Scalable Web Application Deployment Using Auto Scaling, Load Balancer, And RDS

The rapid growth of web applications and the increasing demand for high availability, scalability, and performance have made traditional deployment methods inadequate. This project, titled “Scalable Web Application Deployment Using Auto Scaling, Load Balancer, and RDS,” focuses on creating a robust and efficient infrastructure for deploying web applications on the cloud. The main goal is to ensure that the application can automatically adapt to changing workloads while maintaining optimal performance and availability. The proposed system utilizes Amazon Web Services (AWS) as the cloud platform. Key components include Auto Scaling, which dynamically adjusts the number of EC2 instances based on demand; an Elastic Load Balancer (ELB) that distributes incoming traffic evenly across multiple instances to prevent overloading; and Amazon RDS (Relational Database Service) for a scalable and managed database solution. This architecture ensures that the application remains responsive and cost-effective even under varying traffic conditions. The implementation involves configuring a web server environment using EC2 instances, integrating the load balancer, setting up Auto Scaling policies based on CPU utilization, and deploying the backend database using Amazon RDS. Security, fault tolerance, and performance optimization techniques are also applied to ensure a production-ready environment. This project demonstrates the benefits of using cloud-native services to automate deployment processes and enhance application resilience. It significantly reduces manual intervention, minimizes downtime, and ensures that the application can scale in and out based on real- time user demand. The outcome is a highly available, fault-tolerant, and cost-efficient deployment model suitable for modern web applications.