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Static scheduling and execution of Grid workflows is prone to severe performance losses due to inaccurate predictions or the dynamic nature of the Grid environment. In this paper we present an online tool for analysing the performance overheads that appear during the real-time execution of workflow applications in Grid environments. We employ event correlation techniques and a distributed superpeer architecture in which each peer correlates local lowlevel activity and middleware events to infer performance overheads related to larger workflow regions at a higher level of abstraction. The rule-based correlation technique provides full extensibility to our approach that requires no source code modification. We demonstrate the functionality of our tool through online performance analysis of a real-world workflow application executed in a Grid environment. We present automatically generated online graphs of correlated events that promptly signal to the end-users the real reasons of run-time performance overheads in their executions.