Finalize first draft

Author: mocdaniel

content/en/docs/concepts/workloads/autoscaling.md

@@ -32,11 +32,6 @@ See below for examples of both strategies.
 - **Horizontal scaling**: [Running multiple instances of your app](/docs/tutorials/kubernetes-basics/scale/scale-intro/)
 - **Vertical scaling**: [Resizing CPU and memory resources assigned to containers](/docs/tasks/configure-pod-container/resize-container-resources)
 
-{{< note >}}
-Resizing a workload in-place **without** restarting the {{< glossary_tooltip text="Pods" term_id="pod" >}}
-or its {{< glossary_tooltip text="Containers" term_id="container" >}} requires Kubernetes version 1.27 or later.
-{{< /note >}}
-
 ## Scaling workloads automatically
 
 Kubernetes also supports _automatic scaling_ of workloads, which is the focus of this page.
@@ -57,6 +52,8 @@ There is a [walkthrough tutorial](/docs/tasks/run-application/horizontal-pod-aut
 
 ### Scaling workloads vertically
 
+{{< feature-state for_k8s_version="v1.25" state="stable" >}}
+
 You can automatically scale a workload vertically using a _VerticalPodAutoscaler_ (VPA).
 Different to the HPA, the VPA doesn't come with Kubernetes by default, but is a separate project
 that can be found [on GitHub](https://github.com/kubernetes/autoscaler/tree/9f87b78df0f1d6e142234bb32e8acbd71295585a/vertical-pod-autoscaler).
@@ -65,12 +62,11 @@ Once installed, it allows you to create {{< glossary_tooltip text="CustomResourc
 (CRDs) for your workloads which define _how_ and _when_ to scale the resources of the managed replicas.
 
 {{< note >}}
-The current default version of the HPA (**v0.14.0**) requires **Kubernetes version 1.25** or later.
-You will also need to have the [Metrics Server](https://github.com/kubernetes-sigs/metrics-server)
-installed to your cluster.
+You will need to have the [Metrics Server](https://github.com/kubernetes-sigs/metrics-server)
+installed to your cluster for the HPA to work.
 {{< /note >}}
 
-At the moment, the VPA operates can operate in four different modes:
+At the moment, the VPA can operate in four different modes:
 
 {{< table caption="Different modes of the VPA" >}}
 Mode | Description
@@ -81,14 +77,25 @@ Mode | Description
 `Off` | The VPA does not automatically change the resource requirements of the pods. The recommendations are calculated and can be inspected in the VPA object.
 {{< /table >}}
 
+#### Requirements for in-place resizing
+
+{{< feature-state for_k8s_version="v1.27" state="alpha" >}}
+
+Resizing a workload in-place **without** restarting the {{< glossary_tooltip text="Pods" term_id="pod" >}}
+or its {{< glossary_tooltip text="Containers" term_id="container" >}} requires Kubernetes version 1.27 or later.<br />
+Additionally, the `InPlaceVerticalScaling` feature gate needs to be enabled.
+
+{{< feature-gate-description name="InPlacePodVerticalScaling" >}}
+
 ### Autoscaling based on cluster size
 
 For workloads that need to be scaled based on the size of the cluster (for example
 `cluster-dns` or other system components), you can use the _Cluster Proportional Autoscaler_.<br />
 Just like the VPA, it is not part of the Kubernetes core, but hosted in its
 own repository [on GitHub](https://github.com/kubernetes-sigs/cluster-proportional-autoscaler).
 
-The Cluster Proportional Autoscaler watches the number of schedulable {{< glossary_tooltip text="nodes" term_id="node" >}} and cores and scales the number of replicas of the target workload accordingly.
+The Cluster Proportional Autoscaler watches the number of schedulable {{< glossary_tooltip text="nodes" term_id="node" >}}
+and cores and scales the number of replicas of the target workload accordingly.
 
 ### Event driven Autoscaling
 
@@ -101,20 +108,30 @@ a wide range of adapters for different event sources to choose from.
 
 ### Autoscaling based on schedules
 
-_tbd_
+Another strategy for scaling your workloads is to **schedule** the scaling operations, for example in order to
+reduce resource consumption during off-peak hours.
+
+Similar to event driven autoscaling, such behavior can be achieved using KEDA in conjunction with
+its [`Cron` scaler](https://keda.sh/docs/2.13/scalers/cron/). The `Cron` scaler allows you to define schedules
+(and time zones) for scaling your workloads in or out.
 
 ## Scaling cluster infrastructure
 
-_tbd_, short summary
+If scaling workloads isn't enough to meet your needs, you can also scale your cluster infrastructure itself.
+
+Scaling the cluster infrastructure normally means adding or removing {{< glossary_tooltip text="nodes" term_id="node" >}}.
+This can be done using one of two available autoscalers:
 
-## Third-party Autoscalers
+- [**Cluster Autoscaler**](https://github.com/kubernetes/autoscaler/tree/master/cluster-autoscaler)
+- [**Karpenter**](https://github.com/kubernetes-sigs/karpenter?tab=readme-ov-file)
 
-_tbd_, short summary of KEDA and KNative autoscalers
+Both scalers work by watching for pods marked as _unschedulable_ or _underutilized_ nodes and then adding or
+removing nodes as needed.
 
 ## {{% heading "whatsnext" %}}
 
-- item 1
-- item 2
-  - subitem 1
-  - subitem 2
-- item 3
+- Learn more about scaling horizontally
+  - [Scale a StatefulSet](/docs/tasks/run-application/scale-stateful-set/)
+  - [HorizontalPodAutoscaler Walkthrough](/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/)
+- [Resize Container Resources In-Place](/docs/tasks/configure-pod-container/resize-container-resources/)
+- [Autoscale the DNS Service in a Cluster](/docs/tasks/administer-cluster/dns-horizontal-autoscaling/)