docs(srv): update

Author: SamyOubouaziz

pages/serverless-containers/reference-content/containers-autoscaling.mdx

@@ -18,19 +18,27 @@ categories:
 
 [Autoscaling](/serverless-containers/concepts/#autoscaling) offers several benefits, including improved responsiveness and cost efficiency. By automatically adjusting the number of instances of your resource based on current demand, you ensure that your applications can handle varying loads without manual intervention. This not only enhances user experience by maintaining performance levels but also helps in reducing costs by only using resources when necessary. Additionally, autoscaling helps in optimal resource utilization, minimizing the risk of performance degradation during peak times.
 
-## Minimum and maximum scales
+Autoscaling can be based on exactly one of the following parameters:
 
-### Minimum scale (min-scale)
+- Request concurrency
+- CPU percentage
+- RAM percentage
 
-This parameter sets the lowest value your resource is allowed to scale down to:
+## Request concurrency
+
+### Minimum and maximum scales
+
+#### Minimum scale (min-scale)
+
+This parameter sets the minimum number of instances your resource is allowed to scale down to:
 
 - If you set a value of `0`, all instances of your resource will be terminated after 15 minutes of inactivity.
 
 - If you set a value of `1` or more, the corresponding number of instances of your resource will remain available at all time.
 
 Customizing the minimum scale for Serverless can help ensure that an instance remains pre-allocated and ready to handle requests, reducing delays associated with [cold starts](/serverless-containers/concepts/#cold-start). However, this setting also impacts the costs of your Serverless Container.
 
-### Maximum scale (max-scale)
+#### Maximum scale (max-scale)
 
 This parameter sets the maximum number of instances of your resource. You should adjust it based on your resource's traffic spikes, keeping in mind that you may wish to limit the max scale to manage costs effectively.
 
@@ -51,4 +59,26 @@ The same autoscaler decides to remove instances when:
 
 <Message type="note">
 Redeploying your resource results in the termination of existing instances and a return to the min scale, which you observe when redeploying.
-</Message>
+</Message>
+
+## CPU and RAM percentage
+
+### Minimum and maximum scales
+
+#### Minimum scale (min-scale)
+
+This parameter sets the minimum number of instances your resource is allowed to scale down to.
+
+<Message type="note">
+For technical reasons, the minimum scale for CPU/RAM-based autoscaling is `1`.
+</Message>
+
+#### Maximum scale (max-scale)
+
+This parameter sets the maximum number of instances of your resource. You should adjust it based on your resource's CPU or RAM usage spikes, keeping in mind that you may wish to limit the max scale to manage costs effectively.
+
+### Autoscaler behavior
+
+The autoscaler decides to start new instances when the existing instances' CPU or RAM usage exceeds the threshold you defined for a certain amount of time.
+
+The same autoscaler decides to remove existing instances when the CPU or RAM usage of certain instances is reduced, and the remaining instances' usage does not exceed the threshold.