Kubernetes - Deploy Your Application at Scale in K8S

A Hands-On Workshop on Scaling Application on Kubernetes

Note: Prepared for Kubernetes Community Days Kerala 2024.

Table of Contents

Abstract

Dive into the world of Kubernetes with our hands-on guide on deploying your application on a Kubernetes platform. This session will walk you through the fundamental steps, from the initial deployment to exploring and accessing your application. We’ll demystify the process of scaling your app to meet varying demands and guide you through seamless updates to keep your application in sync with the latest enhancements and with insights into Monitoring. Whether you’re a newcomer or looking to brush up on your skills, join us for an interactive journey into the heart of Kubernetes deployment.

Target audience:

Beginners to Kubernetes

Takeaways for the attendee:

Basic understanding on how application can be deployed and scaled on Kubernetes

Prerequisites

1. Kubernetes Cluster

A working Kubernetes Cluster (See other options) - We are using a single node minikube cluster for the demonstration.

2. kubectl

kubectl installed and configured.

3. Sample deployment YAML files

Access to the Demo Repository

4. Enable metrics-server

This command is intended for clusters utilizing minikube. If you’re employing alternative methods in your Kubernetes lab, ensure to use the suitable approach for installing the metric server.

$ minikube addons enable metrics-server
💡  metrics-server is an addon maintained by Kubernetes. For any concerns contact minikube on GitHub.
You can view the list of minikube maintainers at: https://github.com/kubernetes/minikube/blob/master/OWNERS
    ▪ Using image registry.k8s.io/metrics-server/metrics-server:v0.6.4
🌟  The 'metrics-server' addon is enabled

Ensure metrics-server pod is running.

$ kubectl get po -n kube-system | grep metrics-server
metrics-server-7c66d45ddc-22svg    1/1     Running   0             2m1s

5. Get load test tool

You can use any available load testing/benchmarking tools but we are using a simple tool called hey in this workshop.

  • Download the hey package for your operating system.
  • Set executable permission and copy the file to a executable path (eg: ln -s ~/Downloads/hey_linux_amd64 ~/.local/bin/)

Check hey repo for more details.

Exercise 1 - Deploy a simple nginx

Prepare the Application Deployment

Prepare the declarations for deployment and service.

Clone the repo - [iamgini/workshops-demos][https://github.com/iamgini/workshops-demos] - and verify the todo-app.yaml YAML file.

Deploy Application

$ kubectl apply -f nginx.yaml
namespace/webapp created
deployment.apps/nginx-deployment created
service/nginx-nodeport-service created

$ kubectl get po,svc -n webapp
NAME                                    READY   STATUS    RESTARTS   AGE
pod/nginx-deployment-57c9fb648d-km4rv   1/1     Running   0          3m44s

NAME                             TYPE       CLUSTER-IP      EXTERNAL-IP   PORT(S)          AGE
service/nginx-nodeport-service   NodePort   10.111.52.104   <none>        8080:30442/TCP   3m44s

Note: you can also expose the application using imperative commands as follows. For the demonstration purpose we are using the YAMLs.

$ kubectl expose deployment wordpress --type=NodePort --port=8082

Verify application

Feel free to employ any service type; however, for this instance, we’re utilizing the NodePort service. Obtain the NodePort of the application service with the provided command. Note that this is specific to minikube-based clusters; refer to alternative documentation for other Kubernetes cluster setups.

$ minikube service --url nginx-nodeport-service -n webapp
http://192.168.49.2:30442
  • nginx-nodeport-service - the service name (refer to nginx.yaml)
  • -n webapp - the namespace
  • http://192.168.49.2:30442 - the application url returned by the command.

You can verify the application access using the returned URL via CLI (curl) or from a Web browser.

$  curl http://192.168.49.2:30442

Refer to How to access applications deployed in minikube Kubernetes cluster using NodePort to learn more.

Scaling Manually

kubectl scale deployment nginx-deployment -n webapp --replicas 3

Create HorizontalPodAutoscaler

$ kubectl autoscale deployment nginx-deployment --cpu-percent=80 --min=1 --max=5 -n webapp
horizontalpodautoscaler.autoscaling/nginx-deployment autoscaled
  • Targets the nginx-deployment for autoscaling.
  • Scales based on CPU usage, aiming for 80% utilization.
  • Allows replicas to scale between 1 and 5.
$ kubectl get hpa -n webapp
NAME               REFERENCE                     TARGETS   MINPODS   MAXPODS   REPLICAS   AGE
nginx-deployment   Deployment/nginx-deployment   0%/80%    1         5         1          57s

Increase the application load

$ hey -z 4m -c 15 http://192.168.49.2:<PORT>
  • Runs for 4 minutes (-z 4m) to sustain load for a longer period.
  • Uses 15 concurrent connections (-c 15) to generate higher load, aiming to push CPU usage closer to 80%.

Check Pods and load

$ watch kubectl top pods  webapp

Every 2.0s: kubectl top pods -n webapp  gmadappa: Sat Jan 13 12:42:33 2024

NAME                                CPU(cores)   MEMORY(bytes)
nginx-deployment-57c9fb648d-6c4gf   240m         10Mi
nginx-deployment-57c9fb648d-94dzt   261m         10Mi
nginx-deployment-57c9fb648d-gm576   225m         10Mi
nginx-deployment-57c9fb648d-gsp8x   254m         10Mi
nginx-deployment-57c9fb648d-rhgrm   232m         10Mi

$ watch kubectl get po -n webapp

Every 2.0s: kubectl get po -n webapp                               iamgini: Sat Jan 13 12:42:17 2024

NAME                                READY   STATUS    RESTARTS   AGE
nginx-deployment-57c9fb648d-6c4gf   1/1     Running   0          2m53s
nginx-deployment-57c9fb648d-94dzt   1/1     Running   0          3m53s
nginx-deployment-57c9fb648d-gm576   1/1     Running   0          113s
nginx-deployment-57c9fb648d-gsp8x   1/1     Running   0          21m
nginx-deployment-57c9fb648d-rhgrm   1/1     Running   0          2m53s

Clean up

Remove the resources and namespace from cluster as part of housekeeping

$ kubectl delete -f nginx.yaml
namespace "webapp" deleted
deployment.apps "nginx-deployment" deleted
service "nginx-nodeport-service" deleted

Exercise 2 - Deploy a Todo app

Prepare the Application Deployment

Prepare the declarations for deployment and service.

Clone the repo - [iamgini/workshops-demos][https://github.com/iamgini/workshops-demos] - and verify the todo-app.yaml YAML file.

Deploy Application

$ kubectl apply -f todo-app.yaml
namespace/todo created
deployment.apps/todo-app created
service/todo-app created

Verify application

$ minikube service --url todo-app -n todo
http://192.168.49.2:31680

Create HorizontalPodAutoscaler

$ kubectl autoscale deployment todo-app --cpu-percent=80 --min=1 --max=5 -n todo
horizontalpodautoscaler.autoscaling/todo-app autoscaled


$ kubectl get hpa -n todo
NAME       REFERENCE             TARGETS         MINPODS   MAXPODS   REPLICAS   AGE
todo-app   Deployment/todo-app   <unknown>/80%   1         5         1          59s

Increase the application load

$ hey -z 4m -c 15 http://192.168.49.2:<PORT>

Check Pods and load

$ watch "kubectl get all -n todo;kubectl top pods -n todo"

Clean up

Remove the resources and namespace from cluster as part of housekeeping

$ kubectl delete -f todo-app.yaml
namespace "todo" deleted
deployment.apps "todo-app" deleted
service "todo-app" deleted

Exercise 3 - Deploy a WordPress site (2 tier)

Prepare the Application Deployment

Prepare the declarations for deployment and service.

Clone the repo - [iamgini/workshops-demos][https://github.com/iamgini/workshops-demos] - and verify the todo-app.yaml YAML file.

Deploy Application

$ kubectl apply -f todo-app.yaml
namespace/todo created
deployment.apps/todo-app created
service/todo-app created

Verify application

$ minikube service --url wordpress-app -n wordpress
http://192.168.49.2:31680

Create HorizontalPodAutoscaler

$ kubectl autoscale deployment wordpress-deployment --cpu-percent=80 --min=1 --max=5 -n wordpress

Increase the application load

$ hey -z 4m -c 10 http://192.168.49.2:<PORT>

Check Pods and load

$ watch "kubectl get all -n wordpress;kubectl top pods -n wordpress"

Clean up

Remove the resources and namespace from cluster as part of housekeeping

$ kubectl delete -f wordpress.yaml

References & Resources

Building a Kubernetes Cluster

You can try one or many (We suggest to try all if possible) methods to create your own Kubernetes cluster for learning and practicing.

Simple HPA with CPU and Memory metrics

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: nginx-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: nginx-deployment
  minReplicas: 1
  maxReplicas: 5
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 50
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 60

Advanced HPA with custom metrics:

apiVersion: autoscaling/v2beta2
kind: HorizontalPodAutoscaler
metadata:
  name: nginx-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: nginx-deployment
  minReplicas: 1
  maxReplicas: 5
  metrics:
  - type: Pods
    pods:
      metricName: nginx-request-count
      target:
        type: AverageValue
        averageValue: 100