A comprehensive Python web application demonstrating enterprise-grade DevOps practices with a complete CI/CD pipeline, Infrastructure as Code, GitOps implementation, and comprehensive monitoring.
This project showcases a Solar System visualization web application built with modern DevOps practices, featuring:
|
|
You can view the architecture diagram below for a visual overview of the system design:
📱 Application Stack
| Technology | Purpose | Version |
|---|---|---|
 |
Frontend Structure | Latest |
 |
Styling & Animations | Latest |
 |
Interactive UI | ES6+ |
 |
Backend API | 3.x |
 |
Database | Latest |
 |
Testing Framework | Latest |
🚀 DevOps & Infrastructure
| Category | Technologies |
|---|---|
| 🐳 Containerization |  Multi-stage builds |
| ☸️ Orchestration |   Charts |
| ☁️ Cloud Provider |  (EKS, VPC, Load Balancers, S3) |
| 🏗️ Infrastructure as Code |  with modular design |
| 🔄 CI/CD |  with workflow orchestration |
| 🚀 GitOps |  for automated deployments and drift detection |
| 📦 Container Registry |  +  |
🚀 Scalability & Auto-scaling
| Tool | Purpose |
|---|---|
 |
Auto-scaling and resource management |
📊 Monitoring & Observability
| Tool | Purpose |
|---|---|
 |
Metrics collection and alerting |
 |
Visualization dashboards and analytics |
| 🔍 Health Checks | Built-in health checks and structured logging |
💡 Tip: Make sure you have the following tools installed and configured before starting:
|
|
|
|
|
|
Follow these steps to get your Solar System DevOps application up and running:
git clone https://github.com/karimzakzouk/graduation-project-devops.git
cd graduation-project-devopsUpdate the Terraform/2-backend.tf file with your S3 bucket details for Terraform remote state storage.
Navigate to the Terraform directory and initialize the deployment:
cd Terraform/
terraform init
terraform apply -auto-approve⏳ This will provision: VPC, EKS cluster, ArgoCD, and the monitoring stack.
After Terraform completes, it will output the command to configure kubectl. Run that command to connect to your new EKS cluster.
The CI/CD pipeline handles this automatically. To deploy manually:
kubectl apply -f argocd/application.yaml🗂️ Click to expand project structure
├── 📱 Application Code
│ ├── app.py # Main Python application
│ ├── app_test.py # Test suites
│ ├── index.html # Frontend UI
│ └── Dockerfile # Container definition
│
├── ☸️ Helm
│ └── helm/
│ ├── Chart.yaml # Helm chart metadata
│ ├── values.yaml # Configuration values
│ └── templates/ # Kubernetes manifests
│
│
├── 🏗️ Terraform
│ ├── 0-versions.tf # Provider versions
│ ├── ... # Main infrastructure files
│ └── modules/
│ ├── vpc/ # VPC module
│ └── eks/ # EKS cluster module
├── 🚀 Scalability (Karpenter)
│ └── karpenter/
│ └── karpenter-resources.yaml # Auto-scaling configuration
│
├── 📊 Monitoring & GitOps
│ └── argocd/
│ ├── monitoring.yml # Prometheus & Grafana configuration
│ └── application.yml # Application dashboards
│
├── 🔄 CI/CD Workflows
│ └── .github/workflows/
│ ├── main-pipeline.yml # Orchestrator workflow
│ ├── ci.yml # Test, quality checks & SonarQube
│ ├── docker.yml # Container build & push
│ ├── terraform.yml # Infrastructure deployment
│ ├── karpenter.yml # Auto-scaling provisioner
│ ├── argocd.yml # GitOps controller setup
│ ├── monitoring.yml # Observability stack deployment
│ └── deploy.yml # Application deployment
├── 🔧 backend/
│ └── main.tf # Terraform S3 & DynamoDB
│
└── 🖼️ Static Assets
└── static/ # Planet images & backgrounds
|
|
|
🔍 Detailed Workflow Breakdown
- Orchestrates all sub-workflows (CI, Docker, Terraform, etc.)
- Allows configurable skips for faster development cycles
- Runs unit tests and code coverage
- Enforces quality gates before allowing code to be merged
- Builds multi-architecture container images
- Scans images for vulnerabilities and pushes to multiple registries
- Manages infrastructure provisioning and updates via IaC
- Uses an S3 backend for secure state management
- Manages auto-scaling and resource management
- Manages monitoring stack deployment
- Manages ArgoCD deployment and drift detection
- Manages application deployment
|
Git repository serves as the single source of truth for all deployments |
ArgoCD continuously monitors Git repo and automatically syncs changes to cluster |
Automatically corrects configuration drift to ensure live state matches desired state |
Easily revert to previous stable application states with a single command |
|
|
|
|
|
|
|
Contributions are welcome! If you have suggestions for improvement, please open an issue or submit a pull request.
- 🍴 Fork the Project
- 🌿 Create your Feature Branch
git checkout -b feature/AmazingFeature
- 💾 Commit your Changes
git commit -m 'Add some AmazingFeature' - 📤 Push to the Branch
git push origin feature/AmazingFeature
- 🔄 Open a Pull Request
