[CASCL-1493] change autoscaling profile values and descriptions (#37647)

Author: alekseidiukov

content/en/containers/autoscaling/_index.md

@@ -232,8 +232,8 @@ There are three ways to enable autoscaling for a workload. Pick the path that ma
 The fastest way to get started is the [Setup page][11] in the Datadog UI. The wizard walks you through five steps: select a cluster, verify Agent and permission requirements, choose an install method, pick a scaling template, and deploy. Templates available in the wizard:
 
 - **Optimize cost**: high CPU utilization target, aggressive scale-down, lowest replica floor. Best for stateless, cost-sensitive workloads.
-- **Optimize balance**: moderate utilization target, balanced scale-up and scale-down. Best for most stateless workloads.
-- **Optimize performance**: conservative utilization target, slow scale-down, higher replica floor. Best for stateful or critical services.
+- **Optimize balance**: moderate utilization target, fast scale-up, balanced scale-down. Best for most stateless workloads.
+- **Optimize performance**: conservative utilization target, fast scale-up, slow scale-down, higher replica floor. Best for stateful or critical services.
 - **Customize**: start from any of the above and tune CPU target, replicas, and stabilization windows yourself.
 
 The Setup wizard is best for trying autoscaling on a single workload, getting hands-on with a recommendation, or onboarding a small set of workloads. (Requires `Workload Scaling Write` and `Autoscaling Manage` permissions.)
@@ -282,7 +282,7 @@ spec:
                 - periodSeconds: 120
                   type: Percent
                   value: 50
-            stabilizationWindowSeconds: 300
+            stabilizationWindowSeconds: 190
         update:
             strategy: Auto
     constraints:
@@ -302,7 +302,7 @@ spec:
 {{% /tab %}}
 {{% tab "Optimize Balance" %}}
 
-Pick this template when you want savings without trading off availability. It's a sensible default for most stateless workloads. The defining setting is the moderate CPU utilization target (70%) paired with a conservative scale-down (20% every 20 minutes) and a two-replica minimum. The controller adds capacity rapidly but removes it slowly.
+Pick this template when you want savings without trading off availability. It's a sensible default for most stateless workloads. The defining setting is the moderate CPU utilization target (70%) paired with a conservative scale-down and a two-replica minimum. The controller adds capacity rapidly but removes it slowly.
 
 ```yaml
 apiVersion: datadoghq.com/v1alpha2
@@ -330,7 +330,7 @@ spec:
                 - periodSeconds: 120
                   type: Percent
                   value: 50
-            stabilizationWindowSeconds: 600
+            stabilizationWindowSeconds: 130
         update:
             strategy: Auto
     constraints:
@@ -417,7 +417,7 @@ spec:
                 - periodSeconds: 120
                   type: Percent
                   value: 50
-            stabilizationWindowSeconds: 600
+            stabilizationWindowSeconds: 130
         # Vertical updates disabled — horizontal only
         update:
             strategy: Disabled
@@ -472,9 +472,9 @@ The Cluster Agent ships three built-in profiles and recreates them on startup, s
 
 | Profile | CPU target | Min replicas | Profile of behavior |
 |---|---|---|---|
-| `datadog-optimize-cost` | 85% | 1 | Stateless, cost-sensitive workloads. Fast scale-up and scale-down (5-minute stabilization windows, 50% step every 2 minutes). |
-| `datadog-optimize-balance` | 70% | 2 | Default for most stateless workloads. Balanced 10-minute stabilization windows, conservative scale-down (20% step every 20 minutes). |
-| `datadog-optimize-performance` | 60% | 3 | Stateful or latency-sensitive workloads. Very conservative scale-down (15-minute stabilization windows, 10% step every 30 minutes). |
+| `datadog-optimize-cost` | 85% | 1 | High CPU utilization target, aggressive scale-down, lowest replica floor. Best for stateless, cost-sensitive workloads. |
+| `datadog-optimize-balance` | 70% | 2 | Moderate utilization target, fast scale-up, balanced scale-down. Best for most stateless workloads. |
+| `datadog-optimize-performance` | 60% | 3 | Conservative utilization target, fast scale-up, slow scale-down, higher replica floor. Best for stateful or critical services. |
 
 To activate a profile on a single workload, add the label to the workload's `metadata.labels`:
 
@@ -515,7 +515,7 @@ spec:
     applyPolicy:
       mode: Apply
       scaleUp:
-        stabilizationWindowSeconds: 300
+        stabilizationWindowSeconds: 190
         rules:
           - type: Percent
             value: 50

content/en/containers/guide/manage-datadogpodautoscaler-with-argocd.md

@@ -287,7 +287,7 @@ autoscaler:
       - type: Percent
         value: 50
         periodSeconds: 120
-    stabilizationWindowSeconds: 600
+    stabilizationWindowSeconds: 130
     strategy: Max
   scaleDown:
     rules:

content/en/containers/guide/manage-datdadogpodautoscaler-with-terraform.md

@@ -318,7 +318,7 @@ resource "kubernetes_manifest" "datadogpodautoscaler_nginx_dka_demo_nginx" {
               "value" = 50
             },
           ]
-          "stabilizationWindowSeconds" = 600
+          "stabilizationWindowSeconds" = 130
           "strategy" = "Max"
         }
         "update" = {