Merge pull request #2257 from zroubalik/kedify1

Kedify: Autoscaling HTTP applications on Kubernetes

Author: pareenaverma

content/learning-paths/servers-and-cloud-computing/kedify-http-autoscaling/_index.md

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+---
+title: Autoscaling HTTP applications on Kubernetes
+
+draft: true
+cascade:
+    draft: true
+    
+minutes_to_complete: 45
+
+who_is_this_for: >
+  Developers and SREs running HTTP-based workloads on Kubernetes who want to enable intelligent, event-driven autoscaling.
+
+learning_objectives:
+  - Install Kedify (KEDA build, HTTP Scaler, and Kedify Agent) via Helm
+  - Verify that the components are running in your cluster
+  - Deploy a sample HTTP application and test autoscaling behavior
+
+prerequisites:
+  - A running Kubernetes cluster (local or cloud)
+  - kubectl and helm installed locally
+  - Access to the Kedify Service dashboard (https://dashboard.kedify.io/) to obtain Organization ID and API Key — log in or create an account if you don’t have one
+
+author: Zbynek Roubalik
+
+### Tags
+skilllevels: Introductory
+subjects: Containers and Virtualization
+cloud_service_providers: Any
+armips:
+  - Neoverse
+operatingsystems:
+  - Linux
+tools_software_languages:
+  - Kubernetes
+  - Helm
+  - KEDA
+  - Kedify
+
+further_reading:
+  - resource:
+      title: Kedify HTTP Scaler
+      link: https://kedify.io/scalers/http
+      type: documentation
+  - resource:
+      title: Kedify documentation
+      link: https://docs.kedify.io
+      type: documentation
+  - resource:
+      title: KEDA project
+      link: https://keda.sh/
+      type: documentation
+
+
+### FIXED, DO NOT MODIFY
+# =============================================================================
+weight: 1                       # _index.md always has weight of 1 to order correctly
+layout: "learningpathall"       # All files under learning paths have this same wrapper
+learning_path_main_page: "yes"  # This should be surfaced when looking for related content. Only set for _index.md of learning path content.
+---

content/learning-paths/servers-and-cloud-computing/kedify-http-autoscaling/_next-steps.md

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+---
+# =============================================================================
+#       FIXED, DO NOT MODIFY THIS FILE
+# =============================================================================
+weight: 21                  # Set to always be larger than the content in this path to be at the end of the navigation.
+title: "Next Steps"         # Always the same, html page title.
+layout: "learningpathall"   # All files under learning paths have this same wrapper for Hugo processing.
+---

content/learning-paths/servers-and-cloud-computing/kedify-http-autoscaling/http-scaling.md

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+---
+title: "HTTP Scaling for Ingress-Based Applications"
+weight: 4
+layout: "learningpathall"
+---
+
+Use this section to get a quick, hands-on feel for Kedify HTTP autoscaling. We’ll deploy a small web service, expose it through a standard Kubernetes Ingress, and rely on Kedify’s autowiring to route traffic via its proxy so requests are measured and drive scaling.
+
+Scale a real HTTP app exposed through Kubernetes Ingress using Kedify’s [kedify-http](https://docs.kedify.io/scalers/http-scaler/) scaler. You will deploy a simple app, enable autoscaling with a [ScaledObject](https://keda.sh/docs/latest/concepts/scaling-deployments/), generate load, and observe the system scale out and back in (including scale-to-zero when idle).
+
+## How it works
+
+With ingress autowiring enabled, Kedify automatically routes traffic through its proxy before it reaches your Service/Deployment:
+
+```
+Ingress → kedify-proxy → Service → Deployment
+```
+
+The [Kedify Proxy](https://docs.kedify.io/scalers/http-scaler/#kedify-proxy) gathers request metrics used by the scaler to make decisions.
+
+## What you’ll deploy
+
+- Deployment & Service: an HTTP server with a small response delay to simulate work
+- Ingress: public entry using host `application.keda`
+- ScaledObject: Kedify HTTP scaler with `trafficAutowire: ingress`
+
+## Step 0 — Set up Ingress IP environment variable
+
+Before testing the application, ensure you have the `INGRESS_IP` environment variable set with your ingress controller's external IP or hostname.
+
+If you followed the [Install Ingress Controller](../install-ingress/) guide, you should already have this set. If not, or if you're using an existing ingress controller, run this command:
+
+```bash
+export INGRESS_IP=$(kubectl get service ingress-nginx-controller --namespace=ingress-nginx -o jsonpath='{.status.loadBalancer.ingress[0].ip}{.status.loadBalancer.ingress[0].hostname}')
+echo "Ingress IP/Hostname: $INGRESS_IP"
+```
+You should now have the correct IP address or hostname stored in the `$INGRESS_IP` environment variable. If the command doesn't print any value, please repeat it after some time.
+
+{{% notice Note %}}
+If your ingress controller service has a different name or namespace, adjust the command accordingly. For example, some installations use `nginx-ingress-controller` or place it in a different namespace.
+{{% /notice %}}
+
+## Step 1 — Create the application and Ingress
+
+Let's start with deploying an application that responds to an incoming HTTP server and is exposed via Ingress. You can check the source code of the application on [GitHub](https://github.com/kedify/examples/tree/main/samples/http-server).
+
+#### Deploy the application
+
+Run the following command to deploy our application:
+
+```bash
+cat <<'EOF' | kubectl apply -f -
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: application
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: application
+  template:
+    metadata:
+      labels:
+        app: application
+    spec:
+      nodeSelector:
+        kubernetes.io/arch: arm64
+      tolerations:
+        - key: "kubernetes.io/arch"
+          operator: "Equal"
+          value: "arm64"
+          effect: "NoSchedule"
+      containers:
+        - name: application
+          image: ghcr.io/kedify/sample-http-server:latest
+          imagePullPolicy: Always
+          ports:
+            - name: http
+              containerPort: 8080
+              protocol: TCP
+          env:
+            - name: RESPONSE_DELAY
+              value: "0.3"
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: application-service
+spec:
+  ports:
+    - name: http
+      protocol: TCP
+      port: 8080
+      targetPort: http
+  selector:
+    app: application
+  type: ClusterIP
+---
+apiVersion: networking.k8s.io/v1
+kind: Ingress
+metadata:
+  name: application-ingress
+spec:
+  ingressClassName: nginx
+  rules:
+    - host: application.keda
+      http:
+        paths:
+          - path: /
+            pathType: Prefix
+            backend:
+              service:
+                name: application-service
+                port:
+                  number: 8080
+EOF
+```
+
+Notes:
+- `RESPONSE_DELAY` adds ~300ms latency per request, making scaling effects easier to see.
+- The Ingress uses host `application.keda`. To access this app we will use your ingress controller’s IP with a `Host:` header (shown below).
+
+#### Verify the application is running correctly
+
+Let's check that we have 1 replica of the application deployed and ready:
+
+```bash
+kubectl get deployment application
+```
+
+In the output we should see 1 replica ready:
+```
+NAME          READY   UP-TO-DATE   AVAILABLE   AGE
+application   1/1     1            1           3m44s
+```
+
+#### Test the application
+Hit the app to confirm the app is ready and routing works:
+
+```bash
+curl -I -H "Host: application.keda" http://$INGRESS_IP
+```
+
+You should see similar output:
+```
+HTTP/1.1 200 OK
+Date: Thu, 11 Sep 2025 14:11:24 GMT
+Content-Type: text/html
+Content-Length: 301
+Connection: keep-alive
+```
+
+## Step 2 — Enable autoscaling with Kedify
+
+The application is currectly running, Now we will enable autoscaling on this app, we will scale from 0 to 10 replicas. No request shall be lost at any moment. To do that, please run the following command to deploy our `ScaledObject`:
+
+```bash
+cat <<'EOF' | kubectl apply -f -
+apiVersion: keda.sh/v1alpha1
+kind: ScaledObject
+metadata:
+  name: application
+spec:
+  scaleTargetRef:
+    apiVersion: apps/v1
+    kind: Deployment
+    name: application
+  cooldownPeriod: 5
+  minReplicaCount: 0
+  maxReplicaCount: 10
+  fallback:
+    failureThreshold: 2
+    replicas: 1
+  advanced:
+    restoreToOriginalReplicaCount: true
+    horizontalPodAutoscalerConfig:
+      behavior:
+        scaleDown:
+          stabilizationWindowSeconds: 5
+  triggers:
+    - type: kedify-http
+      metadata:
+        hosts: application.keda
+        pathPrefixes: /
+        service: application-service
+        port: "8080"
+        scalingMetric: requestRate
+        targetValue: "10"
+        granularity: 1s
+        window: 10s
+        trafficAutowire: ingress
+EOF
+```
+
+What the key fields do:
+- `type: kedify-http` — Use Kedify’s HTTP scaler.
+- `hosts`, `pathPrefixes` — Which requests to observe for scaling.
+- `service`, `port` — The Service and port receiving traffic.
+- `scalingMetric: requestRate` and `targetValue: 10` — Target 1000 req/s (per granularity/window) before scaling out.
+- `minReplicaCount: 0` — Allows scale-to-zero when idle.
+- `trafficAutowire: ingress` — Lets Kedify auto-wire your Ingress to the kedify-proxy.
+
+After applying, the ScaledObject will appear in the Kedify dashboard (https://dashboard.kedify.io/).
+
+![Kedify Dashboard With ScaledObject](images/scaledobject.png)
+
+## Step 3 — Send traffic and observe scaling
+
+Becuase we are not sending any traffic to our application, after some time, it should be scaled to zero.
+
+#### Verify scale to zero
+
+Run this command and wait until there is 0 replicas:
+
+```bash
+watch kubectl get deployment application -n default
+```
+
+You should see similar output:
+```bash
+Every 2,0s: kubectl get deployment application -n default
+
+NAME          READY   UP-TO-DATE   AVAILABLE   AGE
+application   0/0     0            0           110s
+```
+
+#### Verify the app can scale from zero
+
+Now, hit the app again, it should be scaled to 1 replica and return back correct response:
+```bash
+curl -I -H "Host: application.keda" http://$INGRESS_IP
+```
+
+You should see a 200 OK response. Next, generate sustained load. You can use `hey` (or a similar tool):
+
+#### Test higher load
+
+```bash
+hey -n 40000 -c 200 -host "application.keda" http://$INGRESS_IP
+```
+
+While the load runs, watch replicas change:
+
+```bash
+watch kubectl get deployment application -n default
+```
+
+For example something like this:
+
+```
+Every 2,0s: kubectl get deployment application -n default
+
+NAME          READY   UP-TO-DATE   AVAILABLE   AGE
+application   5/5     5            5           23m
+```
+
+Expected behavior:
+- On bursty load, Kedify scales the Deployment up toward `maxReplicaCount`.
+- When traffic subsides, replicas scale down. After the cooldown, they can return to zero.
+
+You can also observe traffic and scaling in the Kedify dashboard:
+
+![Kedify Dashboard ScaledObject Detail](images/load.png)
+
+## Clean up
+
+```bash
+kubectl delete scaledobject application
+kubectl delete ingress application-ingress
+kubectl delete service application-service
+kubectl delete deployment application
+```
+
+## Next steps
+
+Explore the official Kedify [How-to guides](https://docs.kedify.io/how-to/) for more configurations such as Gateway API, Istio VirtualService, or OpenShift Routes.
+
+### See also
+
+- Kedify documentation: https://docs.kedify.io