When load balancing data centers with all servers active to serve jobs, the result can be excessive energy usage. On the other hand, using dynamic server provisioning, the number of servers that serve requests can be reduced by turning off idle servers and thereby save energy. However, such a scheme, usually increases the risk of instability of server queues. In this work, we analyze the trade-off between energy usage and stability of servers in a data center when we balance the load by dispatching arriving jobs. We propose an algorithm, SEOL, to solve a stability and energy objective stochastic optimization problem with a high degree of flexibility to handle the trade-off between these two objectives. We show the performance of our proposed algorithm in minimizing the risk of queue length growth as well as the number of active servers needed to serve jobs, and compare it with a number of well-established commercial load balancing mechanisms.