Learning Kubernetes

Alvinditya Saputra included in Documentation

2021-05-24 2155 words 11 minutes

Contents

What is Kubernetes?

Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services, that facilitates both declarative configuration and automation. It has a large, rapidly growing ecosystem. Kubernetes services, support, and tools are widely available.

More information, please follow this link Kubernetes Overview.

Why we need Kubernetes

Containers are a good way to bundle and run your applications. In a production environment, you need to manage the containers that run the applications and ensure that there is no downtime. For example, if a container goes down, another container needs to start. Wouldn’t it be easier if this behavior was handled by a system?

That’s how Kubernetes comes to the rescue! Kubernetes provides you with a framework to run distributed systems resiliently. It takes care of scaling and failover for your application, provides deployment patterns, and more. For example, Kubernetes can easily manage a canary deployment for your system.

Kubernetes can provide with :

Service discovery and load balancing
Storage orchestration
Automated rollouts and rollbacks
Automatic bin packing
Self healing
Secret and configuratio management

For more information please follow this link Why you Need Kubernetes.

Start using Kubernetes

Getting Start with Kubernetes on Docker Desktop

Docker Desktop is the easiest way to run Kubernetes on your local machine - it gives you a fully certified Kubernetes cluster and manages all the components for you.

In this lab you’ll learn how to set up Kubernetes on Docker Desktop and run a simple demo app. You’ll gain experience of working with Kubernetes and comparing the app definition syntax to Docker Compose.

Install Docker Desktop from official website, please follow this link Install Docker Desktop. Docker Desktop is freely available in a community edition, for Windows and Mac.

Enable Kubernetes

Kubernetes itself runs in containers. When you deploy a Kubenetes cluster you first install Docker (or another container runtime like containerd) and then use tools like kubeadm which starts all the Kubernetes components in containers. Docker Desktop does all that for you.

Verify Kubernetes Cluster

If you’ve worked with Docker before, you’re used to managing containers with the docker and docker-compose command lines. Kubernetes uses a different tool called kubectl to manage apps - Docker Desktop installs kubectl for you too.

The cluster can be interacted with using the kubectl CLI. This is the main approach used for managing Kubernetes and the applications running on top of the cluster.

Details of the cluster and its health status is.

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kubectl cluster-info

We should get an output

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Kubernetes control plane is running at https://kubernetes.docker.internal:6443
KubeDNS is running at https://kubernetes.docker.internal:6443/api/v1/namespaces/kube-system/services/kube-dns:dns/proxy

To further debug and diagnose cluster problems, use 'kubectl cluster-info dump'.

To view the nodes in the cluster with.

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kubectl get nodes

We shoulkd get an output

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NAME             STATUS   ROLES    AGE     VERSION
docker-desktop   Ready    master   4d22h   v1.19.7

If the node is marked as NotReady then it is still starting the components.

This command shows all nodes that can be used to host our applications. Now we have only one node, and we can see that it’s status is ready (it is ready to accept applications for deployment).

Deploy Container

With a running Kubernetes cluster, containers can now be deployed.

Using kubectl run, it allows containers to be deployed onto the cluster.

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kubectl create deployment hello-world --image=piinalpin/sample-node-web-app

To check status of the deployment.

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kubectl get pods

We should get an output

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NAME                           READY   STATUS    RESTARTS   AGE
hello-world-6b64556c5b-9pzrp   1/1     Running   0          88s

Once the container is running it can be exposed via different networking options, depending on requirements. One possible solution is NodePort, that provides a dynamic port to a container.

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kubectl expose deployment hello-world --port=8080 --type=NodePort

The command below finds the allocated port and executes a HTTP request.

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export NODE_PORT=$(kubectl get svc hello-world -o go-template='{{range.spec.ports}}{{if .nodePort}}{{.nodePort}}{{"\n"}}{{end}}{{end}}') 
echo "Accessing http://localhost:$NODE_PORT"  
curl http://localhost:$NODE_PORT

We should get an output

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{"status":"success","message":"Hello World! This api from Node.js"}

Kubernetes Dashboard

Deploy latest kubernetes dashboard, you can deploy the dashboard itself with the following single command.

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kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0/aio/deploy/recommended.yaml

If your cluster is working correctly, you should see an output confirming the creation of a bunch of Kubernetes components like in the example below.

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namespace/kubernetes-dashboard created
serviceaccount/kubernetes-dashboard created
service/kubernetes-dashboard created
secret/kubernetes-dashboard-certs created
secret/kubernetes-dashboard-csrf created
secret/kubernetes-dashboard-key-holder created
configmap/kubernetes-dashboard-settings created
role.rbac.authorization.k8s.io/kubernetes-dashboard created
clusterrole.rbac.authorization.k8s.io/kubernetes-dashboard created
rolebinding.rbac.authorization.k8s.io/kubernetes-dashboard created
clusterrolebinding.rbac.authorization.k8s.io/kubernetes-dashboard created
deployment.apps/kubernetes-dashboard created
service/dashboard-metrics-scraper created
deployment.apps/dashboard-metrics-scraper created

Afterwards, you should have two new pods running on your cluster.

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kubectl get pods -A

We should get an output

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NAMESPACE              NAME                                         READY   STATUS    RESTARTS   AGE
...
kubernetes-dashboard   dashboard-metrics-scraper-7b59f7d4df-qkztd   1/1     Running   0          30s
kubernetes-dashboard   kubernetes-dashboard-74d688b6bc-s4595        1/1     Running   0          30s

Running kubectl proxy to accessing the dashbooard, then access this link http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/.

If we get an output

Get token to access dashboard page and paste on authentication page.

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kubectl get secret -n kubernetes-dashboard $(kubectl get serviceaccount default -n kubernetes-dashboard -o jsonpath="{.secrets[0].name}") -o jsonpath="{.data.token}" | base64 --decode

Detail information dashboard please follow Kubernetes.io

Stopping Kubernetes, by type following script

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kubectl delete -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0/aio/deploy/recommended.yaml

We should get an output

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namespace "kubernetes-dashboard" deleted
serviceaccount "kubernetes-dashboard" deleted
service "kubernetes-dashboard" deleted
secret "kubernetes-dashboard-certs" deleted
secret "kubernetes-dashboard-csrf" deleted
secret "kubernetes-dashboard-key-holder" deleted
configmap "kubernetes-dashboard-settings" deleted
role.rbac.authorization.k8s.io "kubernetes-dashboard" deleted
clusterrole.rbac.authorization.k8s.io "kubernetes-dashboard" deleted
rolebinding.rbac.authorization.k8s.io "kubernetes-dashboard" deleted
clusterrolebinding.rbac.authorization.k8s.io "kubernetes-dashboard" deleted
deployment.apps "kubernetes-dashboard" deleted
service "dashboard-metrics-scraper" deleted
deployment.apps "dashboard-metrics-scraper" deleted

Setting Management Script

The steps to deploy or delete the dashboard are not complicated but they can be further simplified.

The following script can be used to start, stop or check the dashboard status.

Create file kubernetes-dashboard.sh

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nano ~/kubernetes-dashboard.sh

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#!/bin/bash
showtoken=1
cmd="kubectl proxy"
count=`ps aux | grep -v "grep" | grep -c "$cmd"`
dashboard_yaml="https://raw.githubusercontent.com/kubernetes/dashboard/v2.0.0/aio/deploy/recommended.yaml"
msgstarted="-e Kubernetes Dashboard \e[92mstarted\e[0m"
msgstopped="Kubernetes Dashboard stopped"

case $1 in
start)
   kubectl apply -f $dashboard_yaml >/dev/null 2>&1

   if [ $count = 0 ]; then
      nohup $cmd >/dev/null 2>&1 &
      echo $msgstarted
   else
      echo "Kubernetes Dashboard already running"
   fi
   ;;

stop)
   showtoken=0
   if [ $count -gt 0 ]; then
      kill -9 $(pgrep -f "$cmd")
   fi
   kubectl delete -f $dashboard_yaml >/dev/null 2>&1
   echo $msgstopped
   ;;

status)
   found=`kubectl get serviceaccount default -n kubernetes-dashboard 2>/dev/null`
   if [[ $count = 0 ]] || [[ $found = "" ]]; then
      showtoken=0
      echo $msgstopped
   else
      found=`kubectl get clusterrolebinding default -n kubernetes-dashboard 2>/dev/null`
      if [[ $found = "" ]]; then
         nopermission=" but user has no permissions."
         echo $msgstarted$nopermission
         echo 'Run "dashboard start" to fix it.'
      else
         echo $msgstarted
      fi
   fi
   ;;
esac

# Show full command line # ps -wfC "$cmd"
if [ $showtoken -gt 0 ]; then
   # Show token
   echo "Admin token:"
   kubectl get secret -n kubernetes-dashboard $(kubectl get serviceaccount default -n kubernetes-dashboard -o jsonpath="{.secrets[0].name}") -o jsonpath="{.data.token}" | base64 --decode
   echo
   echo "Go to:"
   echo "http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/"
fi

Make this script executable

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chmod +x ~/kubernetes-dashboard.sh

Start the dashboard

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./kubernetes-dashboard.sh start

Check whether the dashboard is running or not and output the tokens if currently set.

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./kubernetes-dashboard.sh status

Stop the dashboard

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./kubernetes-dashboard.sh stop

Deploy Container using YAML

Create a kubernetes deployment YAML to tell kubernetes to manage a set of replicas of that Pod — literally, a ReplicaSet — to make sure that a certain number of them are always available. So we might start our Kubernetes Deployment manifest definition YAML deployment.yaml like this:

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---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-world
  labels:
    app: web
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
        - name: hello-world
          image: piinalpin/sample-node-web-app
          ports:
            - containerPort: 8080

kubectl create deployment hello-world
kubectl create 3 replica pods, you can change how many replicas you want
kubectl create deployment container from piinalpin/sample-node-web-app images and expose container port 8080 to master

Run YAML file by type following code

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kubectl apply -f deployment.yaml

Check the deployment list

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kubectl get deployments

We should get an output

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NAME          READY   UP-TO-DATE   AVAILABLE   AGE
hello-world   3/3     3            3           20s

Check pods running

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kubectl get pods

We shoul get an output

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NAME                          READY   STATUS    RESTARTS   AGE
hello-world-f74567869-lsp74   1/1     Running   0          7m7s
hello-world-f74567869-m5vjd   1/1     Running   0          7m7s
hello-world-f74567869-z7pg7   1/1     Running   0          7m7s

There are three replicas created from YAML file.

Create Service using YAML

Create expose deployment YAML file service.yaml like this:

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apiVersion: v1
kind: Service
metadata:
  name: hello-world
  labels:
    app: web
spec:
  selector:
    app: web
  ports:
    - protocol: TCP
      port: 8080
  type: NodePort

kubectl create service name hello-world
kubectl expose deployment which is labeled web
kubectl create connection to port 8080 with type is NodePort

Execute service YAML file by type following code

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kubectl apply -f service.yaml

Check service is running

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kubectl get svc

We should get and output

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NAME          TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)          AGE
hello-world   NodePort    10.107.135.246   <none>        8080:31302/TCP   8s
kubernetes    ClusterIP   10.96.0.1        <none>        443/TCP          5d2h

Check port is exposed and we can execute http request

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curl http://localhost:<EXPOSED_PORT>

We should get an output

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{"status":"success","message":"Hello World! This api from Node.js"}

To delete service and deployment

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kubectl delete -f deployment.yaml
kubectl delete -f service.yaml

Create Deployment and Service on YAML

Create file hello-world.yaml and fill like this:

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---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-world
  labels:
    app: web
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
        - name: hello-world
          image: piinalpin/sample-node-web-app
          ports:
            - containerPort: 8080
---
apiVersion: v1
kind: Service
metadata:
  name: hello-world
  labels:
    app: web
spec:
  selector:
    app: web
  ports:
    - protocol: TCP
      port: 8080
  type: NodePort

Execute service YAML file by type following code

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kubectl apply -f hello-world.yaml

We should get an output

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deployment.apps/hello-world created
service/hello-world created

Check deployment and service is running

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kubectl get deployments
kubectl get pods
kubectl get svc

Check exposed port with http request

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curl http://localhost:<EXPOSED_PORT>

We should get an output

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{"status":"success","message":"Hello World! This api from Node.js"}

Create Deployment, Service and Ingress with Load Balancer YAML

Create file my-kubernetes.yaml and fill like this:

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---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: hello-deployment
  labels:
    app: web
spec:
  replicas: 3
  selector:
    matchLabels:
      app: web
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
        - name: hello-world
          image: gcr.io/google-samples/hello-app:2.0
          env:
          - name: "PORT"
            value: "50000"
        - name: hello-kubernetes
          image: piinalpin/sample-node-web-app
          env:
          - name: "PORT"
            value: "8080"
---
apiVersion: v1
kind: Service
metadata:
  name: hello-service
  labels:
    app: web
spec:
  selector:
    app: web
  ports:
    - name: world-port
      protocol: TCP
      port: 8001
      targetPort: 50000
    - name: kubernetes-port
      protocol: TCP
      port: 8002
      targetPort: 8080
  type: LoadBalancer
---
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: hello-world
spec:
  rules:
    - http:
        paths:
        - path: /hello-world
          pathType: Prefix
          backend:
            service:
              name: hello-service
              port: 
                number: 8001
        - path: /hello-kubernetes
          pathType: Prefix
          backend:
            service:
              name: hello-service
              port: 
                number: 8002

kubectl create deployment hello-deployment
kubectl create 3 replica pods, you can change how many replicas you want
kubectl create deployment container from gcr.io/google-samples/hello-app:2.0 images and expose container port 50000 to master
kubectl create deployment container from piinalpin/sample-node-web-app images and expose container port 8080 to master
kubectl create service name hello-service
kubectl expose deployment which is labeled web
kubectl create port name world-port expose port 50000 to 8001
kubectl create port name kubernetes-port expose port 8080 to 8002
kubectl create type Load Balancer
kubectl create Ingress named hello-world
kubectl expose external IP localhost
kubectl create path /hello-world on port 8001
kubectl create path /hello-kubernetes on port 8002

Thankyou

Docker Labs - Getting Started with Kubernetes on Docker Desktop

kubernetes.io - What is Kubernetes?

KataCoda - Launch Single Node Kubernetes Cluster

Mirantis - Introduction to YAML: Creating a Kubernetes deployment

Network Chuck - you need to learn Kubernetes RIGHT NOW!!

kubernetes.io - Exposing an External IP Address to Access an Application in a Cluster UpCloud - How to deploy Kubernetes Dashboard quickly and easily