AI powered Load Balancer in Cloud Computing

As cloud computing underpins critical infrastructure across industries, ensuring optimal performance and robust security has become imperative. This work presents an AI-powered load balancing system designed to manage traffic dynamically while enhancing security in cloud environments. Leveraging machine learning models for traffic prediction and reinforcement learning for dynamic allocation, the system could minimize latency and maximize throughput. A multi-layered security framework can help in deep packet inspection and AI-based anomaly detection to mitigate cyber threats. Results that were obtained through extensive testing and analysis show that the system significantly improves both traffic distribution and threat detection capabilities compared to traditional methods. This work provides a roadmap for next generation smart, secure, and scalable load balancers.