chore: Promote Scaling Modifiers to GA (#1460)

* chore: Promote Scaling Modifiers to GA Signed-off-by: Jorge Turrado <[email protected]> * chore: Promote Scaling Modifiers to GA Signed-off-by: Jorge Turrado <[email protected]> * chore: Promote Scaling Modifiers to GA Signed-off-by: Jorge Turrado <[email protected]> --------- Signed-off-by: Jorge Turrado <[email protected]>
kedacore · Aug 27, 2024 · 4c95c44 · 4c95c44
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diff --git a/content/docs/2.15/concepts/scaling-deployments.md b/content/docs/2.15/concepts/scaling-deployments.md
@@ -68,7 +68,7 @@ Typically, either one or the other is being used given they serve a different pu
 To unpause (reenable) autoscaling again, remove all paused annotations from the `ScaledObject` definition. If you paused with `autoscaling.keda.sh/paused`, you can unpause by setting the annotation to `false`.
 
 
-## Scaling Modifiers (Experimental)
+## Scaling Modifiers
 
 **Example: compose average value**
 

diff --git a/content/docs/2.15/reference/scaledobject-spec.md b/content/docs/2.15/reference/scaledobject-spec.md
@@ -209,7 +209,7 @@ advanced:
 
 ### scalingModifiers
 
-The `scalingModifiers` is optional and **experimental**. If defined, both `target` and `formula` are mandatory. Using this structure creates `composite-metric` for the HPA that will replace all requests for external metrics and handle them internally. With `scalingModifiers` each trigger used in the `formula` **must** have a name defined.
+If defined, both `target` and `formula` are mandatory. Using this structure creates `composite-metric` for the HPA that will replace all requests for external metrics and handle them internally. With `scalingModifiers` each trigger used in the `formula` **must** have a name defined.
 
 #### scalingModifiers.target
 
@@ -227,7 +227,7 @@ The `scalingModifiers` is optional and **experimental**. If defined, both `targe
 
   `formula` composes metrics together and allows them to be modified/manipulated. It accepts mathematical/conditional statements using [this external project](https://github.com/antonmedv/expr). If the `fallback` scaling feature is in effect, the `formula` will NOT modify its metrics (therefore it modifies metrics only when all of their triggers are healthy). Complete language definition of `expr` package can be found [here](https://expr.medv.io/docs/Language-Definition). Formula must return a single value (not boolean).
 
-For examples of this feature see section [Scaling Modifiers](../concepts/scaling-deployments.md#scaling-modifiers-experimental).
+For examples of this feature see section [Scaling Modifiers](../concepts/scaling-deployments.md).
 
 
 ## triggers

diff --git a/content/docs/2.16/concepts/scaling-deployments.md b/content/docs/2.16/concepts/scaling-deployments.md
@@ -68,7 +68,7 @@ Typically, either one or the other is being used given they serve a different pu
 To unpause (reenable) autoscaling again, remove all paused annotations from the `ScaledObject` definition. If you paused with `autoscaling.keda.sh/paused`, you can unpause by setting the annotation to `false`.
 
 
-## Scaling Modifiers (Experimental)
+## Scaling Modifiers
 
 **Example: compose average value**
 

diff --git a/content/docs/2.16/reference/scaledobject-spec.md b/content/docs/2.16/reference/scaledobject-spec.md
@@ -209,7 +209,7 @@ advanced:
 
 ### scalingModifiers
 
-The `scalingModifiers` is optional and **experimental**. If defined, both `target` and `formula` are mandatory. Using this structure creates `composite-metric` for the HPA that will replace all requests for external metrics and handle them internally. With `scalingModifiers` each trigger used in the `formula` **must** have a name defined.
+If defined, both `target` and `formula` are mandatory. Using this structure creates `composite-metric` for the HPA that will replace all requests for external metrics and handle them internally. With `scalingModifiers` each trigger used in the `formula` **must** have a name defined.
 
 #### scalingModifiers.target
 
@@ -227,7 +227,7 @@ The `scalingModifiers` is optional and **experimental**. If defined, both `targe
 
   `formula` composes metrics together and allows them to be modified/manipulated. It accepts mathematical/conditional statements using [this external project](https://github.com/antonmedv/expr). If the `fallback` scaling feature is in effect, the `formula` will NOT modify its metrics (therefore it modifies metrics only when all of their triggers are healthy). Complete language definition of `expr` package can be found [here](https://expr.medv.io/docs/Language-Definition). Formula must return a single value (not boolean).
 
-For examples of this feature see section [Scaling Modifiers](../concepts/scaling-deployments.md#scaling-modifiers-experimental).
+For examples of this feature see section [Scaling Modifiers](../concepts/scaling-deployments.md).
 
 
 ## triggers