- Abstract
- Introduction
- Problem Statement
- Existing System
- Limitations of Existing System
- Proposed System
- Objectives
- Scope of Project
- Methodology
- System Architecture
- Technology Stack
- Core Concepts
- AWS EC2 Detailed Explanation
- Docker Detailed Explanation
- Ubuntu Linux Fundamentals
- Implementation Plan
- Step-by-Step Implementation
- Security and Networking
- Testing and Validation
- Results and Observations
- Benefits of the System
- Comparative Analysis
- Performance Analysis
- Cost Analysis
- Challenges Faced
- Limitations
- Future Enhancements
- Real-World Applications
- Conclusion
This project demonstrates the deployment of a cloud-native application using Docker on an AWS EC2 instance running Ubuntu Linux. The aim is to eliminate inconsistencies between development and production environments through containerization.
The application is packaged along with all required dependencies into a Docker container and deployed on a cloud server. This ensures portability, scalability, and consistent execution.
In modern software development, deployment plays a critical role in the success of an application. Many applications fail not because of incorrect logic but due to improper deployment practices.
Traditional deployment methods involve manual installation and configuration, which often leads to inconsistencies. DevOps practices address these challenges by introducing automation, containerization, and cloud infrastructure.
This project demonstrates how Docker and AWS EC2 can be used together to build a reliable deployment pipeline.
The primary issues addressed in this project include:
- Applications behave differently across environments
- Manual deployment introduces errors
- Dependency management is complex
- Scaling applications is difficult
There is a need for a system that ensures consistent deployment across all environments.
In traditional systems:
- Applications are developed locally
- Deployment is done manually on servers
- Dependencies are installed individually
- Configuration is performed manually
This approach leads to inefficiencies and inconsistencies.
The traditional deployment approach has several drawbacks:
- Time-consuming setup
- High probability of human error
- Lack of scalability
- Poor portability
- Requires constant manual intervention
The proposed system utilizes:
- AWS EC2 as the cloud infrastructure
- Ubuntu Linux as the operating system
- Docker for containerization
The application runs inside a Docker container, ensuring a consistent and isolated environment.
The objectives of this project are:
- Deploy an application on AWS EC2
- Use Docker for containerization
- Ensure environment consistency
- Simplify the deployment process
This project is useful for:
- Learning DevOps fundamentals
- Understanding cloud deployment
- Building scalable systems
- Real-world application hosting
The project follows these steps:
- Set up AWS EC2 instance
- Install Ubuntu Linux
- Install Docker
- Create Docker container
- Deploy application
User → Browser → EC2 Public IP → Docker Engine → Application Container
- AWS EC2
- Ubuntu Linux
- Docker
- SSH
Cloud computing provides computing resources over the internet instead of local machines.
A virtual machine is a software-based system that acts like a physical computer.
Containerization packages an application along with its dependencies.
DevOps integrates development and operations to improve deployment efficiency.
Amazon EC2 is a scalable virtual server used for hosting applications.
- Elastic scalability
- Pay-as-you-go pricing
- Secure infrastructure
- AMI (Amazon Machine Image)
- Instance type
- Security groups
- Key pairs
Docker is a containerization platform used to package applications.
- Docker Engine
- Docker Image
- Docker Container
- Dockerfile
- Portability
- Isolation
- Efficiency
Ubuntu is a widely used Linux distribution for servers.
- apt (package manager)
- chmod (permissions)
- ssh (remote login)
The implementation is divided into phases:
- Phase 1: EC2 setup
- Phase 2: Docker installation
- Phase 3: Application deployment
- Choose Ubuntu AMI
- Configure security groups
- Download key pair
ssh -i key.pem ubuntu@<ip-address>sudo apt update && sudo apt upgrade -ysudo apt install docker.io -ysudo systemctl start dockerFROM python:3.9
WORKDIR /app
COPY . .
RUN pip install -r requirements.txt
CMD ["python", "app.py"]docker build -t my-app .docker run -d -p 80:8000 my-app- Open port 80 for HTTP traffic
- Use SSH key-based authentication
- Restrict inbound traffic using security groups
- Verify container status using
docker ps - Access application via browser
- Check logs for errors
- Application deployed successfully
- Accessible via public IP
- Stable and consistent performance
- Consistent deployment
- Reduced setup time
- High scalability
- Efficient resource utilization
- Manual vs automated deployment
- Error-prone vs consistent environment
- Lightweight vs heavy
- Faster startup vs slower
Docker containers offer improved performance due to reduced overhead compared to virtual machines.
- AWS Free Tier minimizes cost
- Efficient resource utilization reduces expenses
- Docker permission issues
- Network configuration problems
- Debugging deployment errors
- Single server deployment
- No automatic scaling
- CI/CD pipeline integration
- Kubernetes orchestration
- Monitoring and logging tools
- Web applications
- SaaS platforms
- Microservices architecture
This project demonstrates an efficient and scalable deployment strategy using Docker and AWS EC2. It ensures consistency, portability, and reliability in application deployment.