In this full-day workshop, we will look at some core mechanisms of GKE. We will look at different provisioning models of applications, scaling, monitoring, and command-line-based cluster control. The present subject areas have not yet been fully formulated. There may be changes to the contents and the current schedule. The labs require functional access to a GCP project and a uniform toolset in the local development environment (e.g., kubectl, GCP cloud SDK command-line tools). The lectures on each topic will take about 45 minutes, and the labs will take about 30 minutes each.

For the use of the local development environment for all GKE/K8s relevant CLI/API calls a certain tool set is required and Linux or macOS as operating system is recommended. If it is not possible to install our stack due to limitations in terms of feasibility/availability in the preparation, you can alternatively use the browser-internal cloud shell of your GCP console.

• gcloud sdk installation tutorial
• kubectl installation tutorial

The preparation of the GKE cluster is one of the first steps of our workshop and is the basis for all our further activity using the local development environment of all participants. We will pave the way to our first K8s application deployment step by step in the following section, learning some of the basics of using the gcloud SDK CLI and kubectl.

gcloud components update
gcloud init

alias k='kubectl'

The present gcloud command call initializes the workshop-cluster as regional cluster configuration with one node in each of three availability zones.

• Please make sure that you are also in the project prepared for this workshop or that your used dev/sandbox project has also been selected via cloud init!

• Init your GKE-Cluster with a unique identifier suffix (and remind your cluster-id)

  printf "%s\n" "[INIT] workshop cluster"
  UNIQUE_CLUSTER_KEY=$RANDOM; GCP_PROJECT=$(gcloud config get core/project);
  gcloud container clusters create workshop-${UNIQUE_CLUSTER_KEY} \
  --machine-type n2-standard-2 \
  --scopes "https://www.googleapis.com/auth/source.read_write,cloud-platform" \
  --region europe-west1 \
  --node-locations europe-west1-b,europe-west1-c,europe-west1-d \
  --release-channel regular \
  --disk-type "pd-ssd" \
  --disk-size "60" \
  --num-nodes "1" \
  --max-nodes "1" \
  --min-nodes "1" \
  --logging=SYSTEM,WORKLOAD \
  --monitoring=SYSTEM \
  --network "default" \
  --addons HorizontalPodAutoscaling,HttpLoadBalancing,NodeLocalDNS,ConfigConnector \
  --labels k8s-scope=gke-workshop-doit,k8s-cluster=primary,k8s-env=workshop \
  --workload-pool=${GCP_PROJECT}.svc.id.goog && \
  printf "%s\n" "[INIT] test access new cluster using k8s API via kubectl" \
  kubectl get all --all-namespaces && kubectl cluster-info && \
  printf "\n%s\n\n" "[INIT] workshop cluster finally initialized and available by ID -> [ workshop-${UNIQUE_CLUSTER_KEY} ] <-"

• pydevop's gcloud cheat sheet markdown paper

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