Kedify tech review

assets/contributors.csv

@@ -103,3 +103,4 @@ Rui Chang,,,,,
 Alejandro Martinez Vicente,Arm,,,,
 Mohamad Najem,Arm,,,,
 Zenon Zhilong Xiu,Arm,,zenon-zhilong-xiu-491bb398,,
+Zbynek Roubalik,Kedify,,,,

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

@@ -7,8 +7,7 @@ cascade:
 
 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.
+who_is_this_for: This is an introductory topic for developers running HTTP-based workloads on Kubernetes who want to enable event-driven autoscaling.
 
 learning_objectives:
   - Install Kedify (KEDA build, HTTP Scaler, and Kedify Agent) via Helm
@@ -18,14 +17,13 @@ learning_objectives:
 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
+  - Access to the Kedify Service dashboard (https://dashboard.kedify.io/) to obtain Organization ID and API Key. You can 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:

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

@@ -4,49 +4,48 @@ 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.
+In this section, you’ll gain hands-on experience with Kedify HTTP autoscaling. You will 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).
+You will 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 application, 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:
 
-```
+```output
 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`
+## Deployment Overview
+  * Deployment & Service: An HTTP server with a small response delay to simulate work
+  * Ingress: Public entry point configured using host `application.keda`
+  * ScaledObject: A Kedify HTTP scaler using `trafficAutowire: ingress`
 
-## Step 0 — Set up Ingress IP environment variable
+## Step 1 — Configure the 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.
+Before testing the application, make sure the INGRESS_IP environment variable is set to your ingress controller’s external IP address 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.
+This will store the correct IP or hostname in the $INGRESS_IP environment variable. If no value is returned, wait a short while and try again.
 
 {{% 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.
+If your ingress controller service uses a different name or namespace, update 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
+## Step 2 — Deploy the application and configure 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).
+Now  you will deploy a simple HTTP server and expose it using an Ingress resource. The source code for this application is available on [GitHub](https://github.com/kedify/examples/tree/main/samples/http-server).
 
 #### Deploy the application
 
-Run the following command to deploy our application:
+Run the following command to deploy your application:
 
 ```bash
 cat <<'EOF' | kubectl apply -f -
@@ -123,37 +122,37 @@ Notes:
 
 #### Verify the application is running correctly
 
-Let's check that we have 1 replica of the application deployed and ready:
+You will now check if you have 1 replica of the application deployed and ready:
 
 ```bash
 kubectl get deployment application
 ```
 
-In the output we should see 1 replica ready:
-```
+In the output you should see 1 replica ready:
+```output
 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:
+Once the application and Ingress are deployed, verify that everything is working correctly by sending a request to the exposed endpoint. Run the following command:
 
 ```bash
 curl -I -H "Host: application.keda" http://$INGRESS_IP
 ```
 
-You should see similar output:
-```
+If the routing is set up properly, you should see a response similar to:
+```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
+## Step 3 — 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`:
+The application is now running. Next,  you will enable autoscaling so that it can scale dynamically between 0 and 10 replicas. Kedify ensures that no requests are dropped during scaling. Apply the `ScaledObject` by running the following command:
 
 ```bash
 cat <<'EOF' | kubectl apply -f -
@@ -193,25 +192,25 @@ spec:
 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.
+Key Fields explained:
+- `type: kedify-http` — Specifies that Kedify’s HTTP scaler should be used.
+- `hosts`, `pathPrefixes` — Define which requests are monitored for scaling decisions.
+- `service`, `port` — TIdentify the Kubernetes Service and port that will receive the traffic.
+- `scalingMetric: requestRate` and `targetValue: 10` — Scale out when request rate exceeds the target threshold (e.g., 1000 req/s per window, depending on configuration granularity).
+- `minReplicaCount: 0` — Enables scale-to-zero when there is no traffic.
+- `trafficAutowire: ingress` — Automatically wires your Ingress to the Kedify proxy for seamless traffic management.
 
-After applying, the ScaledObject will appear in the Kedify dashboard (https://dashboard.kedify.io/).
+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
+## Step 4 — Send traffic and observe scaling
 
-Becuase we are not sending any traffic to our application, after some time, it should be scaled to zero.
+Since no traffic is currently being sent to the application, it will eventually scale down to zero replicas.
 
 #### Verify scale to zero
 
-Run this command and wait until there is 0 replicas:
+To confirm that the application has scaled down, run the following command and watch until the number of replicas reaches 0:
 
 ```bash
 watch kubectl get deployment application -n default
@@ -224,31 +223,35 @@ Every 2,0s: kubectl get deployment application -n default
 NAME          READY   UP-TO-DATE   AVAILABLE   AGE
 application   0/0     0            0           110s
 ```
+This continuously monitors the deployment status in the default namespace. Once traffic stops and the idle window has passed, you should see the application deployment report 0/0 replicas, indicating that it has successfully scaled to zero.
 
 #### Verify the app can scale from zero
 
-Now, hit the app again, it should be scaled to 1 replica and return back correct response:
+Next, test that the application can scale back up from zero when traffic arrives. Send a request to the app:
+
 ```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):
+The application should scale from 0 → 1 replica automatically.
+You should receive an HTTP 200 OK response, confirming that the service is reachable again.
 
 #### Test higher load
 
+Now, generate a heavier, sustained load against the application. You can use `hey` (or a similar benchmarking tool):
+
 ```bash
 hey -n 40000 -c 200 -host "application.keda" http://$INGRESS_IP
 ```
 
-While the load runs, watch replicas change:
+While the load test is running, open another terminal and monitor the deployment replicas in real time:
 
 ```bash
 watch kubectl get deployment application -n default
 ```
 
-For example something like this:
+You will see the number of replicas change dynamically. For example:
 
-```
+```output
 Every 2,0s: kubectl get deployment application -n default
 
 NAME          READY   UP-TO-DATE   AVAILABLE   AGE
@@ -259,23 +262,22 @@ 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:
+You can also monitor traffic and scaling in the Kedify dashboard:
 
 ![Kedify Dashboard ScaledObject Detail](images/load.png)
 
 ## Clean up
 
+When you have finished testing, remove the resources created in this Learning Path to free up your cluster:
+
 ```bash
 kubectl delete scaledobject application
 kubectl delete ingress application-ingress
 kubectl delete service application-service
 kubectl delete deployment application
 ```
+This will delete the `ScaledObject`, Ingress, Service, and Deployment associated with the demo 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
+To go futher, you can explore the Kedify [How-to guides](https://docs.kedify.io/how-to/) for more configurations such as Gateway API, Istio VirtualService, or OpenShift Routes.

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

@@ -4,7 +4,7 @@ weight: 3
 layout: "learningpathall"
 ---
 
-Before deploying HTTP applications with Kedify autoscaling, you need an Ingress Controller to handle incoming traffic. Most major cloud providers (AWS EKS, Google GKE, Azure AKS) do not include an Ingress Controller by default in their managed Kubernetes offerings.
+Before deploying HTTP applications with Kedify autoscaling, you need an Ingress Controller to handle incoming traffic. Most managed Kubernetes services offered by major cloud providers (AWS EKS, Google GKE, Azure AKS) do not include an Ingress Controller by default.
 
 {{% notice Note %}}
 If your cluster already has an Ingress Controller installed and configured, you can skip this step and proceed directly to the [HTTP Scaling guide](../http-scaling/).
@@ -64,13 +64,13 @@ This will save the external IP or hostname in the `INGRESS_IP` environment varia
 
 ## Configure Access
 
-For this tutorial, you have two options:
+To configure access to the ingress controller, you have two options:
 
 ### Option 1: DNS Setup (Recommended for production)
 Point `application.keda` to your ingress controller's external IP/hostname using your DNS provider.
 
 ### Option 2: Host Header (Quick setup)
-Use the external IP/hostname directly with a `Host:` header in your requests. When testing, you'll use:
+Use the external IP/hostname directly with a `Host:` header in your requests. When testing, you will use:
 
 ```bash
 curl -H "Host: application.keda" http://$INGRESS_IP
@@ -80,14 +80,13 @@ The `$INGRESS_IP` environment variable contains the actual external IP or hostna
 
 ## Verification
 
-Test that the ingress controller is working by checking its readiness:
+Verify that the ingress controller is working by checking its readiness:
 
 ```bash
 kubectl get pods --namespace ingress-nginx
 ```
 
 You should see the `ingress-nginx-controller` pod in `Running` status.
 
-## Next Steps
 
-Now that you have an Ingress Controller installed and configured, proceed to the [HTTP Scaling guide](../http-scaling/) to deploy an application and configure Kedify autoscaling.
+Now that you have an Ingress Controller installed and configured, proceed to the next section to deploy an application and configure Kedify autoscaling.

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

@@ -4,17 +4,19 @@ weight: 2
 layout: "learningpathall"
 ---
 
-This page installs Kedify on your cluster using Helm. You’ll add the Kedify chart repo, install KEDA (Kedify build), the HTTP Scaler, and the Kedify Agent, then verify everything is running.
+In this section you will learn how to install Kedify on your Kubernetes cluster using Helm. You will add the Kedify chart repo, install KEDA (Kedify build), the HTTP Scaler, and the Kedify Agent, then verify everything is running.
 
-For more details and all installation methods, see Kedify installation docs: https://docs.kedify.io/installation/helm#installation-on-arm
+For more details and all installation methods on Arm, you can refer to the [Kedify installation docs](https://docs.kedify.io/installation/helm#installation-on-arm)
 
-## Prerequisites
+## Before you begin
 
-- A running Kubernetes cluster (kind, minikube, EKS, GKE, AKS, etc.)
-- kubectl and helm installed and configured to talk to your cluster
-- Kedify Service account (https://dashboard.kedify.io/) to obtain Organization ID and API Key — log in or create an account if you don’t have one
+You will need:
 
-## Prepare installation
+- A running Kubernetes cluster (e.g., kind, minikube, EKS, GKE, AKS, etc.), hosted on any cloud provider or local environment.
+- kubectl and helm installed and configured to communicate with your cluster
+- A Kedify Service account (https://dashboard.kedify.io/) to obtain Organization ID and API Key — log in or create an account if you don’t have one
+
+## Installation
 
 1) Get your Organization ID: In the Kedify dashboard (https://dashboard.kedify.io/) go to Organization -> Details and copy the ID.
 
@@ -25,7 +27,7 @@ For more details and all installation methods, see Kedify installation docs: htt
 kubectl get secret -n keda kedify-agent -o=jsonpath='{.data.apikey}' | base64 --decode
 ```
 
-- Otherwise, in the Kedify dashboard (https://dashboard.kedify.io/) go to Organization -> API Keys, click Create Agent Key, and copy the key.
+Otherwise, in the Kedify dashboard (https://dashboard.kedify.io/) go to Organization -> API Keys, click Create Agent Key, and copy the key.
 
 Note: The API Key is shared across all your Agent installations. If you regenerate it, update existing Agent installs and keep it secret.
 
@@ -40,9 +42,9 @@ helm repo update
 
 ## Helm installation
 
-Most providers like AWS EKS and Azure AKS automatically place pods on ARM nodes when you specify `nodeSelector` for `kubernetes.io/arch=arm64`. However, Google Kubernetes Engine (GKE) applies an explicit taint on ARM nodes, requiring matching `tolerations`.
+Most providers like AWS EKS and Azure AKS automatically place pods on Arm nodes when you specify `nodeSelector` for `kubernetes.io/arch=arm64`. However, Google Kubernetes Engine (GKE) applies an explicit taint on Arm nodes, requiring matching `tolerations`.
 
-To ensure a portable deployment strategy across all cloud providers, we recommend configuring both `nodeSelector` and `tolerations` in your Helm values or CLI flags.
+To ensure a portable deployment strategy across all cloud providers, it is recommended that you configure both `nodeSelector` and `tolerations` in your Helm values or CLI flags.
 
 Install each component into the keda namespace. Replace placeholders where noted.
 
@@ -101,13 +103,15 @@ helm upgrade --install kedify-agent kedifykeda/kedify-agent \
 
 ## Verify installation
 
+You are now ready to verify your installation:
+
 ```bash
 kubectl get pods -n keda
 ```
 
-Expected example (names may differ):
+Expected output should look like (names may differ):
 
-```text
+```output
 NAME                                             READY   STATUS    RESTARTS   AGE
 keda-add-ons-http-external-scaler-xxxxx          1/1     Running   0          1m
 keda-add-ons-http-interceptor-xxxxx              1/1     Running   0          1m
@@ -117,4 +121,4 @@ keda-operator-metrics-apiserver-xxxxx            1/1     Running   0          1m
 kedify-agent-xxxxx                               1/1     Running   0          1m
 ```
 
-Proceed to the next section to deploy a sample HTTP app and test autoscaling.
+Proceed to the next section to learn how to install an Ingress controller before deploying a sample HTTP app and testing autoscaling.