Applications that are exposed to large-scale workloads must ensure elasticity, that is the ability to scale up and down rapidly to meet the demand. Cloud infrastructures provide adaptation tasks, which allow applications to automatically scale up and down straightforwardly. These adaptation tasks drive the system to new states, which may expose implementation errors and therefore must be tested. In this paper, we focus on testing elastic applications during dier-ent elasticity-related states. This test is dicult since the elasticity states are not directly controlled by the tester. To execute the test at dierent elasticity-related states, we propose a monitoring-based procedure. This procedure consists in monitoring the resource status to identify the occurrences of the elasticity states at real-time, and in parallel, execute the state-related tests. To validate our test procedure, we performed experiments on Amazon EC2. These experiments successfully identied non-functional errors.