This project demonstrates the deployment of a microservices-based application using Kubernetes (K8s) on Azure Cloud, following best practices in:

✅ Automation (Infrastructure as Code, GitOps) ✅ CI/CD (Continuous Integration & Deployment) ✅ IaC (Infrastructure as Code using Terraform) ✅ Observability (Monitoring, Logging, and Tracing)

The microservices application consists of:

• Frontend (Angular)
• Backend services (Node.js, Spring Boot, Go)
• Database (PostgreSQL, Redis)
• API Gateway (NGINX)

Deployed in an AKS (Azure Kubernetes Service) cluster with NGINX Ingress Controller for traffic routing.

1. Infrastructure Setup (IaC)

   • Use Terraform to provision GKE, networking, and databases.
   • Secure configurations using GitHub Secrets.

2. Containerization & CI/CD

   • Build & push Docker images to Google Artifact Registry.
   • Use GitHub Actions to deploy workloads.

3. Kubernetes Deployment

   • Set up Ingress & Service Mesh.
   • Configure autoscaling & security policies.

4. Observability & Security

   • Monitor logs with Prometheus, Grafana.
   • Implement Network Policies.

📅 Date: 2025-04-23 🌐 Cluster: GKE with infrastructure automated via Terraform 🔒 Focus: Security, scalability, and continuous quality

• Implemented Namespaces:

  • frontend: user-facing applications
  • backend: business logic services
  • database: persistence services
  • monitoring: observability tools (Prometheus, Grafana, Sonar)

• NGINX Ingress configured to:

  • Expose only necessary services publicly
  • Apply centralized security and routing rules

• Terraform used to provision cluster and resources

• GitHub Actions workflows for:

  • Building and pushing images to private registry
  • Automatic deployment on image updates
  • Tests and static analysis using SonarQube

• Monitoring stack: Prometheus + Grafana

• Security:

  • Workload Identity
  • Secrets managed via GitHub Secrets
  • Network Policies enforced

• Node pools by service type
• Cluster-level Load Balancer enabled