Recently, Service-level agreement (SLA) is deemed to be an integral aspect for ondemand provisioning of scalable resources on Cloud. SLA defnes important constraints for instance guaranteed quality of service (QoS), pricing, fault-tolerant availability, security, and period of service. Currently, there is a dire need of SLA-based scheduling that improves resources utilization on Cloud. Scheduling with reduced execution time and cost may adversely afect resource utilization. To overcome this issue, we present a cost-efcient SLA-based load balancing scheduler, namely SLARALBA, for heterogeneous Cloud infrastructures. The proposed technique supports three levels of SLA opted by the Cloud users. The proposed novel technique incorporates the execution cost for the successful execution of users’ services to elevate the resource utilization on Cloud. The SLA-RALBA is simulated for performance analysis using the benchmark GoCJ and HCSP datasets. The performance results of the SLA-RALBA are compared with the existing schedulers, namely ExecutionMCT, Proft-MCT, SLA-MCT, Execution-Min-Min, Proft-Min-Min, and SLA-MinMin in terms of average resource utilization, execution time, and cost of the Cloud services. The obtained results reveal that SLA-RALBA provides an even trade-of between execution time and cost of the services by guaranteeing a drastic improvement in resource utilization on Cloud than existing algorithms