**Cloud Infrastructure Automation with GCP: VPC, Cloud SQL, Cloud Run, and CI/CD 🚀 **

** #Tester This project showcases cloud infrastructure automation using Google Cloud Platform (GCP) services such as VPC networks, Cloud SQL, and Cloud Run, with an emphasis on private connectivity and security through SQL Proxy. The project also integrates CI/CD pipelines using Cloud Build, Artifact Registry, and Cloud Deploy to automate web application deployments.

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Project Overview

This project automates the following tasks using Python scripts (to be transitioned to Terraform in future iterations):

1. VPC and Subnet Creation:

   • Set up custom VPC networks and subnets for regional cloud resources in North America and Asia.

2. Cloud SQL Instance Deployment:

   • Create Cloud SQL instances with private IP connectivity using VPC peering and SQL Proxy for enhanced security.

3. SQL Proxy Setup for Private Connections:

   • Automate the creation of a Cloud SQL Proxy instance and configure firewalls and NAT routing to manage secure access.

4. Web Application Deployment on Cloud Run (In progress):

   • Build and deploy Dockerized applications to Cloud Run, integrating with Cloud SQL for data persistence.

5. CI/CD Pipeline Implementation (In-progress)):

   • Automate the deployment workflow using Cloud Build, Artifact Registry, and Cloud Deploy to enable continuous delivery of the web application.

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Key Technologies & Tools Used

• Google Cloud Platform (GCP): VPC, Cloud SQL, Cloud Run, Cloud Build, Artifact Registry, Cloud Deploy
• Python: Automates infrastructure creation (temporary solution; transitioning to Terraform)
• Terraform (planned): Infrastructure-as-Code to replace Python scripts
• Docker: Containerize and deploy the web application on Cloud Run
• SQL Proxy: Secure, private connectivity for Cloud SQL
• CI/CD: Cloud Build, Artifact Registry, and Cloud Deploy for seamless application delivery

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Project Structure

SILLYGULLY_WEBAPP_PROJECT/
│
├── .github/                     # CI/CD workflows for automation
│
├── Infra_python_scripts/        # Python scripts for infrastructure automation
│   ├── cloud_run_setup.py       # Sets up Cloud Run service
│   ├── cloud_sql_setup.py       # Configures and deploys Cloud SQL
│   ├── infra_setup.py           # Manages overall infrastructure setup
│   ├── sql_proxy_setup.py       # Configures SQL Proxy for private connectivity
│   └── vpc_setup.py             # Creates and configures VPC with subnets
│
├── silly-webapp/                # Web application files
│   ├── .env                     # Environment variables for web app
│   ├── app.py                   # Python web app code
│   └── Dockerfile               # Docker configuration for app container
│
├── terraform/                   # Terraform configurations for IaC
│   └── modules/                 # Modular Terraform infrastructure components
│       ├── main.tf              # Main configuration file
│       ├── outputs.tf           # Output values for infrastructure resources
│       ├── terraform.tfvars     # Terraform variable values
│       └── variables.tf         # Variable definitions for Terraform
│
├── .env                         # Project-wide environment variables
├── .gitignore                   # Rules for ignored files and directories
└── README.md                    # Project documentation

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How to Run Locally

1. Clone the Repository:

   git clone https://github.com/hadoopbhanu/sillygully_webapp_code.git
   cd GCP_sillygully_webapp_code

2. Set Up Environment Variables:

   • Create a .env file with the required variables for your GCP project and SQL credentials.

3. Run Python Automation Scripts:

   python3 python-scripts/vpc_creation.py
   python3 python-scripts/cloud_sql_setup.py

4. Push Code to GitHub to Trigger CI/CD:

   git add .
   git commit -m "Initial commit"
   git push origin main

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5. Monitor CI/CD Pipeline in GitHub Actions.

Future Improvements

• Transition all automation scripts to Terraform for better scalability.
• Add dynamic secrets management using Google Secret Manager.
• Extend the application to include Cloud Monitoring and Logging for observability.

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Author Bhanu Koduri