Production-Grade CI/CD Platform for Automated Container Deployments on AWS ECS Fargate
Forgeline is a cloud-native CI/CD platform that automates the complete software delivery lifecycle from source code commits to production deployments. The platform integrates GitHub, Jenkins, Docker, Amazon ECR, AWS ECS Fargate, and Application Load Balancer to deliver secure, scalable, and zero-downtime application releases.
Built around real-world DevOps practices, Forgeline demonstrates automated build pipelines, container image management, deployment orchestration, monitoring, logging, and operational reliability in a production-style AWS environment.
End-to-end automated CI/CD pipeline with zero-downtime deployments
From GitHub commit to live production on AWS
This repository demonstrates a real-world, production-grade CI/CD pipeline that automates the complete lifecycle of deploying a containerized application on AWS.
Whenever code is pushed to GitHub, the pipeline automatically:
- Builds the application
- Creates a Docker image
- Pushes the image to Amazon ECR
- Deploys the application to AWS ECS (Fargate)
- Exposes it via an Application Load Balancer
Once configured, the process requires no manual intervention.
- Fully automated Continuous Integration and Continuous Deployment
- Consistent builds using Docker
- Serverless container execution with AWS Fargate
- Zero-downtime deployments using Application Load Balancer
- Secure IAM role–based AWS access
- Centralized logging, monitoring, and alerting
- Architecture aligned with real production systems
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Step-by-Step Implementation Guide
- STEP 1 – Create EC2 Instance for Jenkins
- STEP 2 – IAM Role Setup
- STEP 3 – Prepare EC2 Server
- STEP 4 – Install and Configure Jenkins
- STEP 5 – Connect Jenkins with GitHub
- STEP 6 – Build Docker Image (CI)
- STEP 7 – Push Docker Image to Amazon ECR
- STEP 8 – Create ECS Cluster
- STEP 9 – Create ECS Task Definition
- STEP 10 – Create ECS Service
- STEP 11 – Create Application Load Balancer
- STEP 12 – Create Target Group
- STEP 13 – Attach Target Group to ECS Service
This project shows how modern DevOps teams design and operate CI/CD pipelines for reliable, repeatable, and safe production deployments. The workflow and architecture mirror what is commonly used in startups, SaaS platforms, and enterprise environments.
| Component | Responsibility |
|---|---|
| GitHub | Source code management and pipeline trigger |
| Jenkins | CI/CD orchestration engine |
| Docker | Application packaging and runtime consistency |
| Amazon ECR | Secure container image registry |
| AWS ECS (Fargate) | Serverless container orchestration |
| Application Load Balancer | Traffic routing and health checks |
This architecture is widely used to:
- Deploy microservices
- Release features continuously
- Reduce deployment risk
- Achieve zero-downtime updates
Understanding this project means understanding how real production deployments work.
Manual deployments are:
- Time-consuming
- Error-prone
- Inconsistent across team members
- Difficult to scale
- Risky in production environments
Automation provides:
- Speed and repeatability
- Predictable deployment behavior
- Safer rollbacks
- Higher system reliability
- Confidence in production releases
| Term | Description | Manual Approval |
|---|---|---|
| Continuous Integration | Automatic build and validation | No |
| Continuous Delivery | Deployment-ready artifacts | Yes |
| Continuous Deployment | Automatic production deployment | No |
This project implements full Continuous Deployment.
- Eliminates manual build and deployment steps
- Ensures environment consistency using containers
- Uses serverless compute to reduce operational overhead
- Provides a stable public endpoint via ALB
- Demonstrates real DevOps workflows used in industry
- Automated deployments on every code change
- Zero-downtime application updates
- Scalable container-based architecture
- Secure image storage and access
- Strong foundation for DevOps interviews
- Reusable design for real-world projects
| Tool | Purpose |
|---|---|
| GitHub | Source control and CI trigger |
| Jenkins | Pipeline orchestration |
| Docker | Containerization |
| Amazon ECR | Docker image registry |
| AWS ECS (Fargate) | Serverless container execution |
| Application Load Balancer | Traffic distribution |
- Developer pushes code to GitHub
- GitHub webhook triggers Jenkins
- Jenkins pulls source code
- Docker image is built
- Image is pushed to Amazon ECR
- ECS service is updated
- Fargate launches new containers
- ALB performs health checks
- Traffic is routed to healthy containers
- Default ECS deployment strategy
- Gradual replacement of running containers
- No service interruption
- Parallel task execution
- Health-check-based traffic routing
- Automatic traffic shifting
- No single point of failure
- IAM roles with least privilege
- No AWS credentials stored in Jenkins
- Private Amazon ECR repositories
- Secure Jenkins credential handling
- Separate security groups for ALB and ECS
- Hardcoded AWS access keys
- Using only the
latestimage tag - Manual ECS restarts
- Over-permissive IAM policies
Ubuntu-based EC2 instance with required network access and storage.
IAM role enabling EC2 to securely interact with ECR and ECS without access keys.
System updates, Docker installation, AWS CLI v2 installation, and IAM verification.
Java installation, Jenkins service setup, plugin installation, and Docker permissions.
Pipeline configured using Jenkinsfile pulled directly from source control.
Docker image built and tagged using Jenkins build numbers.
Secure authentication and automated image publishing.
Serverless ECS cluster using AWS Fargate.
Container configuration, execution role, and logging setup.
Service definition with auto-healing and desired task count.
Public ALB with HTTP listener.
IP-based target group with health checks.
Traffic routing from ALB to ECS tasks with zero downtime.
This project includes production-ready observability:
- Centralized ECS logs in CloudWatch
- ALB health and error monitoring
- ECS service stability metrics
- SNS-based alerting
- Failure simulation for validation
Detailed documentation is available at: Automated Monitoring & Logging for Deployment Issues
This repository demonstrates how modern cloud-native applications are:
- Built
- Deployed
- Monitored
- Operated
The architecture and workflow reflect real DevOps practices used in production environments and provide a strong foundation for professional and enterprise-grade deployments.