chore: move to the new hub url (#5302)

jina-ai · Oct 25, 2022 · 92ea7fb · 92ea7fb
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diff --git a/.github/hub-system.svg b/.github/hub-system.svg
diff --git a/README.md b/README.md
@@ -35,7 +35,7 @@ Applications built with Jina enjoy the following features out of the box:
   - Async and non-blocking data processing over dynamic flows.
 
 ☁️ **Cloud-native**
-  - Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via [Executor Hub](https://hub.jina.ai).
+  - Seamless Docker container integration: sharing, exploring, sandboxing, versioning and dependency control via [Executor Hub](https://cloud.jina.ai).
   - Full observability via Prometheus and Grafana.
   - Fast deployment to Kubernetes, Docker Compose.
 
@@ -338,7 +338,7 @@ executors:
 
 ### Seamless Container integration
 
-Without having to worry about dependencies, you can easily share your Executors with others; or use public/private Executors in your project thanks to [Executor Hub](https://hub.jina.ai).
+Without having to worry about dependencies, you can easily share your Executors with others; or use public/private Executors in your project thanks to [Executor Hub](https://cloud.jina.ai).
 
 To create an Executor:
 

diff --git a/docs/_templates/sidebar/navigation.html b/docs/_templates/sidebar/navigation.html
@@ -7,7 +7,7 @@
                 <img class="sidebar-ecosys-logo only-light-line" src="{{ pathto('_static/search-light.svg', 1) }}">
                 <img class="sidebar-ecosys-logo only-dark-line" src="{{ pathto('_static/search-dark.svg', 1) }}">
                 Jina</a></li>
-        <li class="toctree-l1"><a class="reference external" href="https://hub.jina.ai">
+        <li class="toctree-l1"><a class="reference external" href="https://cloud.jina.ai">
             <img class="sidebar-ecosys-logo only-light-line" src="{{ pathto('_static/hub-light.svg', 1) }}">
             <img class="sidebar-ecosys-logo only-dark-line" src="{{ pathto('_static/hub-dark.svg', 1) }}">
             Jina Hub</a></li>

diff --git a/docs/fundamentals/executor/executor-run.md b/docs/fundamentals/executor/executor-run.md
@@ -32,7 +32,7 @@ Text: hello world
 
 
 ````{tab} From Executor Hub
-You can pull an Executor from Executor Hub and use it directly as a Python object. [Executor Hub](https://hub.jina.ai/) is our marketplace for Executors.
+You can pull an Executor from Executor Hub and use it directly as a Python object. [Executor Hub](https://cloud.jina.ai/) is our marketplace for Executors.
 
 ```python
 from docarray import Document, DocumentArray

diff --git a/docs/fundamentals/executor/hub/debug-executor.md b/docs/fundamentals/executor/hub/debug-executor.md
@@ -6,7 +6,7 @@
 This does not work for containerized Executors.
 ````
 
-In this tutorial you will learn how to debug [Hello Executor](https://hub.jina.ai/executor/9o9yjq1q) step by step.
+In this tutorial you will learn how to debug [Hello Executor](https://cloud.jina.ai/executor/9o9yjq1q) step by step.
 
 ## Pull the Executor
 

diff --git a/docs/fundamentals/executor/hub/hub-portal.md b/docs/fundamentals/executor/hub/hub-portal.md
@@ -2,7 +2,7 @@
 
 Executor Hub is a marketplace for {class}`~jina.Executor`s where you can upload your own Executors or use ones already developed by the community. If this is your first time developing an Executor you can check our {ref}`tutorials <create-hub-executor>` that guide you through the process.
 
-Let's see the [Hub portal](https://hub.jina.ai) in detail.
+Let's see the [Hub portal](https://cloud.jina.ai) in detail.
 
 ## Catalog page
 
@@ -50,4 +50,4 @@ On the left, you'll see possible ways to use this Executor, including Docker ima
 :align: center
 ```
 
-That's it. Now you have an overview of the [Hub portal](https://hub.jina.ai) and how to navigate it. 
+That's it. Now you have an overview of the [Hub portal](https://cloud.jina.ai) and how to navigate it. 
diff --git a/docs/fundamentals/executor/hub/push-executor.md b/docs/fundamentals/executor/hub/push-executor.md
@@ -25,7 +25,7 @@ If you haven't logged into Jina, it will return `NAME` and `SECRET`. You need th
 If you are logged into the Hub using our CLI tools (`jina auth login` or `jcloud login`), you can push and pull your Executors without `SECRET`.
 ````
 
-You can then visit [Executor Hub](https://hub.jina.ai), select the "Recent" tab and see your published Executor.
+You can then visit [Executor Hub](https://cloud.jina.ai), select the "Recent" tab and see your published Executor.
 
 ````{admonition} Note
 :class: note

diff --git a/docs/fundamentals/executor/hub/use-hub-executor.md b/docs/fundamentals/executor/hub/use-hub-executor.md
@@ -57,7 +57,7 @@ To use a private Executor, you must provide the `SECRET` which is generated afte
 If you are a Mac user, please use `host.docker.internal` as your URL when you want to connect a local port from an Executor
 Docker container.
 
-For example: [PostgreSQLStorage](https://hub.jina.ai/executor/d45rawx6)
+For example: [PostgreSQLStorage](https://cloud.jina.ai/executor/d45rawx6)
 will connect PostgreSQL server which was started locally. Then you must use it with:
 
 ```python

diff --git a/docs/fundamentals/jcloud/index.md b/docs/fundamentals/jcloud/index.md
@@ -58,7 +58,7 @@ A Flow can have two types of file structure: a single YAML file or a project fol
 
 A self-contained YAML file, consisting of all configuration at the [Flow](https://docs.jina.ai/fundamentals/flow/)-level and [Executor](https://docs.jina.ai/fundamentals/executor/)-level.
 
-> All Executors' `uses` must follow the format `jinahub+docker://MyExecutor` (from [Executor Hub](https://hub.jina.ai)) to avoid any local file dependencies:
+> All Executors' `uses` must follow the format `jinahub+docker://MyExecutor` (from [Executor Hub](https://cloud.jina.ai)) to avoid any local file dependencies:
 
 ```yaml
 # flow.yml

diff --git a/docs/get-started/what-is-jina.md b/docs/get-started/what-is-jina.md
@@ -179,7 +179,7 @@ Here's the deal. These features come out of the box with the above 15 lines of c
 - gRPC, Websockets, HTTP, GraphQL gateway support
 - Microservice from day one, seamless Docker containerization
 - Explicit version and dependency control
-- Reusable building blocks from [Hub marketplace](https://hub.jina.ai)
+- Reusable building blocks from [Hub marketplace](https://cloud.jina.ai)
 - Immediate observability via Prometheus and Grafana
 - Seamless Kubernetes integration.
 

diff --git a/docs/how-to/docker-compose.md b/docs/how-to/docker-compose.md
@@ -49,8 +49,8 @@ the Gateway are built with the same Jina version to guarantee compatibility.
 
 Install [`Docker Compose`](https://docs.docker.com/compose/install/) locally to follow this how-to.
 
-This example shows how to build and deploy a Flow with Docker Compose, using [`CLIPImageEncoder`](https://hub.jina.ai/executor/0hnlmu3q)
-as an image encoder and [`ANNLiteIndexer`](https://hub.jina.ai/executor/7yypg8qk) as an indexer to perform fast nearest
+This example shows how to build and deploy a Flow with Docker Compose, using [`CLIPImageEncoder`](https://cloud.jina.ai/executor/0hnlmu3q)
+as an image encoder and [`ANNLiteIndexer`](https://cloud.jina.ai/executor/7yypg8qk) as an indexer to perform fast nearest
 neighbor retrieval on image embeddings.
 
 ### Deploy the Flow

diff --git a/docs/how-to/gpu-executor.md b/docs/how-to/gpu-executor.md
@@ -130,7 +130,7 @@ pip install jina
 ```{admonition} Executor Hub
 :class: hint
 
-Let's create an Executor using [Executor Hub](https://hub.jina.ai/). This still creates your Executor locally
+Let's create an Executor using [Executor Hub](https://cloud.jina.ai/). This still creates your Executor locally
 and privately, but makes it quick and easy to run your
 Executor inside a Docker container, or (if you so choose) to publish it to Executor Hub later.
 ```

diff --git a/docs/how-to/kubernetes.md b/docs/how-to/kubernetes.md
@@ -70,7 +70,7 @@ You can essentially define any Flow of your liking.
 Just ensure that all Executors are containerized, either by using *'jinahub+docker'*, or by {ref}`containerizing your local
 Executors <dockerize-exec>`.
 
-The example Flow here simply encodes and indexes text or image data using two Executors from [Executor Hub](https://hub.jina.ai/).
+The example Flow here simply encodes and indexes text or image data using two Executors from [Executor Hub](https://cloud.jina.ai/).
 
 Next, generate Kubernetes YAML configs from the Flow.
 It's good practice to define a new Kubernetes namespace for that purpose:

diff --git a/docs/how-to/scale-out.md b/docs/how-to/scale-out.md
@@ -107,7 +107,7 @@ As you can see, it now only takes three seconds to finish the task. If you deplo
 ### Context
 
 Now with the text corpus encoded as TF-IDF embeddings, it's time to save the results.
-We'll use Jina's [ANNLiteIndexer](https://hub.jina.ai/executor/7yypg8qk) to persist the embeddings for fast Approximate Nearest Neighbor Search.
+We'll use Jina's [ANNLiteIndexer](https://cloud.jina.ai/executor/7yypg8qk) to persist the embeddings for fast Approximate Nearest Neighbor Search.
 
 Let's add `ANNLiteIndexer` to the Flow: