Install kubectl on Ubuntu Instance | How to install kubectl in Ubuntu | Install and Set Up kubectl on Linux

Kubernetes uses a command line utility called kubectl for communicating with the cluster API server. It is tool for controlling Kubernetes clusters. 

The Kubernetes command-line tool, kubectl, allows you to run commands against Kubernetes clusters. You can use kubectl to deploy applications, inspect and manage cluster resources, and view logs. 

kubectl looks for a file named config in the $HOME directory.

How to install Kubectl in Ubuntu instance

Install kubectl binary with curl on Linux

curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"

Install kubectl

sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

Verify if kubectl got installed

kubectl version --short --client

Install kubectl on Ubuntu Instance | How to install kubectl in Ubuntu | Install kubectl on Linux Instance

Kubernetes uses a command line utility called kubectl for communicating with the cluster API server. It is tool for controlling Kubernetes clusters. kubectl looks for a file named config in the $HOME directory.

sudo curl --silent --location -o /usr/local/bin/kubectl   https://s3.us-west-2.amazonaws.com/amazon-eks/1.22.6/2022-03-09/bin/linux/amd64/kubectl

sudo chmod +x /usr/local/bin/kubectl 

Verify if kubectl got installed

kubectl version --short --client

Install kubectl on Mac OS | How to install kubectl in MAC OS

Kubernetes uses a command line utility called kubectl for communicating with the cluster API server. It is tool for controlling Kubernetes clusters.  

Kubectl is installable on a variety of Linux platforms, macOS and Windows.

How to install Kubectl in MAC OS

Kubectl can be installed in Mac OS by using Homebrew:

Run the update first and install

brew update && brew install kubectl 
or 
brew install kubernetes-cli

To check the version of Kubernetes CLI

kubectl version --client

=

Deploy Python App into Kubernetes Cluster using kubectl Jenkins Pipeline | Containerize Python App and Deploy into AKS Cluster | Kubectl Deployment using Jenkins

We will learn how to automate Docker builds using Jenkins and Deploy into Kubernetes Cluster(AKS) in Azure Cloud. We will use kubectl command to deploy Docker images into AKS cluster. We will use Python based application. I have already created a repo with source code + Dockerfile. The repo also have Jenkinsfile for automating the following:

- Automating builds using Jenkins
- Automating Docker image creation
- Automating Docker image upload into Docker registry
- Automating Deployments to Kubernetes Cluster using kubectl CLI plug-in

 

 

Pre-requistes:
1. AKS Cluster is setup and running. Click here to learn how to create AKS cluster.

2. Jenkins Master is up and running.
3. Docker, Docker pipeline and Kubectl CLI plug-ins are installed in Jenkins

5. Azure container registry is setup in https://portal.azure.com

Step #1 - Create Credentials for Acure Container Registry

Go to Jenkins UI, click on Credentials -->

Click on Global credentials

Click on Add Credentials

Now Create an entry for connecting to ACR. Make sure you enter the ID as ACR

Step #3 - Create Credentials entry for AKS Cluster

Click on Add Credentials, use Kubernetes configuration from drop down.

execute the below command to get kubeconfig info, copy the entire content of the file:

sudo cat ~/.kube/config

Enter ID as K8S and choose enter directly and paste the above file content and save.

Step # 4 - Create a pipeline in Jenkins

Create a new pipeline job.

Step # 5 - Copy the pipeline code from below
Make sure you change red highlighted values below:
Your docker user id should be updated.
your registry credentials ID from Jenkins from step # 1 should be copied

Step # 6 - Build the pipeline

Once you create the pipeline and changes values per your Docker user id and credentials ID, click on 

Step # 7 - Verify deployments to K8S

kubectl get pods

kubectl get deployments

kubectl get services

Steps # 8 - Access Python App in K8S cluster

Once build is successful, go to browser and enter master or worker node public ip address along with port number mentioned above

http://master_or_worker_node_public_ipaddress:port_no_from_above

You should see page like below:

Please watch the above steps in YouTube channel:

Deploy Python App into Kubernetes Cluster using kubectl in Jenkins Pipeline | Containerize Python App and Deploy into Kubernetes Cluster

 We will learn how to automate Docker builds using Jenkins and Deploy into Kubernetes Cluster. We will use Python based application. I have already created a repo with source code + Dockerfile. The repo also have Jenkinsfile for automating the following:

- Automating builds using Jenkins
- Automating Docker image creation
- Automating Docker image upload into Docker registry
- Automating Deployments to Kubernetes Cluster

 

Pre-requisites:
1. Jenkins Master is up and running. 

2. Spin up Jenkins slave, install docker in it. Install kubectl on Slave.
3. Docker, Docker pipeline and Kubernetes Deploy plug-ins are installed in Jenkins

4. Docker hub account setup in https://cloud.docker.com

5. Kubernetes Cluster is setup and running.

Step #1 - Login to Jenkins slave instance through command line - Install Docker

sudo apt install docker.io -y

 

Add Jenkins to Docker Group
sudo usermod -aG docker jenkins
sudo systemctl daemon-reload

 

Restart Docker service

sudo systemctl start docker

sudo systemctl enable docker
sudo systemctl restart docker

Restart Jenkins service

sudo service jenkins restart

 

Install kubectl command on Jenkins slave.

Step #2 - Create Credentials for Docker Hub

Go to Jenkins UI, click on Credentials -->

Click on Global credentials

Click on Add Credentials

Now Create an entry for your Docker Hub account. Make sure you enter the ID as dockerhub

Step #3 - Create Credentials for Kubernetes Cluster

execute the below command to get kubeconfig info, copy the entire content of the file:

sudo cat ~/.kube/config

Go to Jenkins, Manage Jenkins, Click on Add Credentials, use Kubernetes configuration from drop down.

Enter ID as kubeconfig_raw and upload kubeconfig file

 Click on browse

 

Upload kube config and enter id as ID kubeconfig-raw

Step # 4 - Create a pipeline in Jenkins

Create a new pipeline job.

Step # 5 - Copy the pipeline code from below
Make sure you change red highlighted values below:
Your docker user id should be updated.
your registry credentials ID from Jenkins from step # 1 should be copied

pipeline {

     agent {
         label 'myslave'
     }
        environment {
        //once you sign up for Docker hub, use that user_id here
        registry = "your_docker_hub_user_id/mypython-app"
        //- update your credentials ID after creating credentials for connecting to Docker Hub
        registryCredential = 'dockerhub'
        dockerImage = ''
    }
    stages {

        stage ('checkout') {
            steps {
            checkout([$class: 'GitSCM', branches: [[name: '*/master']], doGenerateSubmoduleConfigurations: false, extensions: [], submoduleCfg: [], userRemoteConfigs: [[url: 'https://github.com/akannan1087/myPythonDockerRepo']]])
            }
        }
       
        stage ('Build docker image') {
            steps {
                script {
                dockerImage = docker.build registry
                }
            }
        }
       
         // Uploading Docker images into Docker Hub
    stage('Upload Image') {
     steps{   
         script {
            docker.withRegistry( '', registryCredential ) {
            dockerImage.push()
            }
        }
      }
    }
   
       stage('K8S Deploy') {
        steps{   
            script {
                withKubeConfig([credentialsId: 'kubeconfig-raw', serverUrl: '']) {
                sh ('kubectl apply -f k8s-deployment.yaml')
                }
            }
        }
       }
  
    }  
}

Step # 6 - Build the pipeline

Once you create the pipeline and changes values per your Docker user id and credentials ID, click on 

Step # 7 - Verify deployments to K8S

kubectl get pods

kubectl get deployments

kubectl get services

Steps # 8 - Access Python App in K8S cluster

Once build is successful, go to browser and enter master or worker node public ip address along with port number mentioned above

http://master_or_worker_node_public_ipaddress:port_no_from_above

You should see page like below: