Load balancing optimizes cloud performance by automatizing distribution of resources. With demand for cutting-edge cloud services, efficient algorithms are vital. Challenges include ensuring service reliability, meeting QoS, and fulfilling CSP contracts. Effective workload mapping boosts performance but is complex. Metaheuristics efficiently address these issues. This review analyzes current load-balancing techniques—genetic techniques, round-robin technique, ant colony optimization, and nature-inspired techniques. We evaluate how they affect the ability of the cloud to improve scalability, use resources, and work well. Integration of AI and ML is very significant trend which is aimed at improving efficiency. I look forward to this research focusing on how we can automate and improve the methods.