Setup K8s cluster on GCP VMs

Overview This section explains how to set up a Kubernetes (K8s) cluster on Google Cloud Platform (GCP) using Terraform. Instead of using GCP's managed Kubernetes service, we will install open-source Kubernetes manually inside virtual machines (VMs). Objective In software and microservice architecture design, it is essential to consider the scalability, availability, and performance of the application. I am proposing the following design considerations when selecting Kubernetes as part of the software architecture: When the application requires high performance, availability, scalability, and security When greater control over and maintenance of the infrastructure is needed When the application architecture involves complex microservices When opting for open-source solutions (optional) When Kubernetes may not be the right choice: If the application is small and can be supported by a cloud provider’s managed services, such as AWS ECS with Fargate (serverless technology) If the application does not require high throughput If the goal is to minimize IT operational costs and reduce infrastructure management responsibilities In this setup, I considered the following points while building Kubernetes (K8s) on GCP: Terraform: Used to easily deploy, manage, and destroy the cluster infrastructure. HAProxy: Implemented an open-source load balancer instead of relying on GCP’s native load balancer. HAProxy provides high-performance load balancing. GCP RBAC: Leveraged GCP’s Role-Based Access Control to simplify node joining, manage Kubernetes-related files in GCP Buckets, and associate service accounts with bucket roles and virtual machines. Minimal Permissions: As a best practice, configured minimal necessary roles for infrastructure components to enhance security. Firewall Rules: Configured the following rules: Public → HAProxy (port 80) and HAProxy → Kubernetes Worker Nodes (port 30080). Public and Private Subnets: Separated application workloads and network traffic by isolating resources into public and private subnets. Note: This is not a production-ready architecture. In production environments, the default network should not be used. Instead, you should create your own VPCs, such as separate networks for Management, Development, and Production environments (for eg: following HIPAA-compliant recommended network architecture practices). Prerequisites We have to setup the following tools and accounts Create GCP account [we can create free tier account] Install Terraform in your machine [Min Terraform v1.9.3] Install gcloud command line in your machine Login GCP account Login the GCP account through gcloud CLI command. Execute following command gcloud auth login (Optional) Re-authenticate for a Specific Project To log in and set a GCP project: gcloud config set project PROJECT_ID Replace GCP PROJECT_ID with your actual project. Configure the env variables Following environment variables need to configure. Replace the GCP project id with {your-gcp-project-id}. CLOUDSDK_CORE_PROJECT: This variable configure the GCP project id to use the gcloud cli command TF_VAR_gcp_project_id: This variable to configure the GCP project id to use the terraform export CLOUDSDK_CORE_PROJECT={your-gcp-project-id} export set TF_VAR_gcp_project_id={your-gcp-project-id} Terraform Structure Following the terraform module maintain to deploy the resources in the GCP account Create the Terraform workspace The following command is used to create a Terraform workspace. A workspace in Terraform functions similarly to managing different environments in software development, such as dev and prod. In this setup, the workspace helps differentiate resources for each environment within the same GCP project. We are following a consistent naming convention for resource creation in the GCP account: Naming Pattern: {project-id}-{env}-{resource-name} Examples for the dev environment: myp-dev-secure-bucket myp-dev-k8s-master-node myp-dev-k8s-worker-node-1 Examples for the prod environment: myp-prod-secure-bucket myp-prod-k8s-master-node myp-prod-k8s-worker-node-1 Note: As a best practice, production workloads should be managed in a separate GCP project. This approach improves production performance, enhances security, and ensures complete isolation between development and production environments. terraform workspace new dev Terraform Configuration Resource configurations can be defined in a dev.tfvars variable file. Different variable files can be maintained for different environments (e.g., dev.tfvars, prod.tfvars). For example, project-specific values such as the project ID and project name for each environment can be configured in these files. For example: #--------------------- Development Project Configuration --------------------- #Development Project configuration, this pro

Apr 28, 2025 - 18:41

Overview

This section explains how to set up a Kubernetes (K8s) cluster on Google Cloud Platform (GCP) using Terraform. Instead of using GCP's managed Kubernetes service, we will install open-source Kubernetes manually inside virtual machines (VMs).

Objective

In software and microservice architecture design, it is essential to consider the scalability, availability, and performance of the application. I am proposing the following design considerations when selecting Kubernetes as part of the software architecture:

When the application requires high performance, availability, scalability, and security
When greater control over and maintenance of the infrastructure is needed
When the application architecture involves complex microservices
When opting for open-source solutions (optional)

When Kubernetes may not be the right choice:

If the application is small and can be supported by a cloud provider’s managed services, such as AWS ECS with Fargate (serverless technology)
If the application does not require high throughput
If the goal is to minimize IT operational costs and reduce infrastructure management responsibilities

In this setup, I considered the following points while building Kubernetes (K8s) on GCP:

Terraform: Used to easily deploy, manage, and destroy the cluster infrastructure.
HAProxy: Implemented an open-source load balancer instead of relying on GCP’s native load balancer. HAProxy provides high-performance load balancing.
GCP RBAC: Leveraged GCP’s Role-Based Access Control to simplify node joining, manage Kubernetes-related files in GCP Buckets, and associate service accounts with bucket roles and virtual machines.
Minimal Permissions: As a best practice, configured minimal necessary roles for infrastructure components to enhance security.
Firewall Rules: Configured the following rules: Public → HAProxy (port 80) and HAProxy → Kubernetes Worker Nodes (port 30080).
Public and Private Subnets: Separated application workloads and network traffic by isolating resources into public and private subnets.

Note: This is not a production-ready architecture. In production environments, the default network should not be used. Instead, you should create your own VPCs, such as separate networks for Management, Development, and Production environments (for eg: following HIPAA-compliant recommended network architecture practices).

Prerequisites

We have to setup the following tools and accounts

Create GCP account [we can create free tier account]
Install Terraform in your machine [Min Terraform v1.9.3]
Install gcloud command line in your machine

Login GCP account

gcloud auth login

(Optional) Re-authenticate for a Specific Project
To log in and set a GCP project:

gcloud config set project PROJECT_ID

Replace GCP PROJECT_ID with your actual project.

Configure the `env` variables

Following environment variables need to configure. Replace the GCP project id with {your-gcp-project-id}.

CLOUDSDK_CORE_PROJECT: This variable configure the GCP project id to use the gcloud cli command
TF_VAR_gcp_project_id: This variable to configure the GCP project id to use the terraform

export CLOUDSDK_CORE_PROJECT={your-gcp-project-id}
export set TF_VAR_gcp_project_id={your-gcp-project-id}

Terraform Structure

Following the terraform module maintain to deploy the resources in the GCP account

Create the Terraform workspace

The following command is used to create a Terraform workspace. A workspace in Terraform functions similarly to managing different environments in software development, such as dev and prod. In this setup, the workspace helps differentiate resources for each environment within the same GCP project.

We are following a consistent naming convention for resource creation in the GCP account:
Naming Pattern: {project-id}-{env}-{resource-name}

Examples for the `dev` environment:

myp-dev-secure-bucket
myp-dev-k8s-master-node
myp-dev-k8s-worker-node-1

Examples for the `prod` environment:

myp-prod-secure-bucket
myp-prod-k8s-master-node
myp-prod-k8s-worker-node-1

Note: As a best practice, production workloads should be managed in a separate GCP project. This approach improves production performance, enhances security, and ensures complete isolation between development and production environments.

terraform workspace new dev

Terraform Configuration

Resource configurations can be defined in a dev.tfvars variable file. Different variable files can be maintained for different environments (e.g., dev.tfvars, prod.tfvars).
For example, project-specific values such as the project ID and project name for each environment can be configured in these files.

For example:

#--------------------- Development Project Configuration ---------------------
#Development Project configuration, this project configuration is used to maintain resources for this project. eg: project_id will be used to create the GCP resources
project_id   = "myp"
project_name = "My Project"
# --------------------- GCP Project and Regsion Configuration ---------------------
gcp_region = "us-east1"
gcp_zone   = "us-east1-b"
#--------------------- Network Configuration ---------------------
nw_network_name          = "default"
nw_subnet_public_address_range = "10.0.0.0/24"
nw_subnet_private_address_range = "10.0.1.0/24"

Setup the resources in GCP

Run the following Terraform command to create the resources in the GCP .

terraform init --upgrade
terraform plan -var-file="dev.tfvars"
terraform apply -var-file="dev.tfvars"

It creates the following resources in GCP project account

Service Account:
- k8s-master-node-sa@xxxxxx.gserviceaccount.com
- k8s-worker-node-sa@xxxxxx.gserviceaccount.com
VPC Network (default)→Subnet:
- myp-dev-private-subnet
- myp-dev-public-subnet
VPC Network (default)→Firewall:
- myp-dev-haproxy-lb-allow-http
- myp-dev-k8s-incoming-from-haproxy-lb
- myp-dev-k8s-wroker-incoming-from-k8s-master
- myp-dev-k8s-wroker-egress-to-k8s-master
- myp-dev-k8s-outgoing-to-haproxy-lb-allow
Buckets:
- Bucket name: myp-dev-{uniqueid}-secure-bukcet
  - Unique id can be configured in the dev.tfvars
- Folder name: /k8s/master-node
- Permission
  - k8s-master-node-sa@xxxxxx.gserviceaccount.com
  - k8s-worker-node-sa@xxxxxx.gserviceaccount.com
VM Instances
- myp-dev-haproxy-lb-1
- myp-dev-k8s-master-node
- myp-dev-k8s-worker-node-1

Verify the services are installed in the K8s VM and HAProxy VM

We can verify whether the services have been installed successfully. The following steps can help monitor and validate the status of the services.

SSH into Master VM in the GCP console

Verify all initial script execute properly while start the VM

#For Google Cloud VM Instances:
#When using the metadata_startup_script in a GCP VM, the startup script output is logged to:
tail -500f /var/log/syslog

cat /var/log/syslog | grep "Intalled the tools!"
cat /var/log/syslog | grep "Container configure default configuration!"
cat /var/log/syslog | grep "Enabiling IP forwarding"
cat /var/log/syslog | grep "Configured the paramters of VM for K8s!"
cat /var/log/syslog | grep "Kubernetes has initialized successfully!"
cat /var/log/syslog | grep "Uploaded token into bucket!"

SSH into Worker VM in the GCP console

Verify all initial script execute properly while start the VM

tail -500f /var/log/syslog
cat /var/log/syslog | grep "Joined the master node successfully!"

SSH into HAProxy VM in the GCP console

Verify all initial script execute properly while start the VM

    tail -500f /var/log/syslog
    cat /var/log/syslog | grep "Restart HAPorxy!"

    ##Output:
    startup-script: Restart HAPorxy!

Verify HAProxy configuration and checking internal IP configure of k8s backend service

cat /etc/haproxy/haproxy.cfg

#Following information will be added in the configuration, Output:
frontend http_front
        bind *:80
        mode http
        default_backend haproxy_ingress_backend
backend haproxy_ingress_backend
    mode http
    balance roundrobin
    server k8s-node1 :30080 check maxconn 32

Verify the tcp connection 30080 port

sudo apt install telnet -y
telnet  30080

Verify the Bucket

Check the bucket storage to verify whether the file /k8s/master-node/join_node.sh has been uploaded.
This shell script is used to join worker nodes to the Kubernetes cluster. It will be downloaded and executed on each worker node during the setup process.

Verify the nodes join

We can verify the worker nodes are joined with master node. Following step helps monitor the services
SSH into Master VM in the GCP console

Verify the nodes are joined in the K8s cluster. Execute following command

#Login into ubuntu user
sudo su ubuntu
##Check the nodes
kubectl get nodes

Following Output:

NAME                            STATUS   ROLES           AGE   VERSION
myp-dev-k8s-master-node     Ready    control-plane   26m   v1.32.3
myp-dev-k8s-worker-node-1   Ready              25m   v1.32.3

Verify the pods are installed eg: network plugin (Calico in this case)

##Check the pods
kubectl get pods --all-namespaces

##Following Output:
NAMESPACE     NAME                                                  READY   STATUS    RESTARTS   AGE
kube-system   calico-kube-controllers-7498b9bb4c-44pf8              1/1     Running   0          29m
kube-system   calico-node-b4bnh                                     1/1     Running   0          28m
kube-system   calico-node-bhpv8                                     1/1     Running   0          29m
kube-system   coredns-668d6bf9bc-8tdsb                              1/1     Running   0          29m
kube-system   coredns-668d6bf9bc-j6q4p                              1/1     Running   0          29m
kube-system   etcd-myp-default-k8s-master-node                      1/1     Running   0          29m
kube-system   kube-apiserver-myp-default-k8s-master-node            1/1     Running   0          29m
kube-system   kube-controller-manager-myp-default-k8s-master-node   1/1     Running   0          29m
kube-system   kube-proxy-4qgkc                                      1/1     Running   0          28m
kube-system   kube-proxy-zvlsb                                      1/1     Running   0          29m
kube-system   kube-scheduler-myp-default-k8s-master-node            1/1     Running   0          29m

Install Web Applications K8s cluster

We are deploying nginx-web as a sample application on the worker nodes and connecting to it through the HAProxy load balancer.
Since we are using HAProxy as the load balancer in our architecture, we need to configure an HAProxy Ingress Controller to properly route incoming requests to the applications running inside the pods.

Install the HAProxy ingress controller into master VM in the GCP console

Install helm

#Login to ubuntu user
sudo su ubuntu

#Install helm
curl https://baltocdn.com/helm/signing.asc | sudo apt-key add -
sudo apt-get install apt-transport-https --yes
echo "deb https://baltocdn.com/helm/stable/debian/ all main" | sudo tee /etc/apt/sources.list.d/helm-stable-debian.list
# Install
sudo apt update
sudo apt install helm

#Check the version
helm version

#Output:
version.BuildInfo{Version:"v3.17.2", GitCommit:"cc0bbbd6d6276b83880042c1ecb34087e84d41eb", GitTreeState:"clean", GoVersion:"go1.23.7"}

Add HAProxy repo

helm repo add haproxytech https://haproxytech.github.io/helm-charts
helm repo update

Install the HAProxy ingress controller and expose the http and https Node Port to connect the HAProxy Load Balancer

helm install haproxy-kubernetes-ingress haproxytech/kubernetes-ingress \
    --create-namespace \
    --namespace haproxy-controller \
    --set controller.service.type=NodePort \
    --set controller.service.nodePorts.http=30080 \
    --set controller.service.nodePorts.https=30443 \
    --set controller.service.nodePorts.stat=30002 \
    --set controller.service.nodePorts.prometheus=30003

#Verify the service
kubectl get svc -n haproxy-controller haproxy-kubernetes-ingress
#Output
haproxy-kubernetes-ingress   NodePort   10.109.135.187           80:30080/TCP,443:30443/TCP,443:30443/UDP,1024:30002/TCP   103s

Install sample nginx server in the K8s and create ingress resource of HAProxy

Install nginx-web server on K8s and expose 80 port

kubectl create deployment nginx-web --image=nginx --port=80
kubectl get deployments.apps -o wide
kubectl expose deployment nginx-web --port=80 --target-port=80 --type=ClusterIP
kubectl get  svc

#Output
NAME         TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)   AGE
kubernetes   ClusterIP   10.96.0.1                443/TCP   60m
nginx-web    ClusterIP   10.110.173.152           80/TCP    16m

Create the ingress resource to rout the request into nginx-web:80 application

#Install VI editor to create the resource file
sudo apt install vim -y
vi nginx-ingress.yaml

#Copy following configuration insuide `nginx-ingress.yaml`
#nginx-ingress.yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
    name: nginx-ingress
    namespace: default
    annotations:
    ingress.class: "haproxy"
spec:
    rules:
    - http:
        paths:
        - path: /
        pathType: Prefix
        backend:
            service:
            name: nginx-web
            port:
                number: 80

Apply the ingress resource

kubectl apply -f nginx-ingress.yaml

Identify the worker node Ip and test access of app through Node Port of worker node

kubectl get nodes -o wide
curl http://:30080

We will see following output of Nginx server home page

Welcome to nginx! If you see this page, the nginx web server is successfully installed and working. Further configuration is required. For online documentation and support please refer to href="http://nginx.org/">nginx.org. Commercial support is available at href="http://nginx.com/">nginx.com.

Thank you for using nginx.

Identify the haporxay external Ip address from GCP console and execute following command on browser

http://

Destroy the resources in GCP account

Execute following commands to destroy / clean the resources which are created on GCP

terraform destroy -var-file="dev.tfvars"

Git Repo : (setup-k8s-cluster-on-gcp)[https://github.com/developerhelperhub/setup-k8s-cluster-on-gcp]