Document the support for different metric types

content/docs/2.7/concepts/external-scalers.md

@@ -38,7 +38,7 @@ The `Scaler` interface defines 4 methods:
 - `Close` is called to allow the scaler to clean up connections or other resources.
 - `GetMetricSpec` returns the target value for the HPA definition for the scaler. For more details refer to [Implementing `GetMetricSpec`](#5-implementing-getmetricspec).
 - `GetMetrics` returns the value of the metric referred to from `GetMetricSpec`. For more details refer to [Implementing `GetMetrics`](#6-implementing-getmetrics).
-> Refer to the [HPA docs](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/) for how HPA calculates `replicaCount` based on metric value and target value. KEDA uses the metric target type `AverageValue` for external metrics. This will cause the metric value returned by the external scaler to be divided by the number of replicas.
+> Refer to the [HPA docs](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/) for how HPA calculates `replicaCount` based on metric value and target value. KEDA supports both `AverageValue` and `Value` metric target types for external metrics. When `AverageValue` (the default metric type) is used, the metric value returned by the external scaler will be divided by the number of replicas.
 
 The `PushScaler` interface adds a `Run` method. This method receives a push channel (`active`), on which the scaler can send `true` at any time. The purpose of this mechanism is to initiate a scaling operation independently from `pollingInterval`.
 

content/docs/2.7/concepts/scaling-deployments.md

@@ -66,8 +66,6 @@ spec:
   # {list of triggers to activate scaling of the target resource}
 ```
 
-> 💡 **NOTE:** You can find all supported triggers [here](/scalers).
-
 ### Details
 ```yaml
   scaleTargetRef:
@@ -116,7 +114,7 @@ The `cooldownPeriod` only applies after a trigger occurs; when you first create
 
 > 💡 **NOTE:** Due to limitations in HPA controller the only supported value for this property is 0, it will not work correctly otherwise. See this [issue](https://github.com/kedacore/keda/issues/2314) for more details.
 
-If this property is set, KEDA will scale the resource down to this number of replicas. If there's some activity on target triggers KEDA will scale the target resource immediately to `minReplicaCount` and then will be scaling handled by HPA. When there is no activity, the target resource is again scaled down to `idleReplicaCount`. This seting must be less than `minReplicaCount`.
+If this property is set, KEDA will scale the resource down to this number of replicas. If there's some activity on target triggers KEDA will scale the target resource immediately to `minReplicaCount` and then will be scaling handled by HPA. When there is no activity, the target resource is again scaled down to `idleReplicaCount`. This setting must be less than `minReplicaCount`.
 
 **Example:** If there's no activity on triggers the target resource is scaled down to `idleReplicaCount` (0), once there is an activity the target resource is immediately scaled to `minReplicaCount` (10) and then up to `maxReplicaCount` (100) as needed. If there's no activity on triggers the resource is again scaled down to `idleReplicaCount` (0).
 
@@ -155,10 +153,9 @@ Due to the HPA metric being of type `AverageValue` (see below), this will have t
 **Example:** When my instance of prometheus is unavailable 3 consecutive times, KEDA will change the HPA metric such that the deployment will scale to 6 replicas.
 
 There are a few limitations to using a fallback:
- - It is **not** supported by the CPU & memory scalers and will assume that fallback is disabled in those cases. This is because it only supports scalers that present their target as an `AverageValue` metric.
+ - It only supports scalers whose target is an `AverageValue` metric. Thus, it is **not** supported by the CPU & memory scalers, or by scalers whose metric target type is `Value`. In these cases, it will assume that fallback is disabled.
  - It is only supported by `ScaledObjects` **not** `ScaledJobs`.
 
-
 ---
 #### advanced
 ```yaml
@@ -195,6 +192,28 @@ Starting from Kubernetes v1.18 the autoscaling API allows scaling behavior to be
 
 **Assumptions:** KEDA must be running on Kubernetes cluster v1.18+, in order to be able to benefit from this setting.
 
+---
+#### triggers
+```yaml
+  triggers:
+  # {list of triggers to activate scaling of the target resource}
+```
+
+> 💡 **NOTE:** You can find all supported triggers [here](/scalers).
+
+Trigger fields:
+- **type**: The type of trigger to use. (Mandatory)
+- **metadata**: The configuration parameters that the trigger requires. (Mandatory)
+- **authenticationRef**: A reference to the `TriggerAuthentication` or `ClusterTriggerAuthentication` object that is used to authenticate the scaler with the environment.
+  - More details can be found [here](./authentication). (Optional)
+- **metricType**: The type of metric that should be used. (Values: `AverageValue`, `Value`, `Utilization`, Default: `AverageValue`, Optional)
+  - Learn more about how the [Horizontal Pod Autoscaler (HPA) calculates `replicaCount`](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/) based on metric type and value.
+  - To show the differences between the metric types, let's assume we want to scale a deployment with 3 running replicas based on a queue of messages:
+    - With `AverageValue` metric type, we can control how many messages, on average, each replica will handle. If our metric is the queue size, the threshold is 5 messages, and the current message count in the queue is 20, HPA will scale the deployment to 20 / 5 = 4 replicas, regardless of the current replica count.
+    - The `Value` metric type, on the other hand, can be used when we don't want to take the average of the given metric across all replicas. For example, with the `Value` type, we can control the average time of messages in the queue. If our metric is average time in the queue, the threshold is 5 milliseconds, and the current average time is 20 milliseconds, HPA will scale the deployment to 3 * 20 / 5 = 12.
+
+> ⚠️ **NOTE:** All scalers, except CPU and Memory, support metric types `AverageValue` and `Value` while CPU and Memory scalers both support `AverageValue` and `Utilization`.
+
 ## Long-running executions
 
 One important consideration to make is how this pattern can work with long running executions.  Imagine a deployment triggers on a RabbitMQ queue message.  Each message takes 3 hours to process.  It's possible that if many queue messages arrive, KEDA will help drive scaling out to many replicas - let's say 4.  Now the HPA makes a decision to scale down from 4 replicas to 2.  There is no way to control which of the 2 replicas get terminated to scale down.  That means the HPA may attempt to terminate a replica that is 2.9 hours into processing a 3 hour queue message.

content/docs/2.7/operate/events.md

@@ -8,23 +8,23 @@ weight = 100
 
 KEDA emits the following [Kubernetes Events](https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.19/#event-v1-core):
 
-| Event                               | Type      | Description                                                                                                                 |
-|-------------------------------------|-----------|-----------------------------------------------------------------------------------------------------------------------------|
-| `ScaledObjectReady`                 | `Normal`  | On the first time a ScaledObject is ready, or if the previous ready condition status of the object was `Unknown` or `False` |
-| `ScaledJobReady`                    | `Normal`  | On the first time a ScaledJob is ready, or if the previous ready condition status of the object was `Unknown` or `False`    |
-| `ScaledObjectCheckFailed`           | `Warning` | If the check validation for a ScaledObject fails                                                                            |
-| `ScaledJobCheckFailed`              | `Warning` | If the check validation for a ScaledJob fails                                                                               |
-| `ScaledObjectDeleted`               | `Normal`  | When a ScaledObject is deleted and removed from KEDA watch                                                                  |
-| `ScaledJobDeleted`                  | `Normal`  | When a ScaledJob is deleted and removed from KEDA watch                                                                     |
-| `KEDAScalersStarted`                | `Normal`  | When Scalers watch loop have started for a ScaledObject or ScaledJob                                                        |
-| `KEDAScalersStopped`                | `Normal`  | When Scalers watch loop have stopped for a ScaledObject or a ScaledJob                                                      |
-| `KEDAScalerFailed`                  | `Warning` | When a Scaler fails to create or check its event source                                                                     |
-| `KEDAScaleTargetActivated`          | `Normal`  | When the scale target (Deployment, StatefulSet, etc) of a ScaledObject is scaled to 1                                       |
-| `KEDAScaleTargetDeactivated`        | `Normal`  | When the scale target (Deployment, StatefulSet, etc) of a ScaledObject is scaled to 0                                       |
-| `KEDAScaleTargetActivationFailed`   | `Warning` | When KEDA fails to scale the scale target of a ScaledObject to 1                                                            |
-| `KEDAScaleTargetDeactivationFailed` | `Warning` | When KEDA fails to scale the scale target of a ScaledObject to 0                                                            |
-| `KEDAJobsCreated`                   | `Normal`  | When KEDA creates jobs for a ScaledJob                                                                                      |
-| `TriggerAuthenticationAdded`        | `Normal`  | When a new TriggerAuthentication is added                                                                                   |
-| `TriggerAuthenticationDeleted`      | `Normal`  | When a TriggerAuthentication is deleted                                                                                     |
-| `ClusterTriggerAuthenticationAdded` | `Normal`  | When a new ClusterTriggerAuthentication is added                                                                                   |
-| `ClusterTriggerAuthenticationDeleted`| `Normal`  | When a ClusterTriggerAuthentication is deleted                                                                                     |
+| Event                                 | Type      | Description                                                                                                                 |
+| ------------------------------------- | --------- | --------------------------------------------------------------------------------------------------------------------------- |
+| `ScaledObjectReady`                   | `Normal`  | On the first time a ScaledObject is ready, or if the previous ready condition status of the object was `Unknown` or `False` |
+| `ScaledJobReady`                      | `Normal`  | On the first time a ScaledJob is ready, or if the previous ready condition status of the object was `Unknown` or `False`    |
+| `ScaledObjectCheckFailed`             | `Warning` | If the check validation for a ScaledObject fails                                                                            |
+| `ScaledJobCheckFailed`                | `Warning` | If the check validation for a ScaledJob fails                                                                               |
+| `ScaledObjectDeleted`                 | `Normal`  | When a ScaledObject is deleted and removed from KEDA watch                                                                  |
+| `ScaledJobDeleted`                    | `Normal`  | When a ScaledJob is deleted and removed from KEDA watch                                                                     |
+| `KEDAScalersStarted`                  | `Normal`  | When Scalers watch loop have started for a ScaledObject or ScaledJob                                                        |
+| `KEDAScalersStopped`                  | `Normal`  | When Scalers watch loop have stopped for a ScaledObject or a ScaledJob                                                      |
+| `KEDAScalerFailed`                    | `Warning` | When a Scaler fails to create or check its event source                                                                     |
+| `KEDAScaleTargetActivated`            | `Normal`  | When the scale target (Deployment, StatefulSet, etc) of a ScaledObject is scaled to 1                                       |
+| `KEDAScaleTargetDeactivated`          | `Normal`  | When the scale target (Deployment, StatefulSet, etc) of a ScaledObject is scaled to 0                                       |
+| `KEDAScaleTargetActivationFailed`     | `Warning` | When KEDA fails to scale the scale target of a ScaledObject to 1                                                            |
+| `KEDAScaleTargetDeactivationFailed`   | `Warning` | When KEDA fails to scale the scale target of a ScaledObject to 0                                                            |
+| `KEDAJobsCreated`                     | `Normal`  | When KEDA creates jobs for a ScaledJob                                                                                      |
+| `TriggerAuthenticationAdded`          | `Normal`  | When a new TriggerAuthentication is added                                                                                   |
+| `TriggerAuthenticationDeleted`        | `Normal`  | When a TriggerAuthentication is deleted                                                                                     |
+| `ClusterTriggerAuthenticationAdded`   | `Normal`  | When a new ClusterTriggerAuthentication is added                                                                            |
+| `ClusterTriggerAuthenticationDeleted` | `Normal`  | When a ClusterTriggerAuthentication is deleted                                                                              |

content/docs/2.7/scalers/cassandra.md

@@ -35,7 +35,7 @@ triggers:
 - `protocolVersion` - CQL Binary Protocol. (Default: `4`, Optional)
 - `keyspace` - The name of the keyspace used in Cassandra.
 - `query` - A Cassandra query that should return single numeric value.
-- `targetQueryValue` - The threshold value that is provided by the user and used as `targetAverageValue` in the Horizontal Pod Autoscaler (HPA).
+- `targetQueryValue` - The threshold value that is provided by the user and used as `targetValue` or `targetAverageValue` (depending on the trigger metric type) in the Horizontal Pod Autoscaler (HPA).
 - `metricName` - Name to assign to the metric. (Default: `s<X>-cassandra-<KEYSPACE>`, Optional, In case of `metricName` is specified, it will be used to generate the `metricName` like this: `s<X>-cassandra-<METRICNAME>`, where `<X>` is the index of the trigger in a ScaledObject)
 
 ### Authentication Parameters

content/docs/2.7/scalers/cpu.md

@@ -18,9 +18,9 @@ This specification describes the `cpu` trigger that scales based on cpu metrics.
 ```yaml
 triggers:
 - type: cpu
+  metricType: Utilization/ AverageValue
   metadata:
-    # Required
-    type: Utilization/ AverageValue
+    type: Utilization/ AverageValue # Deprecated in favor of trigger.metricType
     value: "60"
 ```
 
@@ -31,6 +31,8 @@ triggers:
 	- When using `Utilization`, the target value is the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.
 	- When using `AverageValue`, the target value is the target value of the average of the metric across all relevant pods (quantity).
 
+> 💡 **NOTE:** The `type` parameter is deprecated in favor of the global `metricType` and will be removed in a future release. Users are advised to use `metricType` instead.
+
 ### Example
 
 ```yaml
@@ -44,7 +46,7 @@ spec:
     name: my-deployment
   triggers:
   - type: cpu
+    metricType: Utilization
     metadata:
-      type: Utilization
       value: "50"
 ```

content/docs/2.7/scalers/datadog.md

@@ -20,10 +20,11 @@ This specification describes the `datadog` trigger that scales based on a Datado
 ```yaml
 triggers:
 - type: datadog
+  metricType: Value
   metadata:
     query: "sum:trace.redis.command.hits{env:none,service:redis}.as_count()"
     queryValue: "7"
-    type: "global"
+    type: "global" # Deprecated in favor of trigger.metricType
     age: "120"
     metricUnavailableValue: "0"
 ```
@@ -36,6 +37,8 @@ triggers:
 - `age`: The time window (in seconds) to retrieve metrics from Datadog. (Default: `90`, Optional) 
 - `metricUnavailableValue`: The value of the metric to return to the HPA if Datadog doesn't find a metric value for the specified time window. If not set, an error will be returned to the HPA, which will log a warning. (Optional)
 
+> 💡 **NOTE:** The `type` parameter is deprecated in favor of the global `metricType` and will be removed in a future release. Users are advised to use `metricType` instead.
+
 ### Authentication
 
 Datadog requires both an API key and an APP key to retrieve metrics from your account.
@@ -97,13 +100,13 @@ spec:
     name: worker
   triggers:
   - type: datadog
+    # Optional: (Value or AverageValue). Whether the target value is global or average per pod. Default: AverageValue
+    metricType: "Value"
     metadata:
       # Required: datadog metric query
       query: "sum:trace.redis.command.hits{env:none,service:redis}.as_count()"
       # Required: according to the number of query result, to scale the TargetRef
       queryValue: "7"
-      # Optional: (Global or Average). Whether the target value is global or average per pod. Default: Average
-      type: "Global"
       # Optional: The time window (in seconds) to retrieve metrics from Datadog. Default: 90
       age: "120"
       # Optional: The metric value to return to the HPA if a metric value wasn't found for the specified time window

content/docs/2.7/scalers/memory.md

@@ -18,9 +18,9 @@ This specification describes the `memory` trigger that scales based on memory me
 ```yaml
 triggers:
 - type: memory
+  metricType: Utilization/ AverageValue
   metadata:
-    # Required
-    type: Utilization/ AverageValue
+    type: Utilization/ AverageValue # Deprecated in favor of trigger.metricType
     value: "60"
 ```
 
@@ -31,6 +31,8 @@ triggers:
 	- When using `Utilization`, the target value is the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.
 	- When using `AverageValue`, the target value is the target value of the average of the metric across all relevant pods (quantity).
 
+> 💡 **NOTE:** The `type` parameter is deprecated in favor of the global `metricType` and will be removed in a future release. Users are advised to use `metricType` instead.
+
 ### Example
 
 ```yaml
@@ -44,7 +46,7 @@ spec:
     name: my-deployment
   triggers:
   - type: memory
+    metricType: Utilization
     metadata:
-      type: Utilization
       value: "50"
 ```

content/docs/2.7/scalers/mssql.md

@@ -42,7 +42,7 @@ triggers:
 The `mssql` trigger always requires the following information:
 
 - `query` - A [T-SQL](https://docs.microsoft.com/sql/t-sql/language-reference) query that returns a single numeric value. This can be a regular query or the name of a stored procedure.
-- `targetValue` - A threshold that is used as `targetAverageValue` in the Horizontal Pod Autoscaler (HPA).
+- `targetValue` - A threshold that is used as `targetValue` or `targetAverageValue` (depending on the trigger metric type) in the Horizontal Pod Autoscaler (HPA).
 
 To connect to the MSSQL instance, you can provide either:
 

content/docs/2.7/scalers/mysql.md

@@ -14,7 +14,7 @@ This specification describes the `mysql` trigger that scales based on result of
 The trigger always requires the following information:
 
 - `query` - A MySQL query that should return single numeric value.
-- `queryValue` - A threshold that is used as `targetAverageValue` in HPA.
+- `queryValue` - A threshold that is used as `targetValue` or `targetAverageValue` (depending on the trigger metric type) in HPA.
 
 To provide information about how to connect to MySQL you can provide: