# 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) v2.17.x * [kubernetes](https://github.com/kubernetes/kubernetes) v1.17.9 ## 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 ipip 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 \ --allow tcp,udp,icmp,ipip \ --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 $IP_CONTROLLER_0` Please repeat this procedure for all the controller and worker nodes, to ensure that SSH access is properly functioning for all nodes. ## Set-up Kubespray The following set of instruction is based on the [Quick Start](https://github.com/kubernetes-sigs/kubespray) but slightly altered for our set-up. As Ansible is a python application, we will create a fresh virtual environment to install the dependencies for the Kubespray playbook: ```ShellSession python3 -m venv venv source venv/bin/activate ``` Next, we will git clone the Kubespray code into our working directory: ```ShellSession git clone https://github.com/kubernetes-sigs/kubespray.git cd kubespray git checkout release-2.17 ``` Now we need to install the dependencies for Ansible to run the Kubespray playbook: ```ShellSession pip install -r requirements.txt ``` Copy ``inventory/sample`` as ``inventory/mycluster``: ```ShellSession cp -rfp inventory/sample inventory/mycluster ``` Update Ansible inventory file with inventory builder: ```ShellSession declare -a IPS=($(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 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 45m v1.17.9 worker-1 Ready 45m v1.17.9 worker-2 Ready 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 # launch myshell2 in separate terminal (see next code block) and ping the hostname of myshell2 ping ``` ```ShellSession kubectl run myshell2 -it --rm --image busybox -- sh hostname -i ping ``` > 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-application-cluster/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 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) ``` ### Network 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 ```