docs: add JCloud deployment docs (#739)

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jina-ai · Jun 8, 2022 · 130108c · 130108c
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diff --git a/docs/user-guides/images/jc-deploy.png b/docs/user-guides/images/jc-deploy.png
diff --git a/docs/user-guides/server.md b/docs/user-guides/server.md
@@ -486,5 +486,70 @@ r = c.encode(
     ]
 )
 ```
+## Deploy on JCloud
 
+You can deploy `CLIPTorchEncoder` on JCloud. 
+A minimum YAML file `flow.yml` is as follows:
 
+```yaml
+jtype: Flow
+executors:
+  - name: CLIPTorchEncoder # The name of the encoder
+    uses: jinahub+docker://CLIPTorchEncoder
+```
+
+```{warning}
+All Executors' `uses` must follow the format `jinahub+docker://MyExecutor` (from [Jina Hub](https://hub.jina.ai)) to avoid any local file dependencies.
+```
+
+To deploy,
+
+```bash
+$ jc deploy flow.yml
+```
+
+Here `jc deploy` is the command to deploy a Jina project to JCloud.
+Learn more about [JCloud usage](https://github.com/jina-ai/jcloud).
+
+
+The Flow is successfully deployed when you see:
+
+```{figure} images/jc-deploy.png
+:width: 60%
+
+```
+
+After deploying on jcloud, you can connect to it via client by setting  `grpcs://` as follows:
+
+
+```python
+from clip_client import Client
+
+c = Client('grpcs://174eb69ba3.wolf.jina.ai')  # This is the URL you get from previous step
+
+r = c.encode(
+    [
+        'First do it',
+        'then do it right',
+        'then do it better',
+        'https://picsum.photos/200',
+    ]
+)
+print(r)
+```
+
+will give you:
+
+```text
+[[ 0.03480401 -0.23519686  0.01041038 ... -0.5229086  -0.10081214
+   -0.08695138]
+ [-0.0683605  -0.00324154  0.01490371 ... -0.50309485 -0.06193433
+   -0.08574048]
+ [ 0.15041807 -0.07933374 -0.06650036 ... -0.46410388 -0.08535041
+   0.04270519]
+ [-0.16183889  0.10636599 -0.2062868  ... -0.41244072  0.19485454
+   0.05658712]]
+```
+
+
+It means the client and the JCloud server are now connected. Well done!