This is a PoC for test the KEDA component in a mock cluster with the objective of improve the latency time in a traffic surge.

In this demo we use Locust for make a load test and simulate a common traffic surge in the ingress controller (ingress-nginx), for more details of how works KEDA internally please visit your official site.

Getting started

Requirements

• kind
• terraform
• kubectl

Installation

1. Create a new cluster of k8s with kind

❯ kind create cluster
Creating cluster "kind" ...
 ✓ Ensuring node image (kindest/node:v1.21.1) 🖼
 ✓ Preparing nodes 📦
 ✓ Writing configuration 📜
 ✓ Starting control-plane 🕹️
 ✓ Installing CNI 🔌
 ✓ Installing StorageClass 💾
Set kubectl context to "kind-kind"
You can now use your cluster with:

kubectl cluster-info --context kind-kind

Have a nice day! 👋

❯ kubectl config use-context kind-kind

Make sure that the Kubernetes node is ready:

❯ kubectl get nodes
NAME                 STATUS   ROLES                  AGE     VERSION
kind-control-plane   Ready    control-plane,master   3m25s   v1.21.1

And that system pods are running happily:

❯ kubectl -n kube-system get pods
NAME                                         READY   STATUS    RESTARTS   AGE
coredns-558bd4d5db-thwvj                     1/1     Running   0          3m39s
coredns-558bd4d5db-w85ks                     1/1     Running   0          3m39s
etcd-kind-control-plane                      1/1     Running   0          3m56s
kindnet-84slq                                1/1     Running   0          3m40s
kube-apiserver-kind-control-plane            1/1     Running   0          3m54s
kube-controller-manager-kind-control-plane   1/1     Running   0          3m56s
kube-proxy-4h6sj                             1/1     Running   0          3m40s
kube-scheduler-kind-control-plane            1/1     Running   0          3m54s

2. Run terraform for install keda helm chart

❯ make apply

3. Verify of all deployments is working correctly

Create a port-forward of ingress nginx service

❯ kubectl port-forward service/nginx-ingress-nginx-ingress -n ingress-nginx 8080:80

Make a simple curl for check if the app response with a HTTP 200

❯ curl hello-app.local:8080 --resolve hello-app.local:8080:127.0.0.1

Keda ScaledObject

Now, in your cluster you can see a new Object of KEDA and these autoscaling the hello-app deployment throught metrics of nginx controller (active_connections)

apiVersion: keda.sh/v1alpha1
kind: ScaledObject
metadata:
  name: {{ include "chart.fullname" . }}
  labels:
    {{- include "chart.labels" . | nindent 4 }}
spec:
  scaleTargetRef:
    kind: Deployment
    name: {{ include "chart.fullname" . }}
  minReplicaCount: 1
  maxReplicaCount: 20
  cooldownPeriod: 30
  pollingInterval: 1
  triggers:
  - type: prometheus
    metadata:
      serverAddress: http://prometheus-server.prometheus.svc.cluster.local
      metricName: nginx_connections_active_keda
      query: |
        sum(avg_over_time(nginx_ingress_nginx_connections_active{app="nginx-ingress-nginx-ingress"}[1m]))
      threshold: "100"

Simulate traffic surge with Locust

Deploy Locust with the next command

❯ kubectl apply -f locust/locust.yaml 

Now create a port-forward and then you can access in your browser with http://localhost:7070

❯ kubectl port-forward service/locust -n default 7070:8089 

Return to the Locust server in your browser. Enter the following values in the fields and click the Start swarming button:

• Number of users – 500
• Spawn rate – 100
• Host – http://nginx-ingress-nginx-ingress.ingress-nginx.svc.cluster.local

Now you can see how KEDA and HPA start to autoscaling the nginx pods with a better way for attend the traffic surge with a minor latency vs the traditional way.

Documentation

1. Keda Official Docs
2. NGINX Tutorial: Reduce Kubernetes Latency with Autoscaling

How contribute? 🚀

Please feel free to contribute to this project, please fork the repository and make a pull request!. ❤️

Share the Love ❤️

Like this project? Please give it a ★ on this GitHub! (it helps me a lot).

License

See LICENSE for full details.

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regarding copyright ownership.  The ASF licenses this file
to you under the Apache License, Version 2.0 (the
"License"); you may not use this file except in compliance
with the License.  You may obtain a copy of the License at

  https://www.apache.org/licenses/LICENSE-2.0

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