This project demonstrates a production-grade DevOps CI/CD pipeline for deploying a containerized Node.js application to Microsoft Azure using modern cloud-native technologies.

The pipeline automates the full application lifecycle:

Code → Build → Security Scan → Containerize → Push → Deploy → Monitor

This project demonstrates how a Node.js application can be deployed using a complete DevOps workflow.

Key features implemented:

• CI/CD automation using GitHub Actions
• Infrastructure provisioning using Terraform
• Containerized Node.js application using Docker
• Container vulnerability scanning using Trivy
• Blue-Green deployment using Azure Container Apps revisions
• Manual approval gate before production deployment
• Monitoring and logging using Azure Monitor and Log Analytics

• Automated CI/CD pipeline
• Infrastructure as Code using Terraform
• Container security scanning
• Blue-Green deployment strategy
• Revision-based rollback capability
• Production approval gate
• Monitoring and observability
• Operations runbook

The application is deployed using Azure Container Apps.

Example endpoint format:

https://devops-app-prod..azurecontainerapps.io

Developer
   │
   ▼
GitHub Repository
   │
   ▼
GitHub Actions CI/CD Pipeline
   │
   ├── Build Node.js Application
   ├── Run Tests
   ├── Security Scan (Trivy)
   ├── Build Docker Image
   └── Push Image → Azure Container Registry
   │
   ▼
Deployment Workflow
   │
   ├── Deploy to Dev Environment
   ├── Manual Approval Gate
   └── Deploy to Production
   │
   ▼
Azure Container Apps
   │
   ├── Node.js Container
   ├── Blue-Green Deployment
   ├── Revision-Based Releases
   └── Traffic Splitting
   │
   ▼
Azure Monitor + Log Analytics
   │
   ├── Application Logs
   ├── Container Metrics
   └── Alerts

1️⃣ Developer pushes Node.js code to GitHub

2️⃣ GitHub Actions CI pipeline starts automatically

3️⃣ Application build and tests run

4️⃣ Trivy scans the container image for vulnerabilities

5️⃣ Docker image is built

6️⃣ Image pushed to Azure Container Registry

7️⃣ Application deployed to Dev environment

8️⃣ Manual approval required for Production deployment

9️⃣ Production deployment executed

🔟 Monitoring and logs collected via Azure Monitor

Azure Container Apps supports revision-based deployments, enabling safe releases without downtime.

Traffic can be gradually shifted between versions.

Example traffic distribution:

After validation:

Rollback can be performed instantly by switching traffic back.

Monitoring is implemented using Azure Monitor and Log Analytics.

Metrics available:

• CPU usage
• Memory usage
• Request metrics
• Replica count

Logs available:

• Node.js application logs
• Container runtime logs
• System logs

Example Log Analytics query:

ContainerAppConsoleLogs_CL | limit 50

Infrastructure resources are provisioned using Terraform.

Provisioned resources include:

• Azure Resource Group
• Azure Container Registry
• Azure Container App
• Log Analytics Workspace
• Managed Identity
• RBAC Role Assignments

Terraform state is stored remotely using Azure Storage backend.

devops-azure-github-actions-project

app/ Dockerfile Node.js application

terraform/ main.tf variables.tf backend.tf

.github/workflows/ pipeline.yml

screenshots/ architecture-diagram.png pipeline.png blue-green.png traffic.png

monitoring/ 01-container-cli-logs.png 02-container-revision-details.png 03-application-runtime-logs.png 04-container-port-configuration.png 05-log-analytics-tables.png 06-log-analytics-query-results.png 07-container-metrics-dashboard.png

README.md

az containerapp revision restart --name devops-app-prod --resource-group devops-gha-rg

az containerapp logs show --name devops-app-prod --resource-group devops-gha-rg

az containerapp revision list --name devops-app-prod --resource-group devops-gha-rg --output table

az containerapp ingress traffic set --name devops-app-prod --resource-group devops-gha-rg --revision-weight devops-app-prod-0000001=100

Key metrics available:

• CPU usage
• Memory usage
• Request rate
• Replica scaling

Security scanning is implemented using Trivy.

The CI pipeline scans Docker images for vulnerabilities and blocks deployment if critical issues are detected.

Possible enterprise enhancements:

• Canary deployments
• Automatic rollback based on health checks
• Prometheus & Grafana integration
• Multi-region deployment
• GitOps workflow using ArgoCD
• Automated alerting

If you find this project helpful:

⭐ Star the repository 🍴 Fork the project 🐞 Open issues for improvements

Pavan Kumar Gummadi

DevOps Engineer | Cloud & CI/CD Enthusiast

GitHub https://github.com/cloudwithpavan

Email pavan7071@gmail.com