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Automating Creation of a Compute Instance and Firewall in GCP with Terraform and GitLab CI/CD
Streamlining Infrastructure Management for Secure and Efficient Cloud Deployments
Automating Creation of a Compute Instance and Firewall in GCP with Terraform and GitLab CI/CD
Introduction: In today's cloud-based world, automating infrastructure deployment is essential for efficiency, scalability, and security. In this blog post, we will explore how to automate the creation of a compute instance and a firewall in Google Cloud Platform (GCP) using Terraform. Furthermore, we will leverage GitLab CI/CD to establish a continuous integration and deployment pipeline that automates the entire process, enabling smooth and consistent infrastructure changes.

Prerequisites: Before we begin, ensure you have the following prerequisites in place:
A Google Cloud Platform (GCP) account with the necessary permissions to create compute instances and networking resources.
A GitLab account with a repository set up to manage your Terraform code.
Repo Structure: To keep our project organized, we will follow this directory structure within our GitLab repository: GitLab-Repo

You can simply clone my public repository: GitLab-Repo
Terraform Configuration: Let's dive into the details of each component of our Terraform code:
main.tf: The main.tf
file contains the core Terraform configuration, defining the resources and their properties to be provisioned in the target cloud environment. In this context, it sets up a Google Cloud Platform (GCP) compute instance and firewall rules for secure access.
resource "google_compute_instance" "gitlab-terraform-instance" {
name = "gitlab-terraform-instance"
machine_type = "e2-medium"
boot_disk {
initialize_params {
image = "debian-cloud/debian-11"
}
}
network_interface {
network = "default"
access_config {
// Optional. External IP address configuration.
}
}
tags = ["gitlab-terraform-instance"]
}
resource "google_compute_firewall" "gitlab-firewall" {
name = "gitlab-firewall"
network = "default"
allow {
protocol = "tcp"
ports = ["22", "3389"]
}
source_ranges = ["0.0.0.0/0"]
}
provider.tf: The provider.tf
file specifies the configuration for the Terraform provider, defining the target cloud platform and its necessary details, such as backend bucket, project ID, region, and zone. It allows Terraform to interact with GCP and manage resources in the designated project.
terraform {
required_providers {
google = {
source = "hashicorp/google"
version = "4.58.0"
}
}
backend "gcs" {
bucket = "your-backend-bucket" // Replace with your backend bucket name
prefix = "terraform/state"
}
}
provider "google" {
project = "your-project-id" // Replace with your project ID
region = "us-central1" // Replace with your desired region
zone = "us-central1-c" // Replace with your desired zone
}
GitLab CI/CD Configuration: The .gitlab-ci.yml
file sets up the CI/CD pipeline for automating the infrastructure deployment process. It defines stages, jobs, and associated scripts to perform tasks such as validation, planning, applying, and destroying Terraform changes.
---
workflow:
rules:
- if: $CI_COMMIT_BRANCH != "main" && $CI_PIPELINE_SOURCE != "merge_request_event"
when: never
- when: always
variables:
TF_DIR: ${CI_PROJECT_DIR}/terraform
STATE_NAME: "gitlab-terraform-gcp-tf"
stages:
- validate
- plan
- apply
- destroy
image:
name: hashicorp/terraform:light
entrypoint: [""]
before_script:
- terraform --version
- cd ${TF_DIR}
- terraform init -reconfigure
validate:
stage: validate
script:
- terraform validate
cache:
key: ${CI_COMMIT_REF_NAME}
paths:
- ${TF_DIR}/.terraform
policy: pull-push
plan:
stage: plan
script:
- terraform plan
dependencies:
- validate
cache:
key: ${CI_COMMIT_REF_NAME}
paths:
- ${TF_DIR}/.terraform
policy: pull
apply:
stage: apply
script:
- terraform apply -auto-approve
dependencies:
- plan
cache:
key: ${CI_COMMIT_REF_NAME}
paths:
- ${TF_DIR}/.terraform
policy: pull
destroy:
stage: destroy
script:
- terraform destroy -auto-approve
dependencies:
- plan
- apply
cache:
key: ${CI_COMMIT_REF_NAME}
paths:
- ${TF_DIR}/.terraform
policy: pull
when: manual
Implementation Steps: Now that we have our code and pipeline set up, let's walk through the implementation steps to automate the creation of a compute instance and a firewall in GCP using Terraform and GitLab CI/CD.
Set up GitLab Repository: Create a new repository on GitLab or use an existing one to host your Terraform code. If you haven't already, clone the repository from the following link: GitLab-Repo
Configure GCP Provider: In the
provider.tf
file, configure the GCP provider by specifying your GCP backend bucket, project ID, region, and zone.Set Secrets in GitLab: In your GitLab repository, navigate to Settings > CI/CD > Variables. Add a new variable named "GOOGLE_CREDENTIALS" and paste the contents of your Google Cloud service account key file into the value field. This securely provides the necessary credentials for Terraform to authenticate with GCP.

Note: Make sure to remove any white spaces in your token content before pasting it.
Run the Pipeline: Run the Pipeline Commit and push your Terraform code to the GitLab repository. This action will trigger the GitLab CI/CD pipeline. Monitor the pipeline execution in the CI/CD section of your repository to ensure it completes successfully.
Verify Resource Creation in GCP: Verify Resource Creation in GCP After the pipeline is finished, verify the creation of resources in the Google Cloud Platform (GCP) Console. Ensure that the compute instance and firewall have been provisioned accurately.
Conclusion: In this blog post, we successfully automated the creation of a compute instance and a firewall in Google Cloud Platform using Terraform and GitLab CI/CD. By following the steps outlined above, you can now efficiently manage and automate your GCP infrastructure. Remember to regularly update your Terraform code and pipeline to reflect any changes in your infrastructure requirements. By combining Terraform and GitLab CI/CD, you automate infrastructure management, improve consistency, and minimize errors. Stay agile by updating code, leveraging version control, and fostering collaboration for a secure and auditable infrastructure.
Happy automating!
References: GitLab-Repo