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      Kubeadm

      Getting Started with Kubernetes: Use kubeadm to Deploy a Cluster on Linode


      Updated by Linode Contributed by Linode

      Linode offers several pathways for users to easily deploy a Kubernetes cluster. If you prefer the command line, you can create a Kubernetes cluster with one command using the Linode CLI’s k8s-alpha plugin, and Terraform. Or, if you prefer a full featured GUI, Linode’s Rancher integration enables you to deploy and manage Kubernetes clusters with a simple web interface. The Linode Kubernetes Engine, currently under development with an early access beta version on its way this summer, allows you to spin up a Kubernetes cluster with Linode handling the management and maintenance of your control plane. These are all great options for production ready deployments.

      Kubeadm is a cloud provider agnostic tool that automates many of the tasks required to get a cluster up and running. Users of kubeadm can run a few simple commands on individual servers to turn them into a Kubernetes cluster consisting of a master node and worker nodes. This guide will walk you through installing kubeadm and using it to deploy a Kubernetes cluster on Linode. While the kubeadm approach requires more manual steps than other Kubernetes cluster creation pathways offered by Linode, this solution will be covered as way to dive deeper into the various components that make up a Kubernetes cluster and the ways in which they interact with each other to provide a scalable and reliable container orchestration mechanism.

      Note

      This guide’s example instructions will result in the creation of three billable Linodes. Information on how to tear down the Linodes are provided at the end of the guide. Interacting with the Linodes via the command line will provide the most opportunity for learning, however, this guide is written so that users can also benefit by reading along.

      Before You Begin

      1. Deploy three Linodes running Ubuntu 18.04 with the following system requirements:

        • One Linode to use as the master Node with 4GB RAM and 2 CPU cores.
        • Two Linodes to use as the Worker Nodes each with 1GB RAM and 1 CPU core.
      2. Follow the Getting Started and the Securing Your Server guides for instructions on setting up your Linodes. The steps in this guide assume the use of a limited user account with sudo privileges.

      Note

      When following the Getting Started guide, make sure that each Linode is using a different hostname. Not following this guideline will leave you unable to join some or all nodes to the cluster in a later step.
      1. Disable swap memory on your Linodes. Kubernetes requires that you disable swap memory on any cluster nodes to prevent the Kubernetes scheduler (kube-scheduler) from ever sending a pod to a node that has run out of CPU/memory or reached its designated CPU/memory limit.

        sudo swapoff -a
        

        Verify that your swap has been disabled. You should expect to see a value of 0 returned.

        cat /proc/meminfo | grep 'SwapTotal'
        

        To learn more about managing compute resources for containers, see the official Kubernetes documentation.

      2. Read the Beginners Guide to Kubernetes to familiarize yourself with the major components and concepts of Kubernetes. The current guide assumes a working knowledge of common Kubernetes concepts and terminology.

      Build a Kubernetes Cluster

      Kubernetes Cluster Architecture

      A Kubernetes cluster consists of a master node and worker nodes. The master node hosts the control plane, which is the combination of all the components that provide it the ability to maintain the desired cluster state. This cluster state is defined by manifest files and the kubectl tool. While the control plane components can be run on any cluster node, it is a best practice to isolate the control plane on its own node and to run any application containers on a separate worker node. A cluster can have a single worker node or up to 5000. Each worker node must be able to maintain running containers in a pod and be able to communicate with the master node’s control plane.

      The table below provides a list of the Kubernetes tooling you will need to install on your master and worker nodes in order to meet the minimum requirements for a functioning Kubernetes cluster as described above.

      ToolDescriptionMaster NodeWorker Nodes
      kubeadmThis tool provides a simple way to create a Kubernetes cluster by automating the tasks required to get a cluster up and running. New Kubernetes users with access to a cloud hosting provider, like Linode, can use kubeadm to build out a playground cluster. kubeadm is also used as a foundation to create more mature Kubernetes deployment tooling.xx
      Container RuntimeA container runtime is responsible for running the containers that make up a cluster’s pods. This guide will use Docker as the container runtime.xx
      kubeletkubelet ensures that all pod containers running on a node are healthy and meet the specifications for a pod’s desired behavior.xx
      kubectlA command line tool used to manage a Kubernetes cluster.xx
      Control PlaneSeries of services that form Kubernetes master structure that allow it to control the cluster. Kubeadm allows the control plane services to run as containers on the master node. The control plane will be created when you initialize kubeadm later in this guide.x

      Install the Container Runtime: Docker

      Docker is the software responsible for running the pod containers on each node. You can use other container runtime software with Kubernetes, such as Containerd and CRI-O. You will need to install Docker on all three Linodes.

      These steps install Docker Community Edition (CE) using the official Ubuntu repositories. To install on another distribution, see the official installation page.

      1. Remove any older installations of Docker that may be on your system:

        sudo apt remove docker docker-engine docker.io
        
      2. Make sure you have the necessary packages to allow the use of Docker’s repository:

        sudo apt install apt-transport-https ca-certificates curl software-properties-common
        
      3. Add Docker’s GPG key:

        curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
        
      4. Verify the fingerprint of the GPG key:

        sudo apt-key fingerprint 0EBFCD88
        

        You should see output similar to the following:

          
        pub   4096R/0EBFCD88 2017-02-22
                Key fingerprint = 9DC8 5822 9FC7 DD38 854A  E2D8 8D81 803C 0EBF CD88
        uid                  Docker Release (CE deb) 
        sub   4096R/F273FCD8 2017-02-22
        
        
      5. Add the stable Docker repository:

        sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $(lsb_release -cs) stable"
        
      6. Update your package index and install Docker CE:

        sudo apt update
        sudo apt install docker-ce
        
      7. Add your limited Linux user account to the docker group. Replace $USER with your username:

        sudo usermod -aG docker $USER
        

        Note

        After entering the usermod command, you will need to close your SSH session and open a new one for this change to take effect.

      8. Check that the installation was successful by running the built-in “Hello World” program:

        sudo docker run hello-world
        
      9. Setup the Docker daemon to use systemd as the cgroup driver, instead of the default cgroupfs. This is a recommended step so that Kubelet and Docker are both using the same cgroup manager. This will make it easier for Kubernetes to know which resources are available on your cluster’s nodes.

        sudo bash -c 'cat > /etc/docker/daemon.json <<EOF
        {
          "exec-opts": ["native.cgroupdriver=systemd"],
          "log-driver": "json-file",
          "log-opts": {
            "max-size": "100m"
          },
          "storage-driver": "overlay2"
        }
        EOF'
        
      10. Create a systemd directory for Docker:

        sudo mkdir -p /etc/systemd/system/docker.service.d
        
      11. Restart Docker:

        sudo systemctl daemon-reload
        sudo systemctl restart docker
        

      Install kubeadm, kubelet, and kubectl

      Complete the steps outlined in this section on all three Linodes.

      1. Update the system and install the required dependencies for installation:

        sudo apt-get update && sudo apt-get install -y apt-transport-https curl
        
      2. Add the required GPG key to your apt-sources keyring to authenticate the Kubernetes related packages you will install:

        curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -
        
      3. Add Kubernetes to the package manager’s list of sources:

        sudo bash -c "cat <<EOF >/etc/apt/sources.list.d/kubernetes.list
        deb https://apt.kubernetes.io/ kubernetes-xenial main
        EOF"
        
      4. Update apt, install Kubeadm, Kubelet, and Kubectl, and hold the installed packages at their installed versions:

        sudo apt-get update
        sudo apt-get install -y kubelet kubeadm kubectl
        sudo apt-mark hold kubelet kubeadm kubectl
        
      5. Verify that kubeadm, kubelet, and kubectl have installed by retrieving their version information. Each command should return version information about each package.

        kubeadm version
        kubelet --version
        kubectl version
        

      Set up the Kubernetes Control Plane

      After installing the Kubernetes related tooling on all your Linodes, you are ready to set up the Kubernetes control plane on the master node. The control plane is responsible for allocating resources to your cluster, maintaining the health of your cluster, and ensuring that it meets the minimum requirements you designate for the cluster.

      The primary components of the control plane are the kube-apiserver, kube-controller-manager, kube-scheduler, and etcd. kubeadm provides a way to easily initialize the Kubernetes master node with all the necessary control plane components. For more information on each of control plane component see the Beginner’s Guide to Kubernetes.

      In addition to the baseline control plane components, there are several addons, that can be installed on the master node to access additional cluster features. You will need to install a networking and network policy provider add on that will implement Kubernetes’ network model on the cluster’s pod network.

      This guide will use Calico as the pod network add on. Calico is a secure and open source L3 networking and network policy provider for containers. There are several other network and network policy providers to choose from. To view a full list of providers, refer to the official Kubernetes documentation.

      Note

      kubeadm only supports Container Network Interface (CNI) based networks. CNI consists of a specification and libraries for writing plugins to configure network interfaces in Linux containers

      1. Initialize kubeadm on the master node. This command will run checks against the node to ensure it contains all required Kubernetes dependencies, if the checks pass, it will then install the control plane components.

        When issuing this command, it is necessary to set the pod network range that Calico will use to allow your pods to communicate with each other. It is recommended to use the private IP address space, 10.2.0.0/16.

        Note

        The pod network IP range should not overlap with the service IP network range. The default service IP address range is 10.96.0.0/12. You can provide an alternative service ip address range using the --service-cidr=10.97.0.0/12 option when initializing kubeadm. Replace 10.97.0.0/12 with the desired service IP range.

        For a full list of available kubeadm initialization options, see the official Kubernetes documentation.

        sudo kubeadm init --pod-network-cidr=10.2.0.0/16
        

        You should see a similar output:

          
        Your Kubernetes control-plane has initialized successfully!
        
        To start using your cluster, you need to run the following as a regular user:
        
          mkdir -p $HOME/.kube
          sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
          sudo chown $(id -u):$(id -g) $HOME/.kube/config
        
        You should now deploy a pod network to the cluster.
        Run "kubectl apply -f [podnetwork].yaml" with one of the options listed at:
          https://kubernetes.io/docs/concepts/cluster-administration/addons/
        
        Then you can join any number of worker nodes by running the following on each as root:
        
        kubeadm join 192.0.2.0:6443 --token udb8fn.nih6n1f1aijmbnx5 
            --discovery-token-ca-cert-hash sha256:b7c01e83d63808a4a14d2813d28c127d3a1c4e1b6fc6ba605fe4d2789d654f26
              
        

        The kubeadm join command will be used in the Join a Worker Node to the Cluster section of this guide to bootstrap the worker nodes to the Kubernetes cluster. This command should be kept handy for later use. Below is a description of the required options you will need to pass in with the kubeadm join command:

        • The master node’s IP address and the Kubernetes API server’s port number. In the example output, this is 192.0.2.0:6443. The Kubernetes API server’s port number is 6443 by default on all Kubernetes installations.
        • A bootstrap token. The bootstrap token has a 24-hour TTL (time to live). A new bootstrap token can be generated if your current token expires.
        • A CA key hash. This is used to verify the authenticity of the data retrieved from the Kubernetes API server during the bootstrap process.
      2. Copy the admin.conf configuration file to your limited user account. This file allows you to communicate with your cluster via kubectl and provides superuser privileges over the cluster. It contains a description of the cluster, users, and contexts. Copying the admin.conf to your limited user account will provide you with administrative privileges over your cluster.

        mkdir -p $HOME/.kube
        sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
        sudo chown $(id -u):$(id -g) $HOME/.kube/config
        
      3. Install the necessary Calico manifests to your master node and apply them using kubectl. The first file, rbac-kdd.yaml, works with Kubernetes’ role-based access control (RBAC) to provide Calico components access to necessary parts of the Kubernetes API. The second file, calico.yaml, configures a self-hosted Calico installation that uses the Kubernetes API directly as the datastore (instead of etcd).

        kubectl apply -f https://docs.projectcalico.org/v3.3/getting-started/kubernetes/installation/hosted/rbac-kdd.yaml
        kubectl apply -f https://docs.projectcalico.org/v3.3/getting-started/kubernetes/installation/hosted/kubernetes-datastore/calico-networking/1.7/calico.yaml
        

      Inspect the Master Node with Kubectl

      After completing the previous section, your Kubernetes master node is ready with all the necessary components to manage a cluster. To gain a better understanding of all the parts that make up the master’s control plane, this section will walk you through inspecting your master node. If you have not yet reviewed the Beginner’s Guide to Kubernetes, it will be helpful to do so prior to continuing with this section as it relies on the understanding of basic Kubernetes concepts.

      1. View the current state of all nodes in your cluster. At this stage, the only node you should expect to see is the master node, since worker nodes have yet to be bootstrapped. A STATUS of Ready indicates that the master node contains all necessary components, including the pod network add-on, to start managing clusters.

        kubectl get nodes
        

        Your output should resemble the following:

          
        NAME        STATUS     ROLES     AGE   VERSION
        kube-master   Ready     master      1h    v1.14.1
            
        
      2. Inspect the available namespaces in your cluster.

        kubectl get namespaces
        

        Your output should resemble the following:

          
        NAME              STATUS   AGE
        default           Active   23h
        kube-node-lease   Active   23h
        kube-public       Active   23h
        kube-system       Active   23h
            
        

        Below is an overview of each namespace installed by default on the master node by kubeadm:

        • default: The default namespace contains objects with no other assigned namespace. By default, a Kubernetes cluster will instantiate a default namespace when provisioning the cluster to hold the default set of Pods, Services, and Deployments used by the cluster.
        • kube-system: The namespace for objects created by the Kubernetes system. This includes all resources used by the master node.
        • kube-public: This namespace is created automatically and is readable by all users. It contains information, like certificate authority data (CA), that helps kubeadm join and authenticate worker nodes.
        • kube-node-lease: The kube-node-lease namespace contains lease objects that are used by kubelet to determine node health. kubelet creates and periodically renews a Lease on a node. The node lifecycle controller treats this lease as a health signal. kube-node-lease was released to beta in Kubernetes 1.14.
      3. View all resources available in the kube-system namespace. The kube-system namespace contains the widest range of resources, since it houses all control plane resources. Replace kube-system with another namespace to view its corresponding resources.

        kubectl get all -n kube-system
        

      Join a Worker Node to the Cluster

      Now that your Kubernetes master node is set up, you can join worker nodes to your cluster. In order for a worker node to join a cluster, it must trust the cluster’s control plane, and the control plane must trust the worker node. This trust is managed via a shared bootstrap token and a certificate authority (CA) key hash. kubeadm handles the exchange between the control plane and the worker node. At a high-level the worker node bootstrap process is the following:

      1. kubeadm retrieves information about the cluster from the Kubernetes API server. The bootstrap token and CA key hash are used to ensure the information originates from a trusted source.

      2. kubelet can take over and begin the bootstrap process, since it has the necessary cluster information retrieved in the previous step. The bootstrap token is used to gain access to the Kubernetes API server and submit a certificate signing request (CSR), which is then signed by the control plane.

      3. The worker node’s kubelet is now able to connect to the Kubernetes API server using the node’s established identity.

      Before continuing, you will need to make sure that you know your Kubernetes API server’s IP address, that you have a bootstrap token, and a CA key hash. This information was provided when kubeadm was initialized on the master node in the Set up the Kubernetes Control Plane section of this guide. If you no longer have this information, you can regenerate the necessary information from the master node.

      Regenerate a Bootstrap Token

      These commands should be issued from your master node.

      1. Generate a new bootstrap token and display the kubeadm join command with the necessary options to join a worker node to the master node’s control plane:

        kubeadm token create --print-join-command
        

      Follow the steps below on each node you would like to bootstrap to the cluster as a worker node.

      1. SSH into the Linode that will be used as a worker node in the Kubernetes cluster.

        ssh [email protected]
        
      2. Join the node to your cluster using kubeadm. Ensure you replace 192.0.2.0:6443 with the IP address for your master node along with its Kubernetes API server’s port number, udb8fn.nih6n1f1aijmbnx5 with your bootstrap token, and sha256:b7c01e83d63808a4a14d2813d28c127d3a1c4e1b6fc6ba605fe4d2789d654f26 with your CA key hash. The bootstrap process will take a few moments.

        sudo kubeadm join 192.0.2.0:6443 --token udb8fn.nih6n1f1aijmbnx5 
        --discovery-token-ca-cert-hash sha256:b7c01e83d63808a4a14d2813d28c127d3a1c4e1b6fc6ba605fe4d2789d654f26
        

        When the bootstrap process has completed, you should see a similar output:

          
          This node has joined the cluster:
        * Certificate signing request was sent to apiserver and a response was received.
        * The Kubelet was informed of the new secure connection details.
        
        Run 'kubectl get nodes' on the control-plane to see this node join the cluster.
              
        
      3. Repeat the steps outlined above on the second worker node to bootstrap it to the cluster.

      4. SSH into the master node and verify the worker nodes have joined the cluster:

         kubectl get nodes
        

        You should see a similar output.

          
        NAME          STATUS   ROLES    AGE     VERSION
        kube-master   Ready    master   1d22h   v1.14.1
        kube-node-1   Ready       1d22h   v1.14.1
        kube-node-2   Ready       1d22h   v1.14.1
              
        

      Next Steps

      Now that you have a Kubernetes cluster up and running, you can begin experimenting with the various ways to configure pods, group resources, and deploy services that are exposed to the public internet. To help you get started with this, move on to follow along with the Deploy a Static Site on Linode using Kubernetes guide.

      Tear Down Your Cluster

      If you are done experimenting with your Kubernetes Cluster, be sure to remove the Linodes you have running in order to avoid being further billed for them. See the Removing Services section of the Billing and Payments guide.

      More Information

      You may wish to consult the following resources for additional information on this topic. While these are provided in the hope that they will be useful, please note that we cannot vouch for the accuracy or timeliness of externally hosted materials.

      Find answers, ask questions, and help others.

      This guide is published under a CC BY-ND 4.0 license.



      Source link

      How To Create a Kubernetes Cluster Using Kubeadm on Debian 9


      The author selected the Free and Open Source Fund to receive a donation as part of the Write for DOnations program.

      Introduction

      Kubernetes is a container orchestration system that manages containers at scale. Initially developed by Google based on its experience running containers in production, Kubernetes is open source and actively developed by a community around the world.

      Note: This tutorial uses version 1.14 of Kubernetes, the official supported version at the time of this article’s publication. For up-to-date information on the latest version, please see the current release notes in the official Kubernetes documentation.

      Kubeadm automates the installation and configuration of Kubernetes components such as the API server, Controller Manager, and Kube DNS. It does not, however, create users or handle the installation of operating-system-level dependencies and their configuration. For these preliminary tasks, it is possible to use a configuration management tool like Ansible or SaltStack. Using these tools makes creating additional clusters or recreating existing clusters much simpler and less error prone.

      In this guide, you will set up a Kubernetes cluster from scratch using Ansible and Kubeadm, and then deploy a containerized Nginx application to it.

      Goals

      Your cluster will include the following physical resources:

      The master node (a node in Kubernetes refers to a server) is responsible for managing the state of the cluster. It runs Etcd, which stores cluster data among components that schedule workloads to worker nodes.

      Worker nodes are the servers where your workloads (i.e. containerized applications and services) will run. A worker will continue to run your workload once they’re assigned to it, even if the master goes down once scheduling is complete. A cluster’s capacity can be increased by adding workers.

      After completing this guide, you will have a cluster ready to run containerized applications, provided that the servers in the cluster have sufficient CPU and RAM resources for your applications to consume. Almost any traditional Unix application including web applications, databases, daemons, and command line tools can be containerized and made to run on the cluster. The cluster itself will consume around 300-500MB of memory and 10% of CPU on each node.

      Once the cluster is set up, you will deploy the web server Nginx to it to ensure that it is running workloads correctly.

      Prerequisites

      Step 1 — Setting Up the Workspace Directory and Ansible Inventory File

      In this section, you will create a directory on your local machine that will serve as your workspace. You will configure Ansible locally so that it can communicate with and execute commands on your remote servers. Once that’s done, you will create a hosts file containing inventory information such as the IP addresses of your servers and the groups that each server belongs to.

      Out of your three servers, one will be the master with an IP displayed as master_ip. The other two servers will be workers and will have the IPs worker_1_ip and worker_2_ip.

      Create a directory named ~/kube-cluster in the home directory of your local machine and cd into it:

      • mkdir ~/kube-cluster
      • cd ~/kube-cluster

      This directory will be your workspace for the rest of the tutorial and will contain all of your Ansible playbooks. It will also be the directory inside which you will run all local commands.

      Create a file named ~/kube-cluster/hosts using nano or your favorite text editor:

      • nano ~/kube-cluster/hosts

      Add the following text to the file, which will specify information about the logical structure of your cluster:

      ~/kube-cluster/hosts

      [masters]
      master ansible_host=master_ip ansible_user=root
      
      [workers]
      worker1 ansible_host=worker_1_ip ansible_user=root
      worker2 ansible_host=worker_2_ip ansible_user=root
      
      [all:vars]
      ansible_python_interpreter=/usr/bin/python3
      

      You may recall that inventory files in Ansible are used to specify server information such as IP addresses, remote users, and groupings of servers to target as a single unit for executing commands. ~/kube-cluster/hosts will be your inventory file and you’ve added two Ansible groups (masters and workers) to it specifying the logical structure of your cluster.

      In the masters group, there is a server entry named “master” that lists the master node’s IP (master_ip) and specifies that Ansible should run remote commands as the root user.

      Similarly, in the workers group, there are two entries for the worker servers (worker_1_ip and worker_2_ip) that also specify the ansible_user as root.

      The last line of the file tells Ansible to use the remote servers’ Python 3 interpreters for its management operations.

      Save and close the file after you’ve added the text.

      Having set up the server inventory with groups, let’s move on to installing operating system level dependencies and creating configuration settings.

      Step 2 — Creating a Non-Root User on All Remote Servers

      In this section you will create a non-root user with sudo privileges on all servers so that you can SSH into them manually as an unprivileged user. This can be useful if, for example, you would like to see system information with commands such as top/htop, view a list of running containers, or change configuration files owned by root. These operations are routinely performed during the maintenance of a cluster, and using a non-root user for such tasks minimizes the risk of modifying or deleting important files or unintentionally performing other dangerous operations.

      Create a file named ~/kube-cluster/initial.yml in the workspace:

      • nano ~/kube-cluster/initial.yml

      Next, add the following play to the file to create a non-root user with sudo privileges on all of the servers. A play in Ansible is a collection of steps to be performed that target specific servers and groups. The following play will create a non-root sudo user:

      ~/kube-cluster/initial.yml

      - hosts: all
        become: yes
        tasks:
          - name: create the 'sammy' user
            user: name=sammy append=yes state=present createhome=yes shell=/bin/bash
      
          - name: allow 'sammy' to have passwordless sudo
            lineinfile:
              dest: /etc/sudoers
              line: 'sammy ALL=(ALL) NOPASSWD: ALL'
              validate: 'visudo -cf %s'
      
          - name: set up authorized keys for the sammy user
            authorized_key: user=sammy key="{{item}}"
            with_file:
              - ~/.ssh/id_rsa.pub
      

      Here’s a breakdown of what this playbook does:

      • Creates the non-root user sammy.

      • Configures the sudoers file to allow the sammy user to run sudo commands without a password prompt.

      • Adds the public key in your local machine (usually ~/.ssh/id_rsa.pub) to the remote sammy user’s authorized key list. This will allow you to SSH into each server as the sammy user.

      Save and close the file after you’ve added the text.

      Next, execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/initial.yml

      The command will complete within two to five minutes. On completion, you will see output similar to the following:

      Output

      PLAY [all] **** TASK [Gathering Facts] **** ok: [master] ok: [worker1] ok: [worker2] TASK [create the 'sammy' user] **** changed: [master] changed: [worker1] changed: [worker2] TASK [allow 'sammy' user to have passwordless sudo] **** changed: [master] changed: [worker1] changed: [worker2] TASK [set up authorized keys for the sammy user] **** changed: [worker1] => (item=ssh-rsa AAAAB3...) changed: [worker2] => (item=ssh-rsa AAAAB3...) changed: [master] => (item=ssh-rsa AAAAB3...) PLAY RECAP **** master : ok=5 changed=4 unreachable=0 failed=0 worker1 : ok=5 changed=4 unreachable=0 failed=0 worker2 : ok=5 changed=4 unreachable=0 failed=0

      Now that the preliminary setup is complete, you can move on to installing Kubernetes-specific dependencies.

      Step 3 — Installing Kubernetes Dependencies

      In this section, you will install the operating-system-level packages required by Kubernetes with Debian’s package manager. These packages are:

      • Docker – a container runtime. It is the component that runs your containers. Support for other runtimes such as rkt is under active development in Kubernetes.

      • kubeadm – a CLI tool that will install and configure the various components of a cluster in a standard way.

      • kubelet – a system service/program that runs on all nodes and handles node-level operations.

      • kubectl – a CLI tool used for issuing commands to the cluster through its API Server.

      Create a file named ~/kube-cluster/kube-dependencies.yml in the workspace:

      • nano ~/kube-cluster/kube-dependencies.yml

      Add the following plays to the file to install these packages to your servers:

      ~/kube-cluster/kube-dependencies.yml

      - hosts: all
        become: yes
        tasks:
         - name: install remote apt deps
           apt:
             name: "{{ item }}"
             state: present
           with_items:
             - apt-transport-https
             - ca-certificates
             - gnupg2
             - software-properties-common
      
         - name: add Docker apt-key
           apt_key:
             url: https://download.docker.com/linux/debian/gpg
             state: present
      
         - name: add Docker's APT repository
           apt_repository:
            repo: deb https://download.docker.com/linux/debian stretch stable
            state: present
            filename: 'docker'
      
         - name: install Docker
           apt:
             name: docker-ce
             state: present
             update_cache: true
      
         - name: add Kubernetes apt-key
           apt_key:
             url: https://packages.cloud.google.com/apt/doc/apt-key.gpg
             state: present
      
         - name: add Kubernetes' APT repository
           apt_repository:
            repo: deb http://apt.kubernetes.io/ kubernetes-xenial main
            state: present
            filename: 'kubernetes'
      
         - name: install kubelet
           apt:
             name: kubelet=1.14.0-00
             state: present
             update_cache: true
      
         - name: install kubeadm
           apt:
             name: kubeadm=1.14.0-00
             state: present
      
      - hosts: master
        become: yes
        tasks:
         - name: install kubectl
           apt:
             name: kubectl=1.14.0-00
             state: present
             force: yes
      

      The first play in the playbook does the following:

      • Add dependencies for adding, verifying and installing packages from remote repositories.

      • Adds the Docker APT repository’s apt-key for key verification.

      • Installs Docker, the container runtime.

      • Adds the Kubernetes APT repository’s apt-key for key verification.

      • Adds the Kubernetes APT repository to your remote servers’ APT sources list.

      • Installs kubelet and kubeadm.

      The second play consists of a single task that installs kubectl on your master node.

      Note: While the Kubernetes documentation recommends you use the latest stable release of Kubernetes for your environment, this tutorial uses a specific version. This will ensure that you can follow the steps successfully, as Kubernetes changes rapidly and the latest version may not work with this tutorial.

      Save and close the file when you are finished.

      Next, execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/kube-dependencies.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [all] **** TASK [Gathering Facts] **** ok: [worker1] ok: [worker2] ok: [master] TASK [install Docker] **** changed: [master] changed: [worker1] changed: [worker2] TASK [install APT Transport HTTPS] ***** ok: [master] ok: [worker1] changed: [worker2] TASK [add Kubernetes apt-key] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [add Kubernetes' APT repository] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [install kubelet] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [install kubeadm] ***** changed: [master] changed: [worker1] changed: [worker2] PLAY [master] ***** TASK [Gathering Facts] ***** ok: [master] TASK [install kubectl] ****** ok: [master] PLAY RECAP **** master : ok=9 changed=5 unreachable=0 failed=0 worker1 : ok=7 changed=5 unreachable=0 failed=0 worker2 : ok=7 changed=5 unreachable=0 failed=0

      After execution, Docker, kubeadm, and kubelet will be installed on all of the remote servers. kubectl is not a required component and is only needed for executing cluster commands. Installing it only on the master node makes sense in this context, since you will run kubectl commands only from the master. Note, however, that kubectl commands can be run from any of the worker nodes or from any machine where it can be installed and configured to point to a cluster.

      All system dependencies are now installed. Let’s set up the master node and initialize the cluster.

      Step 4 — Setting Up the Master Node

      In this section, you will set up the master node. Before creating any playbooks, however, it’s worth covering a few concepts such as Pods and Pod Network Plugins, since your cluster will include both.

      A pod is an atomic unit that runs one or more containers. These containers share resources such as file volumes and network interfaces in common. Pods are the basic unit of scheduling in Kubernetes: all containers in a pod are guaranteed to run on the same node that the pod is scheduled on.

      Each pod has its own IP address, and a pod on one node should be able to access a pod on another node using the pod’s IP. Containers on a single node can communicate easily through a local interface. Communication between pods is more complicated, however, and requires a separate networking component that can transparently route traffic from a pod on one node to a pod on another.

      This functionality is provided by pod network plugins. For this cluster, you will use Flannel, a stable and performant option.

      Create an Ansible playbook named master.yml on your local machine:

      • nano ~/kube-cluster/master.yml

      Add the following play to the file to initialize the cluster and install Flannel:

      ~/kube-cluster/master.yml

      - hosts: master
        become: yes
        tasks:
          - name: initialize the cluster
            shell: kubeadm init --pod-network-cidr=10.244.0.0/16 >> cluster_initialized.txt
            args:
              chdir: $HOME
              creates: cluster_initialized.txt
      
          - name: create .kube directory
            become: yes
            become_user: sammy
            file:
              path: $HOME/.kube
              state: directory
              mode: 0755
      
          - name: copy admin.conf to user's kube config
            copy:
              src: /etc/kubernetes/admin.conf
              dest: /home/sammy/.kube/config
              remote_src: yes
              owner: sammy
      
          - name: install Pod network
            become: yes
            become_user: sammy
            shell: kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/a70459be0084506e4ec919aa1c114638878db11b/Documentation/kube-flannel.yml >> pod_network_setup.txt
            args:
              chdir: $HOME
              creates: pod_network_setup.txt
      

      Here’s a breakdown of this play:

      • The first task initializes the cluster by running kubeadm init. Passing the argument --pod-network-cidr=10.244.0.0/16 specifies the private subnet that the pod IPs will be assigned from. Flannel uses the above subnet by default; we’re telling kubeadm to use the same subnet.

      • The second task creates a .kube directory at /home/sammy. This directory will hold configuration information such as the admin key files, which are required to connect to the cluster, and the cluster’s API address.

      • The third task copies the /etc/kubernetes/admin.conf file that was generated from kubeadm init to your non-root user’s home directory. This will allow you to use kubectl to access the newly-created cluster.

      • The last task runs kubectl apply to install Flannel. kubectl apply -f descriptor.[yml|json] is the syntax for telling kubectl to create the objects described in the descriptor.[yml|json] file. The kube-flannel.yml file contains the descriptions of objects required for setting up Flannel in the cluster.

      Save and close the file when you are finished.

      Execute the playbook locally by running:

      • ansible-playbook -i hosts ~/kube-cluster/master.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [master] **** TASK [Gathering Facts] **** ok: [master] TASK [initialize the cluster] **** changed: [master] TASK [create .kube directory] **** changed: [master] TASK [copy admin.conf to user's kube config] ***** changed: [master] TASK [install Pod network] ***** changed: [master] PLAY RECAP **** master : ok=5 changed=4 unreachable=0 failed=0

      To check the status of the master node, SSH into it with the following command:

      Once inside the master node, execute:

      You will now see the following output:

      Output

      NAME STATUS ROLES AGE VERSION master Ready master 1d v1.14.0

      The output states that the master node has completed all initialization tasks and is in a Ready state from which it can start accepting worker nodes and executing tasks sent to the API Server. You can now add the workers from your local machine.

      Step 5 — Setting Up the Worker Nodes

      Adding workers to the cluster involves executing a single command on each. This command includes the necessary cluster information, such as the IP address and port of the master's API Server, and a secure token. Only nodes that pass in the secure token will be able join the cluster.

      Navigate back to your workspace and create a playbook named workers.yml:

      • nano ~/kube-cluster/workers.yml

      Add the following text to the file to add the workers to the cluster:

      ~/kube-cluster/workers.yml

      - hosts: master
        become: yes
        gather_facts: false
        tasks:
          - name: get join command
            shell: kubeadm token create --print-join-command
            register: join_command_raw
      
          - name: set join command
            set_fact:
              join_command: "{{ join_command_raw.stdout_lines[0] }}"
      
      
      - hosts: workers
        become: yes
        tasks:
          - name: join cluster
            shell: "{{ hostvars['master'].join_command }} >> node_joined.txt"
            args:
              chdir: $HOME
              creates: node_joined.txt
      

      Here's what the playbook does:

      • The first play gets the join command that needs to be run on the worker nodes. This command will be in the following format:kubeadm join --token <token> <master-ip>:<master-port> --discovery-token-ca-cert-hash sha256:<hash>. Once it gets the actual command with the proper token and hash values, the task sets it as a fact so that the next play will be able to access that info.

      • The second play has a single task that runs the join command on all worker nodes. On completion of this task, the two worker nodes will be part of the cluster.

      Save and close the file when you are finished.

      Execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/workers.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [master] **** TASK [get join command] **** changed: [master] TASK [set join command] ***** ok: [master] PLAY [workers] ***** TASK [Gathering Facts] ***** ok: [worker1] ok: [worker2] TASK [join cluster] ***** changed: [worker1] changed: [worker2] PLAY RECAP ***** master : ok=2 changed=1 unreachable=0 failed=0 worker1 : ok=2 changed=1 unreachable=0 failed=0 worker2 : ok=2 changed=1 unreachable=0 failed=0

      With the addition of the worker nodes, your cluster is now fully set up and functional, with workers ready to run workloads. Before scheduling applications, let's verify that the cluster is working as intended.

      Step 6 — Verifying the Cluster

      A cluster can sometimes fail during setup because a node is down or network connectivity between the master and worker is not working correctly. Let's verify the cluster and ensure that the nodes are operating correctly.

      You will need to check the current state of the cluster from the master node to ensure that the nodes are ready. If you disconnected from the master node, you can SSH back into it with the following command:

      Then execute the following command to get the status of the cluster:

      You will see output similar to the following:

      Output

      NAME STATUS ROLES AGE VERSION master Ready master 1d v1.14.0 worker1 Ready <none> 1d v1.14.0 worker2 Ready <none> 1d v1.14.0

      If all of your nodes have the value Ready for STATUS, it means that they're part of the cluster and ready to run workloads.

      If, however, a few of the nodes have NotReady as the STATUS, it could mean that the worker nodes haven't finished their setup yet. Wait for around five to ten minutes before re-running kubectl get nodes and inspecting the new output. If a few nodes still have NotReady as the status, you might have to verify and re-run the commands in the previous steps.

      Now that your cluster is verified successfully, let's schedule an example Nginx application on the cluster.

      Step 7 — Running An Application on the Cluster

      You can now deploy any containerized application to your cluster. To keep things familiar, let's deploy Nginx using Deployments and Services to see how this application can be deployed to the cluster. You can use the commands below for other containerized applications as well, provided you change the Docker image name and any relevant flags (such as ports and volumes).

      Still within the master node, execute the following command to create a deployment named nginx:

      • kubectl create deployment nginx --image=nginx

      A deployment is a type of Kubernetes object that ensures there's always a specified number of pods running based on a defined template, even if the pod crashes during the cluster's lifetime. The above deployment will create a pod with one container from the Docker registry's Nginx Docker Image.

      Next, run the following command to create a service named nginx that will expose the app publicly. It will do so through a NodePort, a scheme that will make the pod accessible through an arbitrary port opened on each node of the cluster:

      • kubectl expose deploy nginx --port 80 --target-port 80 --type NodePort

      Services are another type of Kubernetes object that expose cluster internal services to clients, both internal and external. They are also capable of load balancing requests to multiple pods, and are an integral component in Kubernetes, frequently interacting with other components.

      Run the following command:

      This will output text similar to the following:

      Output

      NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 1d nginx NodePort 10.109.228.209 <none> 80:nginx_port/TCP 40m

      From the third line of the above output, you can retrieve the port that Nginx is running on. Kubernetes will assign a random port that is greater than 30000 automatically, while ensuring that the port is not already bound by another service.

      To test that everything is working, visit http://worker_1_ip:nginx_port or http://worker_2_ip:nginx_port through a browser on your local machine. You will see Nginx's familiar welcome page.

      If you would like to remove the Nginx application, first delete the nginx service from the master node:

      • kubectl delete service nginx

      Run the following to ensure that the service has been deleted:

      You will see the following output:

      Output

      NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 1d

      Then delete the deployment:

      • kubectl delete deployment nginx

      Run the following to confirm that this worked:

      Output

      No resources found.

      Conclusion

      In this guide, you've successfully set up a Kubernetes cluster on Debian 9 using Kubeadm and Ansible for automation.

      If you're wondering what to do with the cluster now that it's set up, a good next step would be to get comfortable deploying your own applications and services onto the cluster. Here's a list of links with further information that can guide you in the process:

      • Dockerizing applications - lists examples that detail how to containerize applications using Docker.

      • Pod Overview - describes in detail how Pods work and their relationship with other Kubernetes objects. Pods are ubiquitous in Kubernetes, so understanding them will facilitate your work.

      • Deployments Overview - provides an overview of deployments. It is useful to understand how controllers such as deployments work since they are used frequently in stateless applications for scaling and the automated healing of unhealthy applications.

      • Services Overview - covers services, another frequently used object in Kubernetes clusters. Understanding the types of services and the options they have is essential for running both stateless and stateful applications.

      Other important concepts that you can look into are Volumes, Ingresses and Secrets, all of which come in handy when deploying production applications.

      Kubernetes has a lot of functionality and features to offer. The Kubernetes Official Documentation is the best place to learn about concepts, find task-specific guides, and look up API references for various objects.



      Source link

      How To Create a Kubernetes 1.11 Cluster Using Kubeadm on Ubuntu 18.04


      The author selected the Free and Open Source Fund to receive a donation as part of the Write for DOnations program.

      Introduction

      Kubernetes is a container orchestration system that manages containers at scale. Initially developed by Google based on its experience running containers in production, Kubernetes is open source and actively developed by a community around the world.

      Kubeadm automates the installation and configuration of Kubernetes components such as the API server, Controller Manager, and Kube DNS. It does not, however, create users or handle the installation of operating-system-level dependencies and their configuration. For these preliminary tasks, it is possible to use a configuration management tool like Ansible or SaltStack. Using these tools makes creating additional clusters or recreating existing clusters much simpler and less error prone.

      In this guide, you will set up a Kubernetes cluster from scratch using Ansible and Kubeadm, and then deploy a containerized Nginx application to it.

      Goals

      Your cluster will include the following physical resources:

      The master node (a node in Kubernetes refers to a server) is responsible for managing the state of the cluster. It runs Etcd, which stores cluster data among components that schedule workloads to worker nodes.

      Worker nodes are the servers where your workloads (i.e. containerized applications and services) will run. A worker will continue to run your workload once they’re assigned to it, even if the master goes down once scheduling is complete. A cluster’s capacity can be increased by adding workers.

      After completing this guide, you will have a cluster ready to run containerized applications, provided that the servers in the cluster have sufficient CPU and RAM resources for your applications to consume. Almost any traditional Unix application including web applications, databases, daemons, and command line tools can be containerized and made to run on the cluster. The cluster itself will consume around 300-500MB of memory and 10% of CPU on each node.

      Once the cluster is set up, you will deploy the web server Nginx to it to ensure that it is running workloads correctly.

      Prerequisites

      Step 1 — Setting Up the Workspace Directory and Ansible Inventory File

      In this section, you will create a directory on your local machine that will serve as your workspace. You will configure Ansible locally so that it can communicate with and execute commands on your remote servers. Once that’s done, you will create a hosts file containing inventory information such as the IP addresses of your servers and the groups that each server belongs to.

      Out of your three servers, one will be the master with an IP displayed as master_ip. The other two servers will be workers and will have the IPs worker_1_ip and worker_2_ip.

      Create a directory named ~/kube-cluster in the home directory of your local machine and cd into it:

      • mkdir ~/kube-cluster
      • cd ~/kube-cluster

      This directory will be your workspace for the rest of the tutorial and will contain all of your Ansible playbooks. It will also be the directory inside which you will run all local commands.

      Create a file named ~/kube-cluster/hosts using nano or your favorite text editor:

      • nano ~/kube-cluster/hosts

      Add the following text to the file, which will specify information about the logical structure of your cluster:

      ~/kube-cluster/hosts

      [masters]
      master ansible_host=master_ip ansible_user=root
      
      [workers]
      worker1 ansible_host=worker_1_ip ansible_user=root
      worker2 ansible_host=worker_2_ip ansible_user=root
      
      [all:vars]
      ansible_python_interpreter=/usr/bin/python3
      

      You may recall that inventory files in Ansible are used to specify server information such as IP addresses, remote users, and groupings of servers to target as a single unit for executing commands. ~/kube-cluster/hosts will be your inventory file and you’ve added two Ansible groups (masters and workers) to it specifying the logical structure of your cluster.

      In the masters group, there is a server entry named “master” that lists the master node’s IP (master_ip) and specifies that Ansible should run remote commands as the root user.

      Similarly, in the workers group, there are two entries for the worker servers (worker_1_ip and worker_2_ip) that also specify the ansible_user as root.

      The last line of the file tells Ansible to use the remote servers’ Python 3 interpreters for its management operations.

      Save and close the file after you’ve added the text.

      Having set up the server inventory with groups, let’s move on to installing operating system level dependencies and creating configuration settings.

      Step 2 — Creating a Non-Root User on All Remote Servers

      In this section you will create a non-root user with sudo privileges on all servers so that you can SSH into them manually as an unprivileged user. This can be useful if, for example, you would like to see system information with commands such as top/htop, view a list of running containers, or change configuration files owned by root. These operations are routinely performed during the maintenance of a cluster, and using a non-root user for such tasks minimizes the risk of modifying or deleting important files or unintentionally performing other dangerous operations.

      Create a file named ~/kube-cluster/initial.yml in the workspace:

      • nano ~/kube-cluster/initial.yml

      Next, add the following play to the file to create a non-root user with sudo privileges on all of the servers. A play in Ansible is a collection of steps to be performed that target specific servers and groups. The following play will create a non-root sudo user:

      ~/kube-cluster/initial.yml

      - hosts: all
        become: yes
        tasks:
          - name: create the 'ubuntu' user
            user: name=ubuntu append=yes state=present createhome=yes shell=/bin/bash
      
          - name: allow 'ubuntu' to have passwordless sudo
            lineinfile:
              dest: /etc/sudoers
              line: 'ubuntu ALL=(ALL) NOPASSWD: ALL'
              validate: 'visudo -cf %s'
      
          - name: set up authorized keys for the ubuntu user
            authorized_key: user=ubuntu key="{{item}}"
            with_file:
              - ~/.ssh/id_rsa.pub
      

      Here’s a breakdown of what this playbook does:

      • Creates the non-root user ubuntu.

      • Configures the sudoers file to allow the ubuntu user to run sudo commands without a password prompt.

      • Adds the public key in your local machine (usually ~/.ssh/id_rsa.pub) to the remote ubuntu user’s authorized key list. This will allow you to SSH into each server as the ubuntu user.

      Save and close the file after you’ve added the text.

      Next, execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/initial.yml

      The command will complete within two to five minutes. On completion, you will see output similar to the following:

      Output

      PLAY [all] **** TASK [Gathering Facts] **** ok: [master] ok: [worker1] ok: [worker2] TASK [create the 'ubuntu' user] **** changed: [master] changed: [worker1] changed: [worker2] TASK [allow 'ubuntu' user to have passwordless sudo] **** changed: [master] changed: [worker1] changed: [worker2] TASK [set up authorized keys for the ubuntu user] **** changed: [worker1] => (item=ssh-rsa AAAAB3...) changed: [worker2] => (item=ssh-rsa AAAAB3...) changed: [master] => (item=ssh-rsa AAAAB3...) PLAY RECAP **** master : ok=5 changed=4 unreachable=0 failed=0 worker1 : ok=5 changed=4 unreachable=0 failed=0 worker2 : ok=5 changed=4 unreachable=0 failed=0

      Now that the preliminary setup is complete, you can move on to installing Kubernetes-specific dependencies.

      Step 3 — Installing Kubernetetes’ Dependencies

      In this section, you will install the operating-system-level packages required by Kubernetes with Ubuntu’s package manager. These packages are:

      • Docker – a container runtime. It is the component that runs your containers. Support for other runtimes such as rkt is under active development in Kubernetes.

      • kubeadm – a CLI tool that will install and configure the various components of a cluster in a standard way.

      • kubelet – a system service/program that runs on all nodes and handles node-level operations.

      • kubectl – a CLI tool used for issuing commands to the cluster through its API Server.

      Create a file named ~/kube-cluster/kube-dependencies.yml in the workspace:

      • nano ~/kube-cluster/kube-dependencies.yml

      Add the following plays to the file to install these packages to your servers:

      ~/kube-cluster/kube-dependencies.yml

      - hosts: all
        become: yes
        tasks:
         - name: install Docker
           apt:
             name: docker.io
             state: present
             update_cache: true
      
         - name: install APT Transport HTTPS
           apt:
             name: apt-transport-https
             state: present
      
         - name: add Kubernetes apt-key
           apt_key:
             url: https://packages.cloud.google.com/apt/doc/apt-key.gpg
             state: present
      
         - name: add Kubernetes' APT repository
           apt_repository:
            repo: deb http://apt.kubernetes.io/ kubernetes-xenial main
            state: present
            filename: 'kubernetes'
      
         - name: install kubelet
           apt:
             name: kubelet
             state: present
             update_cache: true
      
         - name: install kubeadm
           apt:
             name: kubeadm
             state: present
      
      - hosts: master
        become: yes
        tasks:
         - name: install kubectl
           apt:
             name: kubectl
             state: present
      

      The first play in the playbook does the following:

      • Installs Docker, the container runtime.

      • Installs apt-transport-https, allowing you to add external HTTPS sources to your APT sources list.

      • Adds the Kubernetes APT repository’s apt-key for key verification.

      • Adds the Kubernetes APT repository to your remote servers’ APT sources list.

      • Installs kubelet and kubeadm.

      The second play consists of a single task that installs kubectl on your master node.

      Save and close the file when you are finished.

      Next, execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/kube-dependencies.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [all] **** TASK [Gathering Facts] **** ok: [worker1] ok: [worker2] ok: [master] TASK [install Docker] **** changed: [master] changed: [worker1] changed: [worker2] TASK [install APT Transport HTTPS] ***** ok: [master] ok: [worker1] changed: [worker2] TASK [add Kubernetes apt-key] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [add Kubernetes' APT repository] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [install kubelet] ***** changed: [master] changed: [worker1] changed: [worker2] TASK [install kubeadm] ***** changed: [master] changed: [worker1] changed: [worker2] PLAY [master] ***** TASK [Gathering Facts] ***** ok: [master] TASK [install kubectl] ****** ok: [master] PLAY RECAP **** master : ok=9 changed=5 unreachable=0 failed=0 worker1 : ok=7 changed=5 unreachable=0 failed=0 worker2 : ok=7 changed=5 unreachable=0 failed=0

      After execution, Docker, kubeadm, and kubelet will be installed on all of the remote servers. kubectl is not a required component and is only needed for executing cluster commands. Installing it only on the master node makes sense in this context, since you will run kubectl commands only from the master. Note, however, that kubectl commands can be run from any of the worker nodes or from any machine where it can be installed and configured to point to a cluster.

      All system dependencies are now installed. Let’s set up the master node and initialize the cluster.

      Step 4 — Setting Up the Master Node

      In this section, you will set up the master node. Before creating any playbooks, however, it’s worth covering a few concepts such as Pods and Pod Network Plugins, since your cluster will include both.

      A pod is an atomic unit that runs one or more containers. These containers share resources such as file volumes and network interfaces in common. Pods are the basic unit of scheduling in Kubernetes: all containers in a pod are guaranteed to run on the same node that the pod is scheduled on.

      Each pod has its own IP address, and a pod on one node should be able to access a pod on another node using the pod’s IP. Containers on a single node can communicate easily through a local interface. Communication between pods is more complicated, however, and requires a separate networking component that can transparently route traffic from a pod on one node to a pod on another.

      This functionality is provided by pod network plugins. For this cluster, you will use Flannel, a stable and performant option.

      Create an Ansible playbook named master.yml on your local machine:

      • nano ~/kube-cluster/master.yml

      Add the following play to the file to initialize the cluster and install Flannel:

      ~/kube-cluster/master.yml

      - hosts: master
        become: yes
        tasks:
          - name: initialize the cluster
            shell: kubeadm init --pod-network-cidr=10.244.0.0/16 >> cluster_initialized.txt
            args:
              chdir: $HOME
              creates: cluster_initialized.txt
      
          - name: create .kube directory
            become: yes
            become_user: ubuntu
            file:
              path: $HOME/.kube
              state: directory
              mode: 0755
      
          - name: copy admin.conf to user's kube config
            copy:
              src: /etc/kubernetes/admin.conf
              dest: /home/ubuntu/.kube/config
              remote_src: yes
              owner: ubuntu
      
          - name: install Pod network
            become: yes
            become_user: ubuntu
            shell: kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/v0.9.1/Documentation/kube-flannel.yml >> pod_network_setup.txt
            args:
              chdir: $HOME
              creates: pod_network_setup.txt
      

      Here’s a breakdown of this play:

      • The first task initializes the cluster by running kubeadm init. Passing the argument --pod-network-cidr=10.244.0.0/16 specifies the private subnet that the pod IPs will be assigned from. Flannel uses the above subnet by default; we’re telling kubeadm to use the same subnet.

      • The second task creates a .kube directory at /home/ubuntu. This directory will hold configuration information such as the admin key files, which are required to connect to the cluster, and the cluster’s API address.

      • The third task copies the /etc/kubernetes/admin.conf file that was generated from kubeadm init to your non-root user’s home directory. This will allow you to use kubectl to access the newly-created cluster.

      • The last task runs kubectl apply to install Flannel. kubectl apply -f descriptor.[yml|json] is the syntax for telling kubectl to create the objects described in the descriptor.[yml|json] file. The kube-flannel.yml file contains the descriptions of objects required for setting up Flannel in the cluster.

      Save and close the file when you are finished.

      Execute the playbook locally by running:

      • ansible-playbook -i hosts ~/kube-cluster/master.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [master] **** TASK [Gathering Facts] **** ok: [master] TASK [initialize the cluster] **** changed: [master] TASK [create .kube directory] **** changed: [master] TASK [copy admin.conf to user's kube config] ***** changed: [master] TASK [install Pod network] ***** changed: [master] PLAY RECAP **** master : ok=5 changed=4 unreachable=0 failed=0

      To check the status of the master node, SSH into it with the following command:

      Once inside the master node, execute:

      You will now see the following output:

      Output

      NAME STATUS ROLES AGE VERSION master Ready master 1d v1.11.1

      The output states that the master node has completed all initialization tasks and is in a Ready state from which it can start accepting worker nodes and executing tasks sent to the API Server. You can now add the workers from your local machine.

      Step 5 — Setting Up the Worker Nodes

      Adding workers to the cluster involves executing a single command on each. This command includes the necessary cluster information, such as the IP address and port of the master's API Server, and a secure token. Only nodes that pass in the secure token will be able join the cluster.

      Navigate back to your workspace and create a playbook named workers.yml:

      • nano ~/kube-cluster/workers.yml

      Add the following text to the file to add the workers to the cluster:

      ~/kube-cluster/workers.yml

      - hosts: master
        become: yes
        gather_facts: false
        tasks:
          - name: get join command
            shell: kubeadm token create --print-join-command
            register: join_command_raw
      
          - name: set join command
            set_fact:
              join_command: "{{ join_command_raw.stdout_lines[0] }}"
      
      
      - hosts: workers
        become: yes
        tasks:
          - name: join cluster
            shell: "{{ hostvars['master'].join_command }} >> node_joined.txt"
            args:
              chdir: $HOME
              creates: node_joined.txt
      

      Here's what the playbook does:

      • The first play gets the join command that needs to be run on the worker nodes. This command will be in the following format:kubeadm join --token <token> <master-ip>:<master-port> --discovery-token-ca-cert-hash sha256:<hash>. Once it gets the actual command with the proper token and hash values, the task sets it as a fact so that the next play will be able to access that info.

      • The second play has a single task that runs the join command on all worker nodes. On completion of this task, the two worker nodes will be part of the cluster.

      Save and close the file when you are finished.

      Execute the playbook by locally running:

      • ansible-playbook -i hosts ~/kube-cluster/workers.yml

      On completion, you will see output similar to the following:

      Output

      PLAY [master] **** TASK [get join command] **** changed: [master] TASK [set join command] ***** ok: [master] PLAY [workers] ***** TASK [Gathering Facts] ***** ok: [worker1] ok: [worker2] TASK [join cluster] ***** changed: [worker1] changed: [worker2] PLAY RECAP ***** master : ok=2 changed=1 unreachable=0 failed=0 worker1 : ok=2 changed=1 unreachable=0 failed=0 worker2 : ok=2 changed=1 unreachable=0 failed=0

      With the addition of the worker nodes, your cluster is now fully set up and functional, with workers ready to run workloads. Before scheduling applications, let's verify that the cluster is working as intended.

      Step 6 — Verifying the Cluster

      A cluster can sometimes fail during setup because a node is down or network connectivity between the master and worker is not working correctly. Let's verify the cluster and ensure that the nodes are operating correctly.

      You will need to check the current state of the cluster from the master node to ensure that the nodes are ready. If you disconnected from the master node, you can SSH back into it with the following command:

      Then execute the following command to get the status of the cluster:

      You will see output similar to the following:

      Output

      NAME STATUS ROLES AGE VERSION master Ready master 1d v1.11.1 worker1 Ready <none> 1d v1.11.1 worker2 Ready <none> 1d v1.11.1

      If all of your nodes have the value Ready for STATUS, it means that they're part of the cluster and ready to run workloads.

      If, however, a few of the nodes have NotReady as the STATUS, it could mean that the worker nodes haven't finished their setup yet. Wait for around five to ten minutes before re-running kubectl get nodes and inspecting the new output. If a few nodes still have NotReady as the status, you might have to verify and re-run the commands in the previous steps.

      Now that your cluster is verified successfully, let's schedule an example Nginx application on the cluster.

      Step 7 — Running An Application on the Cluster

      You can now deploy any containerized application to your cluster. To keep things familiar, let's deploy Nginx using Deployments and Services to see how this application can be deployed to the cluster. You can use the commands below for other containerized applications as well, provided you change the Docker image name and any relevant flags (such as ports and volumes).

      Still within the master node, execute the following command to create a deployment named nginx:

      • kubectl run nginx --image=nginx --port 80

      A deployment is a type of Kubernetes object that ensures there's always a specified number of pods running based on a defined template, even if the pod crashes during the cluster's lifetime. The above deployment will create a pod with one container from the Docker registry's Nginx Docker Image.

      Next, run the following command to create a service named nginx that will expose the app publicly. It will do so through a NodePort, a scheme that will make the pod accessible through an arbitrary port opened on each node of the cluster:

      • kubectl expose deploy nginx --port 80 --target-port 80 --type NodePort

      Services are another type of Kubernetes object that expose cluster internal services to clients, both internal and external. They are also capable of load balancing requests to multiple pods, and are an integral component in Kubernetes, frequently interacting with other components.

      Run the following command:

      This will output text similar to the following:

      Output

      NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 1d nginx NodePort 10.109.228.209 <none> 80:nginx_port/TCP 40m

      From the third line of the above output, you can retrieve the port that Nginx is running on. Kubernetes will assign a random port that is greater than 30000 automatically, while ensuring that the port is not already bound by another service.

      To test that everything is working, visit http://worker_1_ip:nginx_port or http://worker_2_ip:nginx_port through a browser on your local machine. You will see Nginx's familiar welcome page.

      If you would like to remove the Nginx application, first delete the nginx service from the master node:

      • kubectl delete service nginx

      Run the following to ensure that the service has been deleted:

      You will see the following output:

      Output

      NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 <none> 443/TCP 1d

      Then delete the deployment:

      • kubectl delete deployment nginx

      Run the following to confirm that this worked:

      Output

      No resources found.

      Conclusion

      In this guide, you've successfully set up a Kubernetes cluster on Ubuntu 18.04 using Kubeadm and Ansible for automation.

      If you're wondering what to do with the cluster now that it's set up, a good next step would be to get comfortable deploying your own applications and services onto the cluster. Here's a list of links with further information that can guide you in the process:

      • Dockerizing applications - lists examples that detail how to containerize applications using Docker.

      • Pod Overview - describes in detail how Pods work and their relationship with other Kubernetes objects. Pods are ubiquitous in Kubernetes, so understanding them will facilitate your work.

      • Deployments Overview - provides an overview of deployments. It is useful to understand how controllers such as deployments work since they are used frequently in stateless applications for scaling and the automated healing of unhealthy applications.

      • Services Overview - covers services, another frequently used object in Kubernetes clusters. Understanding the types of services and the options they have is essential for running both stateless and stateful applications.

      Other important concepts that you can look into are Volumes, Ingresses and Secrets, all of which come in handy when deploying production applications.

      Kubernetes has a lot of functionality and features to offer. The Kubernetes Official Documentation is the best place to learn about concepts, find task-specific guides, and look up API references for various objects.



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