add cpu/memory scaler

content/docs/2.0/concepts/scaling-deployments.md

@@ -51,13 +51,6 @@ spec:
   advanced:                                          # Optional. Section to specify advanced options
     restoreToOriginalReplicaCount: true/false        # Optional. Default: false
     horizontalPodAutoscalerConfig:                   # Optional. Section to specify HPA related options
-      resourceMetrics:                               # Optional. If not set, KEDA won't scale based on resource utilization
-      - name: cpu/memory                             # Name of the metric to scale on
-        target:
-          type: value/ utilization/ averagevalue
-          value: 60                                  # Optional
-          averageValue: 40                           # Optional
-          averageUtilization: 50                     # Optional
       behavior:                                      # Optional. Use to modify HPA's scaling behavior
         scaleDown:
           stabilizationWindowSeconds: 300
@@ -145,13 +138,6 @@ For example a `Deployment` with `3 replicas` is created, then `ScaledObject` is
 ```yaml
 advanced:
   horizontalPodAutoscalerConfig:                   # Optional. Section to specify HPA related options
-    resourceMetrics:                               # Optional. If not set, KEDA won't scale based on resource utilization
-    - name: cpu/memory                             # Name of the metric to scale on
-      target:
-        type: value/ utilization/ averagevalue
-        value: 60                                  # Optional
-        averageValue: 40                           # Optional
-        averageUtilization: 50                     # Optional
     behavior:                                      # Optional. Use to modify HPA's scaling behavior
       scaleDown:
         stabilizationWindowSeconds: 300
@@ -163,17 +149,6 @@ advanced:
 
 **`horizontalPodAutoscalerConfig:`**
 
- This section contains configuration that is the same as some parts of the standard Horizontal Pod Autoscaler (HPA) configuration. KEDA would feed properties from this section into a appropriate places into the HPA configuration. This way one can modify the HPA that is being created and managed by KEDA.
-
-**`horizontalPodAutoscalerConfig.resourceMetrics:`**
-
-This configuration can be used to scale resources based on standard resource metrics like CPU / Memory. KEDA would feed this value as resource metric(s) into the HPA itself. Please follow [Kubernetes documentation](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/) for details.
-* `name`: This is the name of the resource to be targeted as a metric (cpu, memory etc)
-* `type`: represents whether the metric type is Utilization, Value, or AverageValue.
-* `value`: is the target value of the metric (as a quantity).
-* `averageValue`: is the target value of the average of the metric across all relevant pods (quantity)
-* `averageUtilization`: is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods. Currently only valid for Resource metric source type.
-
 **`horizontalPodAutoscalerConfig.behavior`:**
 
 Starting from Kubernetes v1.18 the autoscaling API allows scaling behavior to be configured through the HPA behavior field. This way one can directly affect scaling of 1<->N replicas, which is internally being handled by HPA. KEDA would feed values from this section directly to the HPA's `behavior` field. Please follow [Kubernetes documentation](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#support-for-configurable-scaling-behavior) for details.

content/docs/2.0/scalers/cpu.md

@@ -0,0 +1,51 @@
++++
+title = "CPU"
+layout = "scaler"
+availability = "v2.0+"
+maintainer = "Community"
+description = "Scale applications based on cpu metrics."
+go_file = "cpu_memory_scaler"
++++
+
+> **Notice:** 
+> - This scaler will never scale to 0 and even when user define multiple scaler types (eg. Kafka + cpu/memory, or Prometheus + cpu/memory), the deployment will never scale to 0
+> - This scaler only applies to ScaledObject, not to Scaling Jobs.
+
+### Trigger Specification
+
+This specification describes the `cpu` trigger that scales based on cpu metrics.
+
+```yaml
+triggers:
+- type: cpu
+  metadata:
+    # Required
+    type: Value/ Utilization/ AverageValue
+    value: 60
+```
+
+**Parameter list:**
+
+- `type ` represents whether the metric type is Utilization, Value, or AverageValue. Required.
+- `value ` this value depends on the type setting
+	- if `type` set to `Value` this value is target value of the metric (as a quantity)
+	- if `type` set to `Utilization ` this value is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.
+	- if `type` set to `AverageValue` this value is the target value of the average of the metric across all relevant pods (quantity).
+
+### Example
+
+```yaml
+apiVersion: keda.sh/v1alpha1
+kind: ScaledObject
+metadata:
+  name: cpu-scaledobject
+  namespace: default
+spec:
+  scaleTargetRef:
+    name: my-deployment
+  triggers:
+  - type: cpu
+    metadata:
+      type: Utilization
+      type: "50"
+```

content/docs/2.0/scalers/memory.md

@@ -0,0 +1,49 @@
++++
+title = "Memory"
+layout = "scaler"
+availability = "v2.0+"
+maintainer = "Community"
+description = "Scale applications based on memory metrics."
+go_file = "cpu_memory_scaler"
++++
+> **Notice:** 
+> - This scaler will never scale to 0 and even when user define multiple scaler types (eg. Kafka + cpu/memory, or Prometheus + cpu/memory), the deployment will never scale to 0
+> - This scaler only applies to ScaledObject, not to Scaling Jobs.
+### Trigger Specification
+
+This specification describes the `memory` trigger that scales based on memory metrics.
+
+```yaml
+triggers:
+- type: memory
+  metadata:
+    # Required
+    type: Value/ Utilization/ AverageValue
+    value: 60
+```
+
+**Parameter list:**
+
+- `type ` represents whether the metric type is Utilization, Value, or AverageValue. Required.
+- `value ` this value depends on the type setting
+	- if `type` set to `Value` this value is target value of the metric (as a quantity)
+	- if `type` set to `Utilization ` this value is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.
+	- if `type` set to `AverageValue` this value is the target value of the average of the metric across all relevant pods (quantity).
+
+### Example
+
+```yaml
+apiVersion: keda.sh/v1alpha1
+kind: ScaledObject
+metadata:
+  name: memory-scaledobject
+  namespace: default
+spec:
+  scaleTargetRef:
+    name: my-deployment
+  triggers:
+  - type: memory
+    metadata:
+      type: Utilization
+      type: "50"
+```