folders following this pattern will be rendered using an image slider:
 

content/docs/dvclive/ml-frameworks/pytorch-lightning.md

@@ -188,4 +188,4 @@ dvclive/metrics/train/epoch/metric.tsv
 [`live`]: /doc/dvclive/live
 [`ModelCheckpoint`]:
   https://lightning.ai/docs/pytorch/stable/api/lightning.pytorch.callbacks.ModelCheckpoint.html
-[DVC Studio]: https://studio.iterative.ai
+[DVC Studio]: https://studio.datachain.ai

content/docs/start/experiments/experiment-tracking.md

@@ -132,7 +132,7 @@ section to share, or skip to the next section if you want to start locally.
 
 DVC tracks the code and metadata for each experiment in Git. If you have a Git
 remote (for example, GitHub) where you `git push`, go to
-[DVC Studio](https://studio.iterative.ai), configure your Git provider, and
+[DVC Studio](https://studio.datachain.ai), configure your Git provider, and
 [add your Git repository as a project](/doc/studio/user-guide/experiments/create-a-project).
 
 Next, you can login to Studio from the command line:
@@ -260,4 +260,4 @@ Learn more about
 
 [dvclive]: /doc/dvclive
 [shared]: /doc/user-guide/experiment-management/sharing-experiments
-[dvc studio]: https://studio.iterative.ai
+[dvc studio]: https://studio.datachain.ai

content/docs/start/model-registry/index.md

@@ -30,7 +30,7 @@ https://www.youtube.com/watch?v=T7MBFpnSr9Q
 These are captured in our [example-get-started-experiments] repo. You can [fork
 it][example-get-started-experiments-fork] to follow along, or you can take a
 look at our
-[public model registry](https://studio.iterative.ai/team/Iterative/models) (read
+[public model registry](https://studio.datachain.ai/team/Iterative/models) (read
 only) to get a feel for what's possible.
 
 [example-get-started-experiments]:

content/docs/start/model-registry/manage-models.md

@@ -7,17 +7,17 @@ description:
 
 # Get Started: Manage models
 
-In this guide, we will be using [DVC Studio](https://studio.iterative.ai) to
+In this guide, we will be using [DVC Studio](https://studio.datachain.ai) to
 manage our model registry. You can check out our
-[example model](https://studio.iterative.ai/team/Iterative/models/b3P4bcYIrGYdzyjqzsf9Xw==/pool-segmentation/v1.0.0)
+[example model](https://studio.datachain.ai/team/Iterative/models/b3P4bcYIrGYdzyjqzsf9Xw==/pool-segmentation/v1.0.0)
 in DVC Studio to see what it will look like once we finish all the steps in this
 guide.
 
 <admon type="info">
 
 To perform the model registry actions in this guide, follow
 [these steps](/doc/studio/user-guide/experiments/create-a-project#connect-to-a-git-repository-and-add-a-project)
-to sign in to [DVC Studio](https://studio.iterative.ai), connect it to your Git
+to sign in to [DVC Studio](https://studio.datachain.ai), connect it to your Git
 account and add your repository as a DVC Studio project.
 
 </admon>
@@ -155,7 +155,7 @@ from the registry entirely. To see how, have a look at the
 [documentation](/doc/studio/user-guide/model-registry/remove-a-model-or-its-details).
 
 The detailed view of our model in the registry should now match what we see
-[in our example](https://studio.iterative.ai/team/Iterative/models/b3P4bcYIrGYdzyjqzsf9Xw==/pool-segmentation/v1.0.0).
+[in our example](https://studio.datachain.ai/team/Iterative/models/b3P4bcYIrGYdzyjqzsf9Xw==/pool-segmentation/v1.0.0).
 
 <details id="under-the-hood-removing-stages">
 

content/docs/studio/index.md

@@ -1,6 +1,6 @@
 # DVC Studio
 
-[DVC Studio](https://studio.iterative.ai/) is a web application that enables
+[DVC Studio](https://studio.datachain.ai/) is a web application that enables
 Machine Learning teams to seamlessly
 
 - [Run and track experiments](/doc/use-cases/experiment-tracking)
@@ -11,7 +11,7 @@ It works on top of [DVC](https://dvc.org/) and [Git](https://git-scm.com/),
 maintaining Git as the single-source-of-truth for your data, experiments and
 models.
 
-Sign in to [DVC Studio](https://studio.iterative.ai/) using your GitHub.com,
+Sign in to [DVC Studio](https://studio.datachain.ai/) using your GitHub.com,
 GitLab.com, or Bitbucket.org account, or with your email address. Explore the
 demo projects and models, and
 [let us know](/doc/studio/user-guide/troubleshooting#support) if you need any

content/docs/studio/rest-api/create-project.md

@@ -27,7 +27,7 @@ Here are the possible values for each parameter in the request json:
   This field is mandatory.
 - `public` (boolean, default: `false`) - specifies whether the project should be
   public (`true`) or not (`false`). A public project, such as the
-  [example-get-started](https://studio.iterative.ai/team/Iterative/projects/example-get-started-zde16i6c4g)
+  [example-get-started](https://studio.datachain.ai/team/Iterative/projects/example-get-started-zde16i6c4g)
   demo project, can be accessed by anyone.
 - `team_name`(string) - the name of the team associated with the project if we
   want to create the project in team space. This field is optional. If team name
@@ -56,7 +56,7 @@ Here is an example JSON response from the API request:
   "projects": [
     {
       "id": "tsanhawn9y",
-      "url": "https://studio.iterative.ai/user/amritghimire/projects/example-get-started-tsanhawn9y",
+      "url": "https://studio.datachain.ai/user/amritghimire/projects/example-get-started-tsanhawn9y",
       "name": "example-get-started"
     }
   ]
@@ -70,7 +70,7 @@ the necessary information about the created project:
   "tsanhawn9y".
 - `url`: The URL of the created project. You can access the project using this
   URL. In this example, the project URL is
-  `https://studio.iterative.ai/user/amritghimire/projects/example-get-started-tsanhawn9y`.
+  `https://studio.datachain.ai/user/amritghimire/projects/example-get-started-tsanhawn9y`.
 - `name`: The name of the created project. In this example, the project name is
   "example-get-started".
 
@@ -95,7 +95,7 @@ import os
 import requests
 
 
-url = "https://studio.iterative.ai/api/create-project"
+url = "https://studio.datachain.ai/api/create-project"
 token = os.environ["DVC_STUDIO_TOKEN"]
 payload = json.dumps({
   "repo_url": "https://github.com/amritghimire/monorepo-model-registry-fixture",
@@ -120,7 +120,7 @@ for project in response.json()["projects"]:
 <tab title="CLI">
 
 ```cli
-$ curl --location 'https://studio.iterative.ai/api/create-project' \
+$ curl --location 'https://studio.datachain.ai/api/create-project' \
 --header "Authorization:token ${DVC_STUDIO_TOKEN}" \
 --header 'Content-Type: application/json' \
 --data '{
@@ -137,7 +137,7 @@ $ curl --location 'https://studio.iterative.ai/api/create-project' \
 
 <admon type="tip">
   If you are interacting with Self hosted Studio, remember to replace the URL
-  https://studio.iterative.ai with the URL of the self-hosted studio.
+  https://studio.datachain.ai with the URL of the self-hosted studio.
 </admon>
 
 [DVC Studio client access token]:

content/docs/studio/rest-api/download-model.md

@@ -58,7 +58,7 @@ import os
 import requests
 
 
-url = "https://studio.iterative.ai/api/model-registry/get-download-uris"
+url = "https://studio.datachain.ai/api/model-registry/get-download-uris"
 token = os.environ["DVC_STUDIO_TOKEN"]
 headers = {"Authorization": f"token {token}"}
 params = {
@@ -78,7 +78,7 @@ for rel_path, obj_url in json.loads(response.content).items():
 <tab title="CLI">
 
 ```cli
-$ curl "https://studio.iterative.ai/api/model-registry/[email protected]:iterative/demo-bank-customer-churn.git&name=randomforest-model&version=v2.0.0" --header "Authorization:token ${DVC_STUDIO_TOKEN}"
+$ curl "https://studio.datachain.ai/api/model-registry/[email protected]:iterative/demo-bank-customer-churn.git&name=randomforest-model&version=v2.0.0" --header "Authorization:token ${DVC_STUDIO_TOKEN}"
 
 {
     ".mlem/model/clf-model": "https://sandbox-datasets-iterative.s3.amazonaws.com/bank-customer-churn/86/bd02376ac675568ba2fac566169ef9?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAU7UXIWDIQFPCO76Q%2F20230706%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230706T134619Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=6807259ddd1f4448ed1e3c5d4503039884f7779381ee556175096b0a884ba1a6"

content/docs/studio/rest-api/index.md

@@ -5,7 +5,7 @@ information in DVC Studio and executing actions in it.
 
 The API is hosted under the `/api` route on the DVC Studio server:
 
-- https://studio.iterative.ai/api, or
+- https://studio.datachain.ai/api, or
 - https://your-domain/api in case of
   [self-hosted DVC Studio](/doc/studio/self-hosting/installation).
 

content/docs/studio/user-guide/account-management/index.md

@@ -118,7 +118,7 @@ The credentials must have the required permissions. For
 you can find more details about required permissions [here][data remote].
 
 [data remote]: /doc/user-guide/data-management/remote-storage
-[settings]: https://studio.iterative.ai/user/_/settings
+[settings]: https://studio.datachain.ai/user/_/settings
 
 Finally, click `Save credentials`.
 
@@ -153,7 +153,7 @@ granting full access to your Studio account.
 The available scopes are:
 
 - `Experiment operations` - DVC uses this scope to share [live experiments] and to
-  notify [Studio](https://studio.iterative.ai/) about [pushed experiments].
+  notify [Studio](https://studio.datachain.ai/) about [pushed experiments].
 - `Dataset operations` - [Coming soon](https://cloud.dvc.ai).
 - `Model registry operations` - like downloading model using
   `dvc artifacts get`.

content/docs/studio/user-guide/experiments/create-a-project.md

@@ -10,7 +10,7 @@ In this section, you will learn how to:
 
 To add a new project, follow these steps.
 
-1. Sign in to [DVC Studio](https://studio.iterative.ai/) using your GitHub.com,
+1. Sign in to [DVC Studio](https://studio.datachain.ai/) using your GitHub.com,
    GitLab.com, or Bitbucket.org account, or with your email address.
 
 2. Click on `Add a Project`. All the organizations that you have access to will

content/docs/studio/user-guide/git-connections/custom-gitlab-server.md

@@ -21,7 +21,7 @@ Once you have obtained the URL and Personal Access Token for your GitLab server,
 do the following:
 
 - Go to you team’s settings at
-  `https://studio.iterative.ai/team/<your team name>/settings`
+  `https://studio.datachain.ai/team/<your team name>/settings`
 - In the `GitLab connections` section, click on the `Connect GitLab server`
   button
 - Enter the URL and token in the form that opens up
@@ -37,7 +37,7 @@ you have any trouble setting up the connection to your GitLab server, please
 Connecting to a self-hosted GitLab server is different from connecting to your
 account on GitLab SaaS ([gitlab.com](http://gitlab.com/)). To connect to GitLab
 SaaS go to the `Git integrations` section in your
-[personal profile settings](https://studio.iterative.ai/user/_/profile). If you
+[personal profile settings](https://studio.datachain.ai/user/_/profile). If you
 signed up to use DVC Studio using your GitLab account, you may already have this
 connection.
 

content/docs/studio/user-guide/model-registry/view-and-compare-models.md

@@ -79,6 +79,6 @@ experimental iterations and make a decision to register a new version out of the
 latter.
 
 [gto]: /doc/gto
-[models dashboard]: https://studio.iterative.ai/team/Iterative/models
+[models dashboard]: https://studio.datachain.ai/team/Iterative/models
 [model detail page]:
-  https://studio.iterative.ai/team/Iterative/models/PTzV-9EJgmZ6TGspXtwKqw==/lightgbm-model/v2.0.1
+  https://studio.datachain.ai/team/Iterative/models/PTzV-9EJgmZ6TGspXtwKqw==/lightgbm-model/v2.0.1

content/docs/studio/user-guide/openid-connect.md

@@ -14,7 +14,7 @@ instructions.
 ### Generic configuration details
 
 - OpenID Connect Discovery URL:
-  https://studio.dvc.ai/api/.well-known/openid-configuration
+  https://studio.datachain.ai/api/.well-known/openid-configuration
 
 - Subject claim format: `credentials:{owner}/{name}` where `{owner}` is the name
   of the DVC Studio **user** or **team** owning the credentials, and `{name}` is
@@ -62,7 +62,7 @@ provider "aws" {
 }
 
 locals {
-  provider  = "studio.dvc.ai/api"
+  provider  = "studio.datachain.ai/api"
   condition = "credentials:example-team/example-credentials"
 }
 
@@ -137,7 +137,7 @@ provider "google" {
 }
 
 locals {
-  provider  = "studio.dvc.ai/api"
+  provider  = "studio.datachain.ai/api"
   condition = "credentials:example-team/example-credentials"
 }
 
@@ -226,7 +226,7 @@ provider "azurerm" {
 }
 
 locals {
-  provider  = "studio.dvc.ai/api"
+  provider  = "studio.datachain.ai/api"
   condition = "credentials:example-team/example-credentials"
 }
 

content/docs/studio/user-guide/single-sign-on.md

@@ -14,7 +14,7 @@ configuration on both DVC Studio and the IdP. The exact steps for this depend on
 the IdP.
 
 Once the SSO configuration is complete users can login to DVC Studio by opening
-their team's login page `http://studio.iterative.ai/api/teams/<TEAM_NAME>/sso`
+their team's login page `http://studio.datachain.ai/api/teams/<TEAM_NAME>/sso`
 in their browser. They can also login directly from their Okta end-user
 dashboards by clicking on the DVC Studio integration icon.
 
@@ -38,9 +38,9 @@ will be auto-assigned the [`Viewer` role](#roles).
       option).
    3. Enter any name (eg, `DVC Studio`) as the `App name`.
    4. `Single sign-on URL`:
-      [https://studio.iterative.ai/api/teams/<TEAM_NAME>/saml/consume](https://studio.iterative.ai/api/teams/<TEAM_NAME>/saml/consume)
+      [https://studio.datachain.ai/api/teams/<TEAM_NAME>/saml/consume](https://studio.datachain.ai/api/teams/<TEAM_NAME>/saml/consume)
       (Replace <TEAM_NAME> with the name of your team in Studio.
-   5. `Audience URI (SP Entity ID)`: https://studio.iterative.ai/api/saml
+   5. `Audience URI (SP Entity ID)`: https://studio.datachain.ai/api/saml
    6. `Name ID Format`: Persistent
    7. `Application username (NameID)`: Okta username
    8. `Attribute Statements (optional)`: 1. `Name`: email 2. `Name format`: URI
@@ -87,7 +87,7 @@ will be auto-assigned the [`Viewer` role](#roles).
    <admon>
 
    The Single Sign-on URL for your team is
-   [https://studio.iterative.ai/api/teams/<TEAM_NAME>/sso](https://studio.iterative.ai/api/teams/<TEAM_NAME>/saml/consume).
+   [https://studio.datachain.ai/api/teams/<TEAM_NAME>/sso](https://studio.datachain.ai/api/teams/<TEAM_NAME>/saml/consume).
    Users that you assign to your team can login to DVC Studio by opening the
    Single Sign-on URL and providing their Okta login credentials.
 

content/docs/studio/user-guide/team-collaboration/index.md

@@ -172,7 +172,7 @@ Details on how to configure SSO for your team can be found
 
 Once the SSO configuration is complete, users can login to DVC Studio using
 their team's login page at
-`http://studio.iterative.ai/api/teams/<TEAM_NAME>/sso`. They can also login
+`http://studio.datachain.ai/api/teams/<TEAM_NAME>/sso`. They can also login
 directly from their Okta dashboards by clicking on the DVC Studio integration
 icon.
 

content/docs/studio/user-guide/troubleshooting.md

@@ -6,7 +6,7 @@ DVC Studio.
 ## Support
 
 If you need further help, you can send us a message using `Help` on the
-[DVC Studio website](https://studio.iterative.ai). You can also
+[DVC Studio website](https://studio.datachain.ai). You can also
 [email us](mailto:[email protected]), create a support ticket on
 [GitHub](https://github.com/iterative/studio-support) or join the discussion in
 [Discord](https://discord.com/invite/dvwXA2N).
@@ -309,7 +309,7 @@ including versions and stage assignments.
 
 ## Questions or problems with billing and payment
 
-Check out the [Frequently Asked Questions](https://studio.iterative.ai/faq) to
+Check out the [Frequently Asked Questions](https://studio.datachain.ai/faq) to
 see if your questions have already been answered. If you still have problems,
 please [contact us](#support).
 

content/docs/use-cases/data-registry/tutorial.md

@@ -239,7 +239,7 @@ either in the UI or programmatically:
 ![Download Registry Datasets](https://static.iterative.ai/img/registry-download-datasets.gif)
 
 [remote storage]: /doc/user-guide/data-management/remote-storage
-[DVC Studio]: https://studio.iterative.ai
+[DVC Studio]: https://studio.datachain.ai
 [Version numbers]: /doc/studio/user-guide/model-registry/register-version
 [stages]: /doc/studio/user-guide/model-registry/assign-stage
 [semantic versioning]: https://semver.org

content/docs/use-cases/model-registry.md

@@ -43,7 +43,7 @@ supporting all stages of ML model lifecycle.
 To begin with this integrated approach to managing your ML models, [start
 managing models] with DVC!
 
-[DVC Studio]: https://studio.iterative.ai
+[DVC Studio]: https://studio.datachain.ai
 [gitops]: https://www.gitops.tech/
 [versions]: /doc/use-cases/versioning-data-and-models
 [start managing models]: /doc/start/model-registry

content/docs/user-guide/data-management/discovering-and-accessing-data.md

@@ -155,5 +155,5 @@ Studio], you can see models and their metadata across all projects, and you can
 artifacts by name, version, and lifecycle stage, without needing to configure access
 to the underlying Git repository or remote storage.
 
-[DVC Studio]: https://studio.iterative.ai
+[DVC Studio]: https://studio.datachain.ai
 [tutorial]: /doc/use-cases/data-registry/tutorial#sharing-and-managing-artifacts

content/docs/user-guide/env.md

@@ -38,4 +38,4 @@ See also [DVCLive environment variables](/doc/dvclive/env).
   /doc/user-guide/experiment-management/sharing-experiments#push-experiments
 [send live metrics and plots]:
   /doc/studio/user-guide/experiments/live-metrics-and-plots
-[dvc studio]: https://studio.iterative.ai
+[dvc studio]: https://studio.datachain.ai

content/docs/user-guide/experiment-management/comparing-experiments.md

@@ -335,7 +335,7 @@ artifacts, etc.) related with the experiments, you can use `dvc gc`.
 
 [dvc extension for vs code]:
   https://marketplace.visualstudio.com/items?itemName=Iterative.dvc
-[dvc studio]: https://studio.iterative.ai
+[dvc studio]: https://studio.datachain.ai
 [sharing experiments]: /doc/user-guide/experiment-management/sharing-experiments
 [visualizing and comparing experiments]:
   /doc/studio/user-guide/experiments/visualize-and-compare