Microsoft Research Audio 104043: Enabling what-if explorations in distributed systems

With a large percentage of total system cost going to system administration tasks, self-management remains a difficult and important goal in systems. As a step towards the self-management vision, I will present a framework we have developed that enables systems to be self-predicting and answer “what-if” questions about their behavior with little or no administrator involvement. We have built a Resource Advisor inside two real systems: Microsoft's SQL Server database and the Ursa Minor storage system at Carnegie Mellon University. The Resource Advisor helps with upgrade and data placement decisions and provides what-if interfaces to external administrators (and internal tuning modules). The Resource Advisor is based on efficient system behavioral models that enable robust predictions in multi-tier systems.

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