Advancements in science and technology have led to increased complexity in computing systems. With a growing number of heterogeneous software and hardware components, computing systems are becoming more and more difficult to monitor, manage and maintain. The goal of this project is to develop an integrated framework on mining log data for automatic system management. The project is conducting research on: (1) developing new methods and tools for log data organization which create consistency and improve the ability to correlate across multiple log files; (2) developing new methods and tools for data-driven pattern discovery and problem determination; and (3) developing new methods and tools to bridge the gap between the system management applications and the intelligent techniques. The integrated framework resulting from this research will provide much better techniques for monitoring, analyzing, and adapting complex computing systems. Results from this research will be disseminated through publications and the software tools being made publicly available through a web portal. The educational component of this project includes developing a new curriculum that incorporates research into the classroom and provides women, minorities, and undergraduate students with opportunities to participate research. Florida International University (FIU) is among the top awarders of computer science degrees to Hispanic students in the USA and its history of involving the participation of underrepresented groups in the research efforts will be leveraged during the course of this project. This project will also strengthen industry research collaborations and have immediate applications to fields other than system management.