diff --git a/content/en/docs/spin-operator/tutorials/scaling-with-hpa.md b/content/en/docs/spin-operator/tutorials/scaling-with-hpa.md
index 5d369b1..ae670a0 100644
--- a/content/en/docs/spin-operator/tutorials/scaling-with-hpa.md
+++ b/content/en/docs/spin-operator/tutorials/scaling-with-hpa.md
@@ -152,13 +152,51 @@ spec:
           averageUtilization: 50
 ```
 
-<aside>
-☁️ TODO - we need to define which metrics we’re supporting with HPA. Is it the [base set used by containers](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#container-resource-metrics)?
-</aside>
+For more information about HPA, please visit the following links:
+- [Kubernetes Horizontal Pod Autoscaling](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/)
+- [Kubernetes HorizontalPodAutoscaler Walkthrough](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale-walkthrough/)
+- [HPA Container Resource Metrics](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#container-resource-metrics)
 
-The Kubernetes documentation is the place to learn more about [limits and requests](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/#requests-and-limits) and [other metrics supported by HPA](https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/#container-resource-metrics).
+Below is an example of the configuration to scale resources:
 
-Let’s deploy the SpinApp and the HPA instance onto our cluster with the following command:
+```yaml
+apiVersion: core.spinoperator.dev/v1alpha1
+kind: SpinApp
+metadata:
+  name: hpa-spinapp
+spec:
+  image: ghcr.io/spinkube/spin-operator/cpu-load-gen:20240311-163328-g1121986
+  executor: containerd-shim-spin
+  enableAutoscaling: true
+  resources:
+    limits:
+      cpu: 500m
+      memory: 500Mi
+    requests:
+      cpu: 100m
+      memory: 400Mi
+---
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+metadata:
+  name: spinapp-autoscaler
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: hpa-spinapp
+  minReplicas: 1
+  maxReplicas: 10
+  metrics:
+  - type: Resource
+    resource:
+      name: cpu
+      target:
+        type: Utilization
+        averageUtilization: 50
+```
+
+Let’s deploy the SpinApp and the HPA instance onto our cluster (using the above `.yaml` configuration). To apply the above configuration we use the following `kubectl apply` command:
 
 ```console
 # Install SpinApp and HPA
@@ -181,6 +219,8 @@ NAME                 REFERENCE                TARGETS   MINPODS   MAXPODS   REPL
 spinapp-autoscaler   Deployment/hpa-spinapp   6%/50%    1         10        1          97m
 ```
 
+> Please note: The [Kubernetes Plugin for Spin](https://www.spinkube.dev/docs/spin-plugin-kube/installation/) is a tool designed for Kubernetes integration with the Spin command-line interface. The [Kubernetes Plugin for Spin has a scaling tutorial](https://www.spinkube.dev/docs/spin-plugin-kube/tutorials/autoscaler-support/) that demonstrates how to use the `spin kube` command to tell Kubernetes when to scale your Spin application up or down based on demand).
+
 ## Generate Load to Test Autoscale
 
 Now let’s use Bombardier to generate traffic to test how well HPA scales our SpinApp. The following Bombardier command will attempt to establish 40 connections during a period of 3 minutes (or less). If a request is not responded to within 5 seconds that request will timeout: