Kubernetes Without Scale: Setting up a Personal Cluster, Part 2

In Part 1, we discussed some good reasons to run your own Kubernetes cluster, even for software that doesn’t need high scalability and reliability. We showed that installing and managing third-party applications such as Ghost becomes as simple as helm install, and that strong support for infrastructure as code makes Kubernetes a great way maintain your “production” environment.

Typically, Kubernetes runs across several different machines, which allows applications to scale up and down with a high degree of resiliency. But here, we’re just looking to self-host some third-party software and personal projects. So we’ll set up Kubernetes on a single t2.small EC2 instance running Ubuntu, which, with 2GB of memory and a single CPU, runs about $15/month.

Unfortunately there’s no helm install for Kubernetes itself. To get up and running, we’ll use KIND, a project that runs Kubernetes inside of Docker, to install Kubernetes. Once that’s done, we’ll install a few crucial add-ons that will help us with DNS and provisioning SSL certificates. Finally, to show off our setup, we’ll install HackMD, an open source collaborative markdown editor, which you can use as a replacement for Google Docs.

Set Up a Machine

We’re going to set up our machine using AWS EC2, but you should be able to adapt these instructions to your cloud provider of choice.

On the EC2 page, click “Launch Instance” and when prompted for an operating system, choose Ubuntu 18.04:Then, when prompted to choose an instance type, choose t2.small:

This will run at about $15/month. We wouldn’t recommend choosing a smaller instance (running Kubernetes comes with a good amount of resource overhead), but if you plan to run any resource-intensive applications, you may want to choose a larger instance type.

Configure the rest of your machine as you see fit. We recommend increasing the default amount of storage if you plan on running data-intensive applications. Be sure to save your SSH private key somewhere, and be sure to open up port 22 so you can log in.

Next, while your instance is starting up, we’ll associate an elastic IP with it. This will give your EC2 instance a permanent IP address, which we’ll use to create DNS records.

From the EC2 page, click “Elastic IPs,” then “Allocate a new address,” and choose your new EC2 instance.

Finally, you can head to Route 53 to register a new domain name (or manage an existing one). You should create a new A Record pointing *.example.com to the elastic IP address you created above. You can also create a similar A Record for example.com if you want the apex domain to point to your cluster as well.

Once that’s done, we’re ready to build the cluster! Connect to your machine via SSH and follow the instructions below to start serving traffic.

Install Dependencies

First, let’s install Docker. Docker lets us run containerized operating systems within our environment. Kubernetes itself will run inside a Docker image, as will all the software we install in the cluster.

sudo apt install -y apt-transport-https ca-certificates curl software-properties-common
curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu bionic stable"
sudo apt update
sudo apt install -y docker-ce
sudo usermod -aG docker $USER
newgrp docker

Next, we’ll install KIND, a project that runs Kubernetes clusters inside Docker on a single machine.

curl -Lo ./kind https://github.com/kubernetes-sigs/kind/releases/download/v0.5.1/kind-$(uname)-amd64
chmod +x ./kind
sudo mv ./kind /usr/local/bin

Then let’s install kubectl, a CLI for interacting with Kubernetes clusters. This will be our main way of talking to the cluster we create with KIND.

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
sudo mv ./kubectl /usr/local/bin/kubectl

Next up is Helm, a package manager for Kubernetes. Helm will give us one-command installs for third-party software such as WordPress, Ghost, MySQL and GitLab.

sudo snap install helm --classic

Finally, to help us manage our Helm packages, we’ll use Reckoner, which lets us declare multiple charts in a single YAML file.

sudo apt-get install python3 python3-pip
export PATH=$PATH:~/.local/bin/
pip3 install reckoner

That’s all the prerequisite software we’ll need. To recap:

  • Docker runs applications in virtual operating systems, known as containers.
  • KIND runs Kubernetes—a container orchestration platform—inside of Docker.
  • kubectl lets us interact with our Kubernetes cluster.
  • Helm helps us install software onto our cluster.
  • Reckoner helps us manage our Helm charts.

Building the Cluster

Now we’ll use KIND to build our Kubernetes cluster. To do this, we’ll create a YAML file, cluster.yaml, which will store the cluster configuration.

In the Kubernetes world (and in all modern DevOps environments), we have a strong bias toward storing all our infrastructure in version control. So now might be a good time to start a git repository where you can keep your code.

Here’s the configuration for our KIND cluster:


kind: Cluster
apiVersion: kind.sigs.k8s.io/v1alpha3
- role: control-plane
- role: worker
  - containerPath: /opt/local-path-provisioner
    hostPath: /home/ubuntu/kind-disk
  - containerPort: 80
    hostPort: 80
    listenAddress: ""
  - containerPort: 443
    hostPort: 443
    listenAddress: ""

There are a few things to note here:

  • We’re creating two roles: one that runs the control plane (the Kubernetes API) and one that runs the workers (where our apps will run).
  • We’re mounting the directory /home/ubuntu/kind-disk as a place for persistent storage. Any databases that run in our cluster will put their data here. You can configure it to whatever you want.
  • We’re exposing ports 80 and 443, which will allow us to connect to our cluster from the outside world.

To create the cluster, run:

kind create cluster --config cluster.yaml
export KUBECONFIG="$(kind get kubeconfig-path --name='kind')"

Now you should be able to run:

kubectl get nodes

And see two nodes:

NAME                 STATUS   ROLES    AGE    VERSION
kind-control-plane   Ready    master   109s   v1.15.3
kind-worker          Ready       73s    v1.15.3

You may have to wait a minute or two for the nodes to show up as Ready.

Setting up the Cluster

We’ll need to install some software onto our cluster to start installing and managing software.

First, let’s set up Tiller, the part of Helm that runs inside the Kubernetes cluster. We’ll start by creating an RBAC role for tiller, which gives it admin access to the cluster.


apiVersion: v1
kind: Namespace
  name: tiller
apiVersion: v1
kind: ServiceAccount
  name: tiller
  namespace: tiller
kind: ClusterRoleBinding
apiVersion: rbac.authorization.k8s.io/v1beta1
  name: tiller-clusterrolebinding
- kind: ServiceAccount
  name: tiller
  namespace: tiller
  kind: ClusterRole
  name: cluster-admin
  apiGroup: ""

Then we’ll initialize Tiller on the cluster:

kubectl apply -f tiller.rbac.yaml
export TILLER_NAMESPACE=tiller
helm init --service-account tiller

We also need to set up local storage, so that any saved data gets put in /home/ubuntu/kind-disk

kubectl apply -f https://raw.githubusercontent.com/rancher/local-path-provisioner/master/deploy/local-path-storage.yaml
kubectl patch storageclass standard -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"false", "storageclass.beta.kubernetes.io/is-default-class":"false"}}}'
kubectl patch storageclass local-path -p '{"metadata": {"annotations":{"storageclass.kubernetes.io/is-default-class":"true", "storageclass.beta.kubernetes.io/is-default-class":"true"}}}'

Finally, we’ll set up cert-manager and nginx-ingress. cert-manager will help us provision SSL certificates from Let’s Encrypt, and nginx-ingress will help us route traffic from particular domain names to the correct application.

First, we’ll create issuer.yaml, which will tell cert-manager to use Let’s Encrypt to provision certificates (you could also use another issuer). Be sure to replace [email protected] with your own email address.


apiVersion: cert-manager.io/v1alpha2
kind: ClusterIssuer
  name: letsencrypt-prod
    server: https://acme-v02.api.letsencrypt.org/directory
    email: [email protected]
      name: letsencrypt-prod
    - http01:
          class:  nginx

Note that you won’t be able to kubectl apply this manifest yet; first, we’ll need to install cert-manager.

To install the Helm charts for nginx-ingress and cert-manager, we’ll create core.course.yaml. Down the line, if there’s any other infrastructure we want to add to our core stack, we can add it here.


    url: https://charts.jetstack.io
namespace: default
      - kubectl apply --validate=false -f https://raw.githubusercontent.com/jetstack/cert-manager/release-0.11/deploy/manifests/00-crds.yaml
      - sleep 30 && kubectl apply -f issuer.yaml
    namespace: cert-manager
    repository: jetstack
    namespace: nginx-ingress
        hostNetwork: true
          type: LoadBalancer

Now run reckoner plot core.course.yaml to install both cert-manager and nginx-ingress on your cluster. If you look at the post_install hook for cert-manager, you’ll notice this also adds issuer.yaml to your cluster.

To check that everything is working as expected, run:

$ kubectl get pods -n nginx-ingress
NAME                                             READY   STATUS    RESTARTS   AGE
nginx-ingress-controller-664b77978-gbd59         1/1     Running   0          14s
nginx-ingress-default-backend-576b86996d-fjb4k   1/1     Running   0          14s

$ kubectl get pods -n cert-manager
NAME                                       READY   STATUS    RESTARTS   AGE
cert-manager-6b78b7c997-mblt4              1/1     Running   0          18s
cert-manager-cainjector-54c4796c5d-psdgt   1/1     Running   0          18s
cert-manager-webhook-77ccf5c8b4-8tkwt      1/1     Running   0          17s

You may have to wait a minute to see every pod in the Running state.

Install an Application

To test out our new cluster, we’ll install HackMD, an open source collaborative markdown editor. It’s a good, lightweight replacement for Google Docs, especially if you want to host all your own data.

First, we’ll create an Ingress for the app, which will tell nginx-ingress to route traffic from hackmd.example.com to the HackMD application (be sure to replace both instances of example.com with your own domain):


apiVersion: extensions/v1beta1
kind: Ingress
    kubernetes.io/ingress.class: nginx
    cert-manager.io/issuer: letsencrypt-prod
    kubernetes.io/tls-acme: "true"
  name: hackmd
  namespace: hackmd
    - host: hackmd.example.com
          - backend:
              serviceName: hackmd
              servicePort: 3000
            path: /
  - secretName: tls-prod-cert
    - hackmd.example.com

Then we’ll create apps.course.yaml. Later on, if we want to add other applications to our cluster, we can add them here.


namespace: default
    namespace: hackmd
      - kubectl apply -f ./ingress.yaml

Again, note the post_install hook, which takes care of adding ingress.yaml for us.

Now we just need to run reckoner plot apps.course.yaml, and we’re off and running! You should be able to see HackMD running at https://hackmd.example.com. You’ll also see the data being stored inside the directory at /home/ubuntu/kind-disk.

In the future, if you want to install another app, it should be as easy as adding a few lines to apps.course.yaml, creating another ingress.yaml, and running reckoner plot apps.course.yaml. And, if you’ve been saving all these files to a Git repository, you can easily migrate your cluster to a new machine or rebuild it from scratch.

Hopefully we’ve convinced you that Kubernetes is a great way to install and manage third-party software. But there are still a lot of moving parts here, so if you run into any trouble, let us know in the comments!

Robert Brennan

Robert Brennan is director of open source software at Fairwinds, a cloud-native infrastructure solution provider. He focuses on the development of open source tools that abstract the complexity from underlying infrastructure to enable an optimal experience for developers. Before Fairwinds, he worked as a software engineer at Google in AI and natural language processing. He is the co-founder of DataFire.io, an open source platform for building API’s and integrations, and LucyBot, developer of a suite of automated API documentation solutions deployed by Fortune 500 companies. He is a graduate of Columbia College and Columbia Engineering where he focused on machine learning.

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