The objective of this project is to design and develop a scalable cloud-based web application that uses auto-scaling and load balancing to handle variable traffic efficiently. The system ensures high availability, performance optimization, and resource efficiency, helping students understand cloud scalability and distributed system management.
Study cloud computing fundamentals, web application architecture, and scalability concepts.
Analyze load balancing strategies such as round-robin, least connections, and IP hash.
Study auto-scaling techniques based on CPU, memory, and network usage thresholds.
Prepare Software Requirement Specification (SRS) and system workflow documentation.
Design system architecture including web application instances, load balancer, and auto-scaling group.
Create database schema for users, sessions, application logs, and instance tracking.
Implement secure user authentication and role-based access control.
Deploy multiple instances of the web application to simulate distributed cloud environment.
Configure load balancer to distribute traffic evenly across active instances.
Implement auto-scaling policies to automatically add or remove instances based on load.
Monitor system performance metrics such as response time, throughput, and instance utilization.
Maintain audit logs for scaling actions and load distribution.
Develop dashboards to visualize traffic, instance health, and scaling events.
Perform unit testing, integration testing, and stress testing under varying load scenarios.
Simulate high traffic scenarios to validate auto-scaling and load balancing behavior.
Prepare documentation including ER diagrams, architecture diagrams, workflow diagrams, and test cases.
Deploy the system on local cloud simulation or cloud provider environment for demonstration.
