As more and more information systems are moving to the cloud, there have been efforts to deploy publishsubscribe (or pub/sub) systems in the cloud environment to take advantage of the elasticity of resources. As a result, there is a need to perform resource management for the cloudbased pub/sub systems that support various types of jobs, each consists of a series of tasks, or a workflow. Designing an efficient and effective resource management approach for the cloudbased pub/sub system is challenging because such an approach needs to be able to support flexible provisioning strategies, model the complex interactions between heterogeneous types of jobs, and provide dynamic resource allocation capability. In this paper, we formulate the resource management problem of elastic pub/sub system as optimization problems using different objectives functions. We model the elastic pub/sub system as a multiple-class open queuing network to derive system performance measures, and propose greedy algorithms to efficiently solve the optimization problems. Our evaluation based on simulation on real system show that our proposed solution outperforms the baseline and is robust in dealing with high-volume and fast-changing workload.