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Deploying a Kubernetes Cluster

Deploying a Kubernetes Cluster
Hostman Team
Technical writer
Kubernetes
25.01.2024
Reading time: 7 min

Beginning DevOps engineers pretty quickly find themselves needing to deploy a Kubernetes cluster, which is typically used to manage and run Docker containers. Let's look at a solid way to deploy a Kubernetes cluster on Ubuntu OS, and then summarize other possible options.

Kubernetes for DevOps: deploying, running, and scaling up

Let's start with a bit of important terminology. By cluster, we mean a pooling of resources under Kubernetes management. A cluster includes at least one master node and one worker node. While nodes are used to run containers, Kubernetes allows you to monitor the nodes and automatically manage and scale the cluster. The easiest way to deploy a Kubernetes cluster is as follows.

Deploying a cluster on Ubuntu: step-by-step instructions

For deployment, we will need external IPs for each node, and each node needs to have 2 GB RAM and 2 CPU cores. For Ubuntu, it is desirable to increase the amount of RAM to 4 GB and provide 30-35 GB of disk space. This configuration is enough to start, but you may need to add extra cloud resources later when the number of running containers increases. With Hostman, you can do this "on the fly".

We assume that you have already installed the OS and have two servers (nodes), one of which will be used as a master and the other as a worker.

Step 1: Generate SSH keys

You will need to generate SSH keys for each node so that you can manage the cluster remotely. Start with this command:

ssh-keygen

You can use the -t flag to specify the type of key to generate. For example, to create an RSA key, execute:

ssh-keygen -t rsa

You can also use the -b flag to specify the bit size:

ssh-keygen -b 2048 -t rsa

Now, you can specify the path to the file to store the key. The default path and file name are usually offered in this format: /home/user_name/ .ssh/id_rsa. Press Enter if you want to use the default path and file name. Otherwise, enter the desired path and file name, and then press Enter. Next, you will be prompted to enter a password. We recommend doing this to protect the key from unauthorized use.

After confirming the password, the program will generate a pair of SSH keys, public and private, and save them to the specified path. The default key file names are id_rsa for the private key and id_rsa.pub for the public key.

Note the path and file names of the private and public key files. You will need to enter the SSH public key to use on the remote device. To log in, you must specify the path to the corresponding SSH private key and enter the password when prompted.

And one more important point regarding security: never share the SSH private key, otherwise anyone can get access to the server. 

Step 2: Install packages

Now, let's connect to the worker node.

First, update the package list. Type:

apt-get update

Next, install the required packages via sudo. Separate the package names with a space:

sudo apt-get install apt-transport-https ca-certificates curl -y

The -y flag at the end will answer "yes" automatically to all system prompts.

Step 3: Obtain the GPG key

To do this, enter the following lines one by one:

sudo mkdir \
-p /etc/apt/keyrings
curl -fsSL https://download.docker.com/linux/ubuntu/gpg \
| sudo gpg - dearmor -o /etc/apt/keyrings/docker.gpg

Step 4: Install Docker

Finally, let's install Docker. Get the package:

sudo add-apt-repository 'deb [arch=amd64] your_URL_here'

Instead of your_URL_here, specify the address of the real repository, depending on your OS. 

For example, for Ubuntu 22.04 'Jammy' the command will look like this:

sudo add-apt-repository 'deb [arch=amd64] https://download.docker.com/linux/ubuntu jammy stable'

Next, update the packages:

sudo apt update

Type the command:

sudo apt install docker-ce -y

Check that Docker is successfully installed: 

sudo docker run hello-world

Step 5: Install Kubernetes modules

Now, we need to install the following Kubernetes modules:

  • Kubelet. We will need it for each node, as it controls the state of containers;

  • Kubeadm. It helps to automate the installation and configuration of other Kubernetes modules. It also should be installed on all nodes;

  • Kubectl. It's used in all projects with Kubernetes, as it is the one that starts the commands.

To install the modules, enter:

apt-get install -y kubelet kubeadm kubectl

And then reboot: 

rm /etc/containerd/config.toml
systemctl restart containerd

Step 6: Create a cluster

After configuring one node, you can easily create and deploy as many copies of it as you need using cloning. To do this, go to your server's page in the Hostman control panel and click Clone to create an exact copy of your node.

Next, we need to convert one of the worker nodes to a master node from which we will manage the cluster. To do this, enter the command:

kubeadm init --pod-network-cidr=10.244.0.0/16

In the output, we will get a long message starting with the line Your Kubernetes control-plane has initialized successfully!. This means that the cluster is created.

Now, go to the last line, which is the token code. Copy and save it in any text editor because you will need it later for further configuration.

Step 7: Start the cluster

Use the command:

export KUBECONFIG=$HOME/admin.conf 

Next, allow containers to be started with the following:

kubectl taint nodes --all node-role.kubernetes.io/master-

Step 8: Provide intranet communication

For this purpose, install SDN Flannel, the latest version of which can be found here

Next, to test it, enter:

kubectl -n kube-system get pods

Step 9: Create a token

Now, we need to get a token to authorize. Add the previously saved token or, if you forgot to save it, enter:

kubeadm token list

Once the token is created, let's start deploying the cluster. Note that the token is only valid for 24 hours, but you can always generate a new one using the following command:

kubeadm token create --print-join-command

Step 10. Connect working nodes

So, our cluster is up and running. Let's start connecting worker nodes to it using the token (IP and token values below are given just as an example):

kubeadm join 172.31.43.204:6443 --token fg691w.pu5qexz1n654vznt --discovery-token-ca-cert-hash [insert the generated token here and remove the square brackets]

If an error occurs (this sometimes happens), simply restart the cluster and re-enter the above kubeadm join command.

Step 11. Check if it works

That's all. Now, we need to see if the nodes are responding. 

kubectl get pods --all-namespaces
kubectl get nodes

If the output shows Running and Ready, everything is done correctly.

Now, let's briefly look at other ways to deploy a cluster, particularly with VMware and Azure applications.

Other ways to deploy

  • vCloud Director

To deploy a cluster, you will need vCloud Director with CSE installed and, of course, Kubernetes itself with the Kubectl plug-in we discussed above.

CSE, or Container service extension, is an extension for VMware products that provides full support for Kubernetes clusters in a virtualized infrastructure. The system requirements for the cluster and its nodes are the same as in the example above. The process of installing and deploying a Kubernetes cluster via vCloud Director is described in the documentation.

  • Azure Kubernetes

We will need the Azure CLI or PowerShell. The cluster in Azure CLI is created via az aks create command with the following parameters (substitute your values instead of myResourceGroup_name_here, myAKSCluster_name_here and acrName_here):

az aks create \
    --resource-group myResourceGroup_name_here.
    --name myAKSCluster_name_here.
    --node-count 2.
    --generate-ssh-keys.
    --attach-acr 

If you are using PowerShell, then the similar commands will apply:

New-AzAksCluster -ResourceGroupName myResourceGroup_name_here -Name myAKSCluster_name_here -NodeCount 2 -GenerateSshKey -AcrNameToAttach <acrName_here>

Of course, Ubuntu is not the only OS where you can deploy a cluster. Almost all Linux-based systems are suitable for this, but keep in mind that the commands you enter may slightly differ. So, on Ubuntu, Docker is installed as follows: apt-get install -y docker.io, but, for example, in CentOS the command will look a little different: yum install -y docker.

Kubernetes
25.01.2024
Reading time: 7 min

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23 August 2024 · 5 min to read
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Running Kubernetes Clusters in the Cloud with VMware

Containerization is an effective way to deliver applications to customers. If your cloud IT infrastructure is deployed on VMware, you can use CSE, or Container Service Extension, to work with Kubernetes (K8s). This solution significantly accelerates the time from receiving code to deploying it in a production cloud system by automating the management (orchestration) of containers with the software. What is CSE? CSE is an extension to the VMware vCloud Director (VCD) platform that adds functionality for interacting with Kubernetes clusters—from creation to lifecycle management. Its installation allows for a comprehensive approach, integrating the management of both legacy and containerized applications within a single VMware infrastructure, while maintaining uniformity and a systematic management approach. Key features The CSE client facilitates cluster deployment, adds worker nodes, and configures NFS storage. 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Open this file with a text editor and find the line active with the following value: extensions:- container_service_extension.client.cse After saving the changes to the configuration file, log in: vcd login <host> <organization_name> <login> Now, verify that the extension is indeed installed and actively interacting with the host: vcd cse versionCSE, Container Service Extension for VMware vCloud Director, version 3.0.1 vcd cse system infoproperty     value-----------  ------------------------------------------------------description  Container Service Extension for VMware vCloud Directorproduct      CSEversion      2.6.1 Creating a Kubernetes Cluster Next, let's look at activating a Kubernetes cluster within VMware. Integration with the vCloud Director platform allows managing the process from a single point in a familiar interface. Data center resources are typically pooled, and deployment is done through VM templates with pre-installed and pre-configured Kubernetes. 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Here's an example of how to use it. 1) Create a namespace and add MetalLB using manifests: kubectl apply -f https://raw.githubusercontent.com/metallb/metallb/v0.9.5/manifests/namespace.yamlkubectl apply -f https://raw.githubusercontent.com/metallb/metallb/v0.9.5/manifests/metallb.yaml 2) Next, configure node connection security. Without this, the transmitted pods will go into a CreateContainerConfigError status, and error messages such as secret memberlist not found will appear in the logs: kubectl create secret generic -n metallb-system memberlist --from-literal=secretkey="$(openssl rand -base64 128)" 3) Check the current status of the utility. If configured correctly, the controller and speaker will be displayed as running: kubectl get pod --namespace=metallb-system  NAME                          READY   STATUS    RESTARTS   AGEcontroller-57f648cb96-2lzm4   1/1     Running   0          5h52mspeaker-ccstt                 1/1     Running   0          5h52mspeaker-kbkps                 1/1     Running   0          5h52mspeaker-sqfqz                 1/1     Running   0          5h52m 4) Finally, manually create a configuration file: apiVersion: v1 kind: ConfigMap metadata:   namespace: metallb-system   name: config data:   config: |     address-pools:     - name: default       protocol: layer2       addresses:      - X.X.X.101-X.X.X.102 You should fill in the addresses parameter with the addresses that remain free and will handle the load balancing. Apply the configuration file: kubectl apply -f metallb-config.yaml The procedure for setting up a LoadBalancer for Kubernetes using MetalLB is complete; next is Ingress support, which is easier to implement with another tool. Project Contour Create a manifest with Project Contour using the command: kubectl apply -f https://projectcontour.io/quickstart/contour.yaml This command automatically deploys the Envoy proxy server, which listens on the standard ports 80 and 443. Conclusion Integrating Kubernetes into VMware with the Container Service Extension (CSE) unifies the management of legacy and containerized applications within VMware vCloud Director. While the setup may be complex, CSE enhances application deployment, scaling, and management, offering a resilient and scalable infrastructure. Despite some limitations, such as native LoadBalancer support, tools like MetalLB and Project Contour provide effective solutions. Overall, CSE empowers organizations to modernize their IT infrastructure, accelerating development and optimizing resources within a secure, multi-tenant cloud environment.
22 August 2024 · 7 min to read

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