docs: update

jina-ai · Aug 11, 2022 · 80d4bbb · 80d4bbb
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diff --git a/docs/fundamentals/jcloud/autoscale.md b/docs/fundamentals/jcloud/autoscale.md
@@ -3,51 +3,53 @@
 In JCloud, demand-based autoscaling functionality is naturally offered thanks to the underlying Kubernetes architecture. This means that you can maintain [serverless](https://en.wikipedia.org/wiki/Serverless_computing) deployments in a cost-effective way with no headache of setting the [right number of replicas](https://docs.jina.ai/how-to/scale-out/#scale-out-your-executor) anymore!
 
 ## Configurations
-Autoscaling configurations can be specified on a per Executor basis using the `autoscale` argument in your Flow YAML, such as:
+
+Autoscaling can be enabled by using `jinahub+serverless` protocol for Exectuor's `uses` in the Flow YAML, such as:
 
 ```yaml
 jtype: Flow
 executors:
   - name: executor1
-    uses: jinahub+docker://Executor1
-    jcloud:
-      autoscale:
-        min: 1
-        max: 2
-        metric: rps
-        target: 50
+    uses: jinahub+serverless://Executor1
 ```
 
-Below are the configurations explained in detail:
+JCloud Autoscaling leverages [Knative](https://knative.dev/docs/) behind the scenes, and `jinahub+serverless` uses a set of Knative configuratons as defaults:
 
 ```{note}
-JCloud Autoscaling leverages [Knative](https://knative.dev/docs/), where the configurations are directly supported. For more information, please visit [Knative Autoscaling](https://knative.dev/docs/serving/autoscaling/).
+For more information about the Knative Autoscaling configurations, please visit [Knative Autoscaling](https://knative.dev/docs/serving/autoscaling/).
 ```
 
+| Name   | Value       | Description                                     |
+|--------|-------------|-------------------------------------------------|
+| min    | 0           | Minimum number of replicas (0 means serverless) |
+| max    | 2           | Maximum number of replicas                      |
+| metric | concurrency | Metric for scaling                              |
+| target | 100         | Target number after which replicas autoscale    |
 
-| Name   | Default     | Allowed                   | Description                                                      |
-|--------|-------------|---------------------------|------------------------------------------------------------------|
-| min    | 1           | int                       | Minimum number of replicas (0 means serverless)                  |
-| max    | 2           | int                       | Maximum number of replicas (up to 5)                             |
-| metric | concurrency | `concurrency`   /   `rps` | Metric for scaling                                               |
-| target | 100         | int                       | Target number for concurrency/rps after which replicas autoscale |
 
-## Serverless
-
-We also support using `jinahub+serverless` protocol for Exectuor's `uses` in the Flow YAML to indiciate the enrollment of Autoscaling, such as:
+If `jinahub+serverless` doesn't meet your requirements, you can further customize Autoscaling configurations by using the `autoscale` argument on a per Executor basis in the Flow YAML, such as:
 
 ```yaml
 jtype: Flow
 executors:
   - name: executor1
-    uses: jinahub+serverless://Executor1
+    uses: jinahub+docker://Executor1
+    jcloud:
+      autoscale:
+        min: 1
+        max: 2
+        metric: rps
+        target: 50
 ```
 
-Example above will take the following defaults:
+Below are the defaults and requirements for the configurations:
 
-| min | max | metric      | target |
-|-----|-----|-------------|--------|
-| 0   | 2   | concurrency | 100    |
+| Name   | Default     | Allowed                  |
+|--------|-------------|--------------------------|
+| min    | 1           | int                      |
+| max    | 2           | int, up to 5             |
+| metric | concurrency | `concurrency`  /   `rps` |
+| target | 100         | int                      |
 
 After JCloud deployment using the Autoscaling configurations, the Flow serving part is just the same; the only difference you would probably notice is it may take extra seconds
 to handle the initial requests since it may need to scale the deployments behind the scenes. Let JCloud handle the scaling from now on and you should only worry about the code!