Non-intrusive transaction monitoring using system logs

We consider the problem of online monitoring of transaction instances in enterprise environments, based on footprints left by the instances in system logs and using a state-based reference model of the transaction. Unlike existing approaches, we do not rely on any platform-specific knowledge, neither do we assume footprints to carry correlating identifiers, as injected through instrumentation. We outline a solution for tracking transaction instances at individual and aggregate levels, present preliminary results on theoretical analysis of monitoring precision and conclude with directions of ongoing and future research.