The pay-as-you-go economic model of cloud computing leads naturally to an earn-as-you-go profit model for many cloud based services. These applications can benefit from low level analyses for cost optimization and verification. Testing cloud applications to ensure they meet monetary cost objectives has not been well explored in the current literature. We present a static analysis approach for determining which control flow paths in cloud applications can exceed a cost threshold. We build on tools used in Worst Case Execution Time analysis that provide a tight bound on processing time, and we implement provisions for adding bandwidth, storage, and service costs. Our approach determines the magnitude of cost excess for nodes in an application's call graph so that cloud developers can better understand where to focus their efforts to lower costs (or deem some excesses acceptable based on business case analysis).