Cloud computing allows customers to allocate cloud resources as needed. Improving Quality of Service (QoS) in cloud computing systems is a difficult task, especially given the rising demand from customers and the need to comply with Service Level Agreements (SLA). Dynamic resource provisioning is necessary for effective resource management in a cloud computing environment. Genetic Algorithm (GA) integration for scheduling user requests. The integration of GAs in scheduling user requests is a significant aspect of this process. Research has proven that these algorithms successfully search large solution spaces for the best or near-best answers to complex optimization problems. This is why they seem to be very suitable for this research application. We will integrate the SLA negotiation methods into our proposed algorithm to deal with an important aspect of cloud service delivery: reducing SLA violations and the penalty fees charged. This is a significant source of customer dissatisfaction and can compromise the reputation of Cloud Service Provider (CSP). Our research advances cloud computing with a method to optimize resource distribution while resolving the contractual obligations of clients and service providers.