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August 6, 2020 | By: Luke Ashe-Brown

Tutorial: Deploy Your First Kubernetes Cluster

    Tutorial: Deploy Your First Kubernetes Cluster

    Maybe you’ve heard of Kubernetes but haven’t explored it any further or you’ve done a bit of research but have yet to test the waters of what it can do. Either way, this step-by-step guide will walk you through setting up a Kubernetes cluster on your own computer and deploy a simple application into the cluster.

    Setting up a local Kubernetes cluster is incredibly simple these days, thanks to the wide availability of tools like Minikube, Mikrok8s, Kind etc… Throughout this tutorial we’ll use kind because it’s the fastest to set up with minimal dependencies, as long as you are able to run Docker on your machine.

    To make things easier for yourself, you can clone the examples within the tutorial in our public git repository: Kubernetes Hello World.

    KIND set-up

    Docker

    To get kind working, you need to have Docker installed. On Linux it's best to use your operating system package manager, apt on ubuntu or debian, yum or dnf on Fedora/Centos/RHEL and pacman or yay on Archlinux. On Mac or Windows, use the instructions for your platform from Docker's documentation.

    Kubectl

    You will also need the kubectl command to interact with the cluster once it's up and running. On Linux, kubectl install instructions are available, including methods to install it, with your Linux distributions' packages manager. But it can be installed easily by using the following commands:

    curl -LO https://storage.googleapis.com/kubernetes-release/release/`curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt` /bin/linux/amd64/kubectl
    chmod +x ./kubectl

    On a Mac, it should be easy if you use the brew package manager by running brew install kubectl. Further instructions for MacOs are available in Kubernetes MacOs kubectl installation instructions

    On Windows, of course, instructions are also available on the Kubernetes kubectl installation instructions page.

    KIND

    Finally, you will need to get the kind command.

    On Linux or Mac you can install it from the Github releases page, much like the kubectl binary, with these commands:

    curl -L https://github.com/kubernetes-sigs/kind/releases/download/v0.8.1/kind-linux-amd64 -o kind
    chmod +x ./kind
    sudo mv ./kind /usr/local/bin/kind

    On a Mac, alternatively it can be installed easily using the brew command again, with:

    brew install kind

    With Windows, either use curl if you have it available...

    curl.exe -Lo kind-windows-amd64.exe https://kind.sigs.k8s.io/dl/v0.8.1/kind-windows-amd64
    Move-Item .\kind-windows-amd64.exe c:\some-dir-in-your-PATH\kind.exe

     

    ... or use the Chocolatey package manager for Windows:

    choco install kind

    For full up to date instructions on any of these kind installation methods, see the projects Quick Start Guide.

     

    Creating your cluster

    Once all these components are installed, you're ready to create your local Kubernetes cluster.

    Kind deploys a Kubernetes instance in a Docker container. If you have other containers running on your system, it's best to stop them as they may conflict with the ports used in this example.

    docker ps will show you any containers that are running already. If you have any,  you can stop them all at once using:

    docker stop $(docker ps -a -q)

    First, we need a little configuration to prepare our new Kubernetes node. Make a file as below:

    # Save this to 'kind.config.yaml'

    kind: Cluster
    apiVersion: kind.sigs.k8s.io/v1alpha3
    nodes:
    - role: control-plane
    extraPortMappings:
    - containerPort: 30080
    hostPort: 80
    listenAddress: "0.0.0.0"
    protocol: TCP

    The extra port mapping is required to allow us to talk to the webserver we will run later on.

    kind create cluster --name mycluster --config config/kind.config.yaml --wait 5m

    It only takes a few minutes, and after this runs you should see a friendly message telling you your cluster is ready.

    image created cluster

    As the output says, the cluster is up and your kubectl command configuration is already set to talk to the cluster.

    Deploy an application

    Now that the cluster is up and running, we can run a process. In this example, we'll run a simple webserver with a "hello world" message of our own creation.

    Kubernetes describes all workloads through a simple yaml format file called a "manifest". So, to set up something on the cluster we need to write a yaml file to describe what we want to run.

    All the manifests for this example deployment can be found in the repository under the manifests folder.

    First, let's describe a workload deployment:

    apiVersion: apps/v1
    kind: Deployment
    metadata:
    labels:
    app: example1
    name: example1
    spec:
    replicas: 1
    selector:
    matchLabels:
    app: example1
    template:
    metadata:
    labels:
    app: example1
    spec:
    containers:
    - image: nginx:latest
    name: nginx

    Write this into a yaml file, or use the file from the Github repository, and use the kubectl command to apply the workload definition.

    kubectl apply -f manifests/1_helloworld_deploy.yaml

    This will deploy the nginx docker container and run it as a process on the cluster. Confirm it's running by looking at the resulting pod that's running, kubectl get pods. You should see output that looks like the following: 

    NAME                        READY   STATUS    RESTARTS   AGE
    example1-7466b89f7c-cs4cc 1/1 Running 0 14s

    If the "STATUS" field says "Running" it's working as expected.

    So, what actually happened?

    When you create a deployment in Kubernetes, the number of replicas you want is set in the manifest, each replica is a copy of the containers that are in the spec. This running instance is actually in an object called a 'Pod'. A Pod is one or more containers running in a logical group. This allows for a number of useful arrangements, like using multiple processes to deal with processing batch jobs, shipping logs or metrics, or a process called "initContainers" that runs once to help set up the 'Pod' for operation.

    In this instance, we're just running the container for nginx on its own, with no need for any more. The Pod contains our single nginx instance as we intended. We can see the logs of the container as if it were running locally using the following command:

    kubectl logs example1-7466b89f7c-cs4cc

    You will have to get the id of the running pod from the command above, as this is dynamic and will be specific to your instance. But then you should see logs like below:

    /docker-entrypoint.sh: /docker-entrypoint.d/ is not empty, will attempt to perform configuration
    /docker-entrypoint.sh: Looking for shell scripts in /docker-entrypoint.d/
    /docker-entrypoint.sh: Launching /docker-entrypoint.d/10-listen-on-ipv6-by-default.sh
    10-listen-on-ipv6-by-default.sh: Getting the checksum of /etc/nginx/conf.d/default.conf
    10-listen-on-ipv6-by-default.sh: Enabled listen on IPv6 in /etc/nginx/conf.d/default.conf
    /docker-entrypoint.sh: Launching /docker-entrypoint.d/20-envsubst-on-templates.sh
    /docker-entrypoint.sh: Configuration complete; ready for start up

    These logs show scripts that run when the container starts up, we will re-visit this later when we've visited our homepage, to see the log entries show up.

    Expose the service

    The process is running, so how do we visit the page? Kubernetes offers a powerful service layer to route connections to containers it runs. When you run your Pod, you need to specify the ports that it will map onto your container. Then you create a Kubernetes resource called a 'Service' that will direct requests to processes running in your Pods.

    How do you do this? First let's add the port definitions to the Deployment Pod specification. Replace the spec block from your yaml file with the lines below:

        spec:
    containers:
    - image: nginx:latest
    name: nginx
    ports:
    - containerPort: 80
    name: nginx

    Then, apply this file as you did before. For convenience in the git repository we have an example of the file:

    kubectl apply -f manifests/2_helloworld_deploy_ports.yaml

    To see the change happen, you may be able to see the Pod be replaced if you are quick enough. run kubectl get pods and you may see something like:

    NAME                        READY   STATUS        RESTARTS   AGE
    example1-7466b89f7c-cs4cc 1/1 Terminating 0 13h
    example1-9f8f59464-x9ntp 1/1 Running 0 2s

    The 'Terminating' instance may be visible for a very short time, otherwise you will just see the new Pod already running without the old Pod in Terminating state. This is how deployments are updated in Kubernetes, allowing for rolling upgrades of configuration or container versions.

    Now that the Pod is set up to receive requests on the port we want, we need to create the Service. We'll use the generally preferred method, create a service defined in a yaml file, which should look like this:

    apiVersion: v1
    kind: Service
    metadata:
    name: example1
    labels:
    app: example1
    spec:
    type: NodePort
    selector:
    app: example1
    ports:
    - protocol: TCP
    targetPort: 80
    port: 80
    nodePort: 30080

    Again, an example is provided in the GitHub repository, so you can apply the example manifest or your own file like so:

    kubectl apply -f manifests/3_helloworld_service.yaml

    Once you've done this you should see the Service (if you get Services):

     $> kubectl get services
    NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE
    example1 NodePort 10.97.195.99 <none> 80:30080/TCP 4s
    kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 15m

    You will notice two Services, 1) your example and 2) the Kubernetes Service. This is normal, kind exposes the Service you are using to communicate with the cluster in this way.

    Now you have your service up and running. Lets see it in a browser, open up the url to http://localhost and hit enter, you should see something like this:

    Welcome to nginx

    "But I want a custom page of my own design",  you might say. Let's add our own custom html page to the deployment.

    The typical way custom content reaches a Kubernetes cluster is by publishing a container with the content bundled to a registry. Many of these exist, such as dockerhub.com, AWS's ECR (Elastic Container Registry), Google's container registry or even a self hosted registry. All of these are outside the scope of this article so we are going to pass content into the existing nginx container with a Kubernetes resource called a configmap.

    These resources are a useful way for passing in config files to processes inPpods, but in this case, we're going to use one to supply a replacement index.html file to the nginx default /usr/share/nginx/html web server file path.

    For convenience there is a html file in the html/ folder in the git repository. Add the config map using this command.

    kubectl create configmap index.html --from-file html/index.html

    You can see it created successfully using the command kubectl get configmaps which should show the result below:

    NAME         DATA   AGE
    index.html 1 33s

    To see what is in the configmap for your own curiosity, you can run kubectl describe configmap index.html.

    Now we just need to tell the nginx Pod to read from this configmap for its content. Let's update the deployment file one more time to add a Volume mount, essentially treating the content of the content map like a mountable file inside the file system of the nginx container.

    Update your yaml file with the new content below at the end of the file:

            volumeMounts:
    - name: htmlcontent
    mountPath: "/usr/share/nginx/html/"
    readOnly: true
    volumes:
    - name: htmlcontent
    configMap:
    name: index.html
    items:
    - key: index.html
    path: index.html

    ...or use the file in the Github repository and apply the change to your deployment with the command as below.

    kubectl apply -f manifests/4_helloworld_deploy_content.yaml

    Finally we will see the deployment update which can be done with kubectl get pods which again we can see a Terminating pod being replaced with a new Pod.

    NAME                        READY   STATUS        RESTARTS   AGE
    example1-587454c8fb-4llk9 1/1 Terminating 0 177m
    example1-566dd9577f-j48bh 1/1 Running 0 2s

    Finally you can view the updated content on our localhost page in your browser and see the lovely branded helloworld page.

     

    Kubernetes Hello World

    Set your own text

    Now for your own enjoyment, try updating the html/index.html file with your own text. Update the configmap with your new content, this requires a little command line trickery, but with the following command you can replace the existing configmap content with your new index.html file content.

    kubectl create configmap index.html --from-file html/index.html -oyaml --dry-run | kubectl replace -f -

    To get the nginx Pod to reload mounting the new value of the configmap, you need to get the pod to recreate. Do this using the following command:

    kubectl rollout restart deployment example1

    This will tell the deployment to re-deploy its pods, so if you do kubectl get pods again, you will see the rolling change happening.

    NAME                        READY   STATUS              RESTARTS   AGE
    example1-566dd9577f-j48bh 1/1 Running 0 14m
    example1-78df6fc9ff-l98cg 0/1 ContainerCreating 0 3s

    Reload your browser and you will see your clever and witty message!

    Clean up your new cluster

    When you are all done with the test cluster, you can clean it up easily by using the following command:

    kind delete cluster --name mycluster

    This deletes the Docker container that is running your cluster, and thankfully clears up the kubectl config file for you too so you don't have to worry about cleaning up your home .kube/config file.

    Don't stop there

    You've made great headway in deploying your first Kubernetes cluster, so continue learning about Kubernetes with our foundational Guide to Kubernetes

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