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  • # Setting up your first cluster with Kubespray
    
    This tutorial walks you through the detailed steps for setting up Kubernetes
    with [Kubespray](https://kubespray.io/).
    
    The guide is inspired on the tutorial [Kubernetes The Hard Way](https://github.com/kelseyhightower/kubernetes-the-hard-way), with the
    difference that here we want to showcase how to spin up a Kubernetes cluster
    in a more managed fashion with Kubespray.
    
    ## Target Audience
    
    The target audience for this tutorial is someone looking for a
    hands-on guide to get started with Kubespray.
    
    ## Cluster Details
    
    
    * [kubespray](https://github.com/kubernetes-sigs/kubespray)
    * [kubernetes](https://github.com/kubernetes/kubernetes)
    
    
    ## Prerequisites
    
    * Google Cloud Platform: This tutorial leverages the [Google Cloud Platform](https://cloud.google.com/) to streamline provisioning of the compute infrastructure required to bootstrap a Kubernetes cluster from the ground up. [Sign up](https://cloud.google.com/free/) for $300 in free credits.
    * Google Cloud Platform SDK: Follow the Google Cloud SDK [documentation](https://cloud.google.com/sdk/) to install and configure the `gcloud` command
     line utility. Make sure to set a default compute region and compute zone.
    * The [kubectl](https://kubernetes.io/docs/tasks/tools/install-kubectl/) command line utility is used to interact with the Kubernetes
     API Server.
    * Linux or Mac environment with Python 3
    
    ## Provisioning Compute Resources
    
    Kubernetes requires a set of machines to host the Kubernetes control plane and the worker nodes where containers are ultimately run. In this lab you will provision the compute resources required for running a secure and highly available Kubernetes cluster across a single [compute zone](https://cloud.google.com/compute/docs/regions-zones/regions-zones).
    
    ### Networking
    
    The Kubernetes [networking model](https://kubernetes.io/docs/concepts/cluster-administration/networking/#kubernetes-model) assumes a flat network in which containers and nodes can communicate with each other. In cases where this is not desired [network policies](https://kubernetes.io/docs/concepts/services-networking/network-policies/) can limit how groups of containers are allowed to communicate with each other and external network endpoints.
    
    > Setting up network policies is out of scope for this tutorial.
    
    #### Virtual Private Cloud Network
    
    In this section a dedicated [Virtual Private Cloud](https://cloud.google.com/compute/docs/networks-and-firewalls#networks) (VPC) network will be setup to host the Kubernetes cluster.
    
    Create the `kubernetes-the-kubespray-way` custom VPC network:
    
    ```ShellSession
    gcloud compute networks create kubernetes-the-kubespray-way --subnet-mode custom
    ```
    
    A [subnet](https://cloud.google.com/compute/docs/vpc/#vpc_networks_and_subnets) must be provisioned with an IP address range large enough to assign a private IP address to each node in the Kubernetes cluster.
    
    
    Create the `kubernetes` subnet in the `kubernetes-the-kubespray-way` VPC network:
    
    
    ```ShellSession
    gcloud compute networks subnets create kubernetes \
      --network kubernetes-the-kubespray-way \
      --range 10.240.0.0/24
     ```
    
    > The `10.240.0.0/24` IP address range can host up to 254 compute instances.
    
    #### Firewall Rules
    
    Create a firewall rule that allows internal communication across all protocols.
    
    It is important to note that the vxlan protocol has to be allowed in order for
    
    the calico (see later) networking plugin to work.
    
    ```ShellSession
    gcloud compute firewall-rules create kubernetes-the-kubespray-way-allow-internal \
    
      --network kubernetes-the-kubespray-way \
      --source-ranges 10.240.0.0/24
    ```
    
    Create a firewall rule that allows external SSH, ICMP, and HTTPS:
    
    ```ShellSession
    gcloud compute firewall-rules create kubernetes-the-kubespray-way-allow-external \
      --allow tcp:80,tcp:6443,tcp:443,tcp:22,icmp \
      --network kubernetes-the-kubespray-way \
      --source-ranges 0.0.0.0/0
    ```
    
    It is not feasible to restrict the firewall to a specific IP address from
    where you are accessing the cluster as the nodes also communicate over the public internet and would otherwise run into
    this firewall. Technically you could limit the firewall to the (fixed) IP
    addresses of the cluster nodes and the remote IP addresses for accessing the
    cluster.
    
    ### Compute Instances
    
    The compute instances in this lab will be provisioned using [Ubuntu Server](https://www.ubuntu.com/server) 18.04.
    Each compute instance will be provisioned with a fixed private IP address and
     a public IP address (that can be fixed - see [guide](https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address)).
    Using fixed public IP addresses has the advantage that our cluster node
    configuration does not need to be updated with new public IP addresses every
    time the machines are shut down and later on restarted.
    
    Create three compute instances which will host the Kubernetes control plane:
    
    ```ShellSession
    for i in 0 1 2; do
      gcloud compute instances create controller-${i} \
        --async \
        --boot-disk-size 200GB \
        --can-ip-forward \
        --image-family ubuntu-1804-lts \
        --image-project ubuntu-os-cloud \
        --machine-type e2-standard-2 \
        --private-network-ip 10.240.0.1${i} \
        --scopes compute-rw,storage-ro,service-management,service-control,logging-write,monitoring \
        --subnet kubernetes \
        --tags kubernetes-the-kubespray-way,controller
    done
    ```
    
    > Do not forget to fix the IP addresses if you plan on re-using the cluster
    after temporarily shutting down the VMs - see [guide](https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address)
    
    Create three compute instances which will host the Kubernetes worker nodes:
    
    ```ShellSession
    for i in 0 1 2; do
      gcloud compute instances create worker-${i} \
        --async \
        --boot-disk-size 200GB \
        --can-ip-forward \
        --image-family ubuntu-1804-lts \
        --image-project ubuntu-os-cloud \
        --machine-type e2-standard-2 \
        --private-network-ip 10.240.0.2${i} \
        --scopes compute-rw,storage-ro,service-management,service-control,logging-write,monitoring \
        --subnet kubernetes \
        --tags kubernetes-the-kubespray-way,worker
    done
    ```
    
    > Do not forget to fix the IP addresses if you plan on re-using the cluster
    after temporarily shutting down the VMs - see [guide](https://cloud.google.com/compute/docs/ip-addresses/reserve-static-external-ip-address)
    
    List the compute instances in your default compute zone:
    
    ```ShellSession
    gcloud compute instances list --filter="tags.items=kubernetes-the-kubespray-way"
    ```
    
    > Output
    
    ```ShellSession
    NAME          ZONE        MACHINE_TYPE   PREEMPTIBLE  INTERNAL_IP  EXTERNAL_IP    STATUS
    controller-0  us-west1-c  e2-standard-2               10.240.0.10  XX.XX.XX.XXX   RUNNING
    controller-1  us-west1-c  e2-standard-2               10.240.0.11  XX.XXX.XXX.XX  RUNNING
    controller-2  us-west1-c  e2-standard-2               10.240.0.12  XX.XXX.XX.XXX  RUNNING
    worker-0      us-west1-c  e2-standard-2               10.240.0.20  XX.XX.XXX.XXX  RUNNING
    worker-1      us-west1-c  e2-standard-2               10.240.0.21  XX.XX.XX.XXX   RUNNING
    worker-2      us-west1-c  e2-standard-2               10.240.0.22  XX.XXX.XX.XX   RUNNING
    ```
    
    ### Configuring SSH Access
    
    Kubespray is relying on SSH to configure the controller and worker instances.
    
    Test SSH access to the `controller-0` compute instance:
    
    ```ShellSession
    IP_CONTROLLER_0=$(gcloud compute instances list  --filter="tags.items=kubernetes-the-kubespray-way AND name:controller-0" --format="value(EXTERNAL_IP)")
    USERNAME=$(whoami)
    ssh $USERNAME@$IP_CONTROLLER_0
    ```
    
    If this is your first time connecting to a compute instance SSH keys will be
    generated for you. In this case you will need to enter a passphrase at the
    prompt to continue.
    
    > If you get a 'Remote host identification changed!' warning, you probably
    already connected to that IP address in the past with another host key. You
    can remove the old host key by running `ssh-keygen -R $IP_CONTROLLER_0`
    
    Please repeat this procedure for all the controller and worker nodes, to
    ensure that SSH access is properly functioning for all nodes.
    
    ## Set-up Kubespray
    
    The following set of instruction is based on the [Quick Start](https://github.com/kubernetes-sigs/kubespray) but slightly altered for our
    set-up.
    
    As Ansible is a python application, we will create a fresh virtual
    environment to install the dependencies for the Kubespray playbook:
    
    ```ShellSession
    python3 -m venv venv
    source venv/bin/activate
    ```
    
    Next, we will git clone the Kubespray code into our working directory:
    
    ```ShellSession
    git clone https://github.com/kubernetes-sigs/kubespray.git
    cd kubespray
    
    ```
    
    Now we need to install the dependencies for Ansible to run the Kubespray
    playbook:
    
    ```ShellSession
    pip install -r requirements.txt
    ```
    
    Copy ``inventory/sample`` as ``inventory/mycluster``:
    
    ```ShellSession
    cp -rfp inventory/sample inventory/mycluster
    ```
    
    Update Ansible inventory file with inventory builder:
    
    ```ShellSession
    declare -a IPS=($(gcloud compute instances list --filter="tags.items=kubernetes-the-kubespray-way" --format="value(EXTERNAL_IP)"  | tr '\n' ' '))
    CONFIG_FILE=inventory/mycluster/hosts.yaml python3 contrib/inventory_builder/inventory.py ${IPS[@]}
    ```
    
    Open the generated `inventory/mycluster/hosts.yaml` file and adjust it so
    that controller-0, controller-1 and controller-2 are control plane nodes and
    worker-0, worker-1 and worker-2 are worker nodes. Also update the `ip` to the respective local VPC IP and
    remove the `access_ip`.
    
    The main configuration for the cluster is stored in
    
    `inventory/mycluster/group_vars/k8s_cluster/k8s_cluster.yml`. In this file we
    
     will update the `supplementary_addresses_in_ssl_keys` with a list of the IP
     addresses of the controller nodes. In that way we can access the
      kubernetes API server as an administrator from outside the VPC network. You
       can also see that the `kube_network_plugin` is by default set to 'calico'.
       If you set this to 'cloud', it did not work on GCP at the time of testing.
    
    Kubespray also offers to easily enable popular kubernetes add-ons. You can
    modify the
    
    list of add-ons in `inventory/mycluster/group_vars/k8s_cluster/addons.yml`.
    
    Let's enable the metrics server as this is a crucial monitoring element for
    the kubernetes cluster, just change the 'false' to 'true' for
    `metrics_server_enabled`.
    
    Now we will deploy the configuration:
    
    ```ShellSession
    ansible-playbook -i inventory/mycluster/hosts.yaml -u $USERNAME -b -v --private-key=~/.ssh/id_rsa cluster.yml
    ```
    
    Ansible will now execute the playbook, this can take up to 20 minutes.
    
    ## Access the kubernetes cluster
    
    We will leverage a kubeconfig file from one of the controller nodes to access
     the cluster as administrator from our local workstation.
    
    
    > In this simplified set-up, we did not include a load balancer that usually sits on top of the three controller nodes for a high available API server endpoint. In this simplified tutorial we connect directly to one of the three controllers.
    
    
    First, we need to edit the permission of the kubeconfig file on one of the
    controller nodes:
    
    ```ShellSession
    ssh $USERNAME@$IP_CONTROLLER_0
    USERNAME=$(whoami)
    sudo chown -R $USERNAME:$USERNAME /etc/kubernetes/admin.conf
    exit
    ```
    
    Now we will copy over the kubeconfig file:
    
    ```ShellSession
    scp $USERNAME@$IP_CONTROLLER_0:/etc/kubernetes/admin.conf kubespray-do.conf
    ```
    
    This kubeconfig file uses the internal IP address of the controller node to
    access the API server. This kubeconfig file will thus not work of from
    outside of the VPC network. We will need to change the API server IP address
    to the controller node his external IP address. The external IP address will be
    accepted in the
    
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    TLS negotiation as we added the controllers external IP addresses in the SSL
    
    certificate configuration.
    Open the file and modify the server IP address from the local IP to the
    external IP address of controller-0, as stored in $IP_CONTROLLER_0.
    
    > Example
    
    ```ShellSession
    apiVersion: v1
    clusters:
    - cluster:
        certificate-authority-data: XXX
        server: https://35.205.205.80:6443
      name: cluster.local
    ...
    ```
    
    Now, we load the configuration for `kubectl`:
    
    ```ShellSession
    export KUBECONFIG=$PWD/kubespray-do.conf
    ```
    
    We should be all set to communicate with our cluster from our local workstation:
    
    ```ShellSession
    kubectl get nodes
    ```
    
    > Output
    
    ```ShellSession
    NAME           STATUS   ROLES    AGE   VERSION
    controller-0   Ready    master   47m   v1.17.9
    controller-1   Ready    master   46m   v1.17.9
    controller-2   Ready    master   46m   v1.17.9
    worker-0       Ready    <none>   45m   v1.17.9
    worker-1       Ready    <none>   45m   v1.17.9
    worker-2       Ready    <none>   45m   v1.17.9
    ```
    
    ## Smoke tests
    
    ### Metrics
    
    Verify if the metrics server addon was correctly installed and works:
    
    ```ShellSession
    kubectl top nodes
    ```
    
    > Output
    
    ```ShellSession
    NAME           CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
    controller-0   191m         10%    1956Mi          26%
    controller-1   190m         10%    1828Mi          24%
    controller-2   182m         10%    1839Mi          24%
    worker-0       87m          4%     1265Mi          16%
    worker-1       102m         5%     1268Mi          16%
    worker-2       108m         5%     1299Mi          17%
    ```
    
    Please note that metrics might not be available at first and need a couple of
     minutes before you can actually retrieve them.
    
    ### Network
    
    Let's verify if the network layer is properly functioning and pods can reach
    each other:
    
    ```ShellSession
    kubectl run myshell1 -it --rm --image busybox -- sh
    hostname -i
    
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    # launch myshell2 in separate terminal (see next code block) and ping the hostname of myshell2
    
    ping <hostname myshell2>
    ```
    
    ```ShellSession
    kubectl run myshell2 -it --rm --image busybox -- sh
    hostname -i
    ping <hostname myshell1>
    ```
    
    > Output
    
    ```ShellSession
    PING 10.233.108.2 (10.233.108.2): 56 data bytes
    64 bytes from 10.233.108.2: seq=0 ttl=62 time=2.876 ms
    64 bytes from 10.233.108.2: seq=1 ttl=62 time=0.398 ms
    64 bytes from 10.233.108.2: seq=2 ttl=62 time=0.378 ms
    ^C
    --- 10.233.108.2 ping statistics ---
    3 packets transmitted, 3 packets received, 0% packet loss
    round-trip min/avg/max = 0.378/1.217/2.876 ms
    ```
    
    ### Deployments
    
    In this section you will verify the ability to create and manage [Deployments](https://kubernetes.io/docs/concepts/workloads/controllers/deployment/).
    
    Create a deployment for the [nginx](https://nginx.org/en/) web server:
    
    ```ShellSession
    kubectl create deployment nginx --image=nginx
    ```
    
    List the pod created by the `nginx` deployment:
    
    ```ShellSession
    kubectl get pods -l app=nginx
    ```
    
    > Output
    
    ```ShellSession
    NAME                     READY   STATUS    RESTARTS   AGE
    nginx-86c57db685-bmtt8   1/1     Running   0          18s
    ```
    
    #### Port Forwarding
    
    In this section you will verify the ability to access applications remotely using [port forwarding](https://kubernetes.io/docs/tasks/access-application-cluster/port-forward-access-application-cluster/).
    
    Retrieve the full name of the `nginx` pod:
    
    ```ShellSession
    POD_NAME=$(kubectl get pods -l app=nginx -o jsonpath="{.items[0].metadata.name}")
    ```
    
    Forward port `8080` on your local machine to port `80` of the `nginx` pod:
    
    ```ShellSession
    kubectl port-forward $POD_NAME 8080:80
    ```
    
    > Output
    
    ```ShellSession
    Forwarding from 127.0.0.1:8080 -> 80
    Forwarding from [::1]:8080 -> 80
    ```
    
    In a new terminal make an HTTP request using the forwarding address:
    
    ```ShellSession
    curl --head http://127.0.0.1:8080
    ```
    
    > Output
    
    ```ShellSession
    HTTP/1.1 200 OK
    Server: nginx/1.19.1
    Date: Thu, 13 Aug 2020 11:12:04 GMT
    Content-Type: text/html
    Content-Length: 612
    Last-Modified: Tue, 07 Jul 2020 15:52:25 GMT
    Connection: keep-alive
    ETag: "5f049a39-264"
    Accept-Ranges: bytes
    ```
    
    Switch back to the previous terminal and stop the port forwarding to the `nginx` pod:
    
    ```ShellSession
    Forwarding from 127.0.0.1:8080 -> 80
    Forwarding from [::1]:8080 -> 80
    Handling connection for 8080
    ^C
    ```
    
    #### Logs
    
    In this section you will verify the ability to [retrieve container logs](https://kubernetes.io/docs/concepts/cluster-administration/logging/).
    
    Print the `nginx` pod logs:
    
    ```ShellSession
    kubectl logs $POD_NAME
    ```
    
    > Output
    
    ```ShellSession
    ...
    127.0.0.1 - - [13/Aug/2020:11:12:04 +0000] "HEAD / HTTP/1.1" 200 0 "-" "curl/7.64.1" "-"
    ```
    
    #### Exec
    
    
    In this section you will verify the ability to [execute commands in a container](https://kubernetes.io/docs/tasks/debug/debug-application/get-shell-running-container/#running-individual-commands-in-a-container).
    
    
    Print the nginx version by executing the `nginx -v` command in the `nginx` container:
    
    ```ShellSession
    kubectl exec -ti $POD_NAME -- nginx -v
    ```
    
    > Output
    
    ```ShellSession
    nginx version: nginx/1.19.1
    ```
    
    ### Kubernetes services
    
    #### Expose outside of the cluster
    
    In this section you will verify the ability to expose applications using a [Service](https://kubernetes.io/docs/concepts/services-networking/service/).
    
    Expose the `nginx` deployment using a [NodePort](https://kubernetes.io/docs/concepts/services-networking/service/#type-nodeport) service:
    
    ```ShellSession
    kubectl expose deployment nginx --port 80 --type NodePort
    ```
    
    > The LoadBalancer service type can not be used because your cluster is not configured with [cloud provider integration](https://kubernetes.io/docs/getting-started-guides/scratch/#cloud-provider). Setting up cloud provider integration is out of scope for this tutorial.
    
    Retrieve the node port assigned to the `nginx` service:
    
    ```ShellSession
    NODE_PORT=$(kubectl get svc nginx \
      --output=jsonpath='{range .spec.ports[0]}{.nodePort}')
    ```
    
    Create a firewall rule that allows remote access to the `nginx` node port:
    
    ```ShellSession
    gcloud compute firewall-rules create kubernetes-the-kubespray-way-allow-nginx-service \
      --allow=tcp:${NODE_PORT} \
      --network kubernetes-the-kubespray-way
    ```
    
    Retrieve the external IP address of a worker instance:
    
    ```ShellSession
    EXTERNAL_IP=$(gcloud compute instances describe worker-0 \
      --format 'value(networkInterfaces[0].accessConfigs[0].natIP)')
    ```
    
    Make an HTTP request using the external IP address and the `nginx` node port:
    
    ```ShellSession
    curl -I http://${EXTERNAL_IP}:${NODE_PORT}
    ```
    
    > Output
    
    ```ShellSession
    HTTP/1.1 200 OK
    Server: nginx/1.19.1
    Date: Thu, 13 Aug 2020 11:15:02 GMT
    Content-Type: text/html
    Content-Length: 612
    Last-Modified: Tue, 07 Jul 2020 15:52:25 GMT
    Connection: keep-alive
    ETag: "5f049a39-264"
    Accept-Ranges: bytes
    ```
    
    #### Local DNS
    
    We will now also verify that kubernetes built-in DNS works across namespaces.
    Create a namespace:
    
    ```ShellSession
    kubectl create namespace dev
    ```
    
    Create an nginx deployment and expose it within the cluster:
    
    ```ShellSession
    kubectl create deployment nginx --image=nginx -n dev
    kubectl expose deployment nginx --port 80 --type ClusterIP -n dev
    ```
    
    Run a temporary container to see if we can reach the service from the default
    namespace:
    
    ```ShellSession
    kubectl run curly -it --rm --image curlimages/curl:7.70.0 -- /bin/sh
    curl --head http://nginx.dev:80
    ```
    
    > Output
    
    ```ShellSession
    HTTP/1.1 200 OK
    Server: nginx/1.19.1
    Date: Thu, 13 Aug 2020 11:15:59 GMT
    Content-Type: text/html
    Content-Length: 612
    Last-Modified: Tue, 07 Jul 2020 15:52:25 GMT
    Connection: keep-alive
    ETag: "5f049a39-264"
    Accept-Ranges: bytes
    ```
    
    Type `exit` to leave the shell.
    
    ## Cleaning Up
    
    ### Kubernetes resources
    
    Delete the dev namespace, the nginx deployment and service:
    
    ```ShellSession
    kubectl delete namespace dev
    kubectl delete deployment nginx
    
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    kubectl delete svc/nginx
    
    ```
    
    ### Kubernetes state
    
    Note: you can skip this step if you want to entirely remove the machines.
    
    If you want to keep the VMs and just remove the cluster state, you can simply
     run another Ansible playbook:
    
    ```ShellSession
    ansible-playbook -i inventory/mycluster/hosts.yaml -u $USERNAME -b -v --private-key=~/.ssh/id_rsa reset.yml
    ```
    
    Resetting the cluster to the VMs original state usually takes about a couple
    of minutes.
    
    ### Compute instances
    
    Delete the controller and worker compute instances:
    
    ```ShellSession
    gcloud -q compute instances delete \
      controller-0 controller-1 controller-2 \
      worker-0 worker-1 worker-2 \
      --zone $(gcloud config get-value compute/zone)
      ```
    
    <!-- markdownlint-disable no-duplicate-heading -->
    ### Network
    <!-- markdownlint-enable no-duplicate-heading -->
    
    Delete the fixed IP addresses (assuming you named them equal to the VM names),
    if any:
    
    ```ShellSession
    gcloud -q compute addresses delete controller-0 controller-1 controller-2 \
      worker-0 worker-1 worker-2
    ```
    
    Delete the `kubernetes-the-kubespray-way` firewall rules:
    
    ```ShellSession
    gcloud -q compute firewall-rules delete \
      kubernetes-the-kubespray-way-allow-nginx-service \
      kubernetes-the-kubespray-way-allow-internal \
      kubernetes-the-kubespray-way-allow-external
    ```
    
    Delete the `kubernetes-the-kubespray-way` network VPC:
    
    ```ShellSession
    gcloud -q compute networks subnets delete kubernetes
    gcloud -q compute networks delete kubernetes-the-kubespray-way
    ```