III:Small:Integrated Problem Diagnosis and Repair in Databases and Storage Area Networks

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Databases are typically used as a subsystem in a larger system thatcontains Web servers, application servers, and network-attachedstorage servers. Such complex systems experience some form of changeall the time, e.g., an update to a Java module in the applicationserver, a statistics update in the database, or a RAID rebuild in astorage volume. Such changes in different subsystems can cause anoverall performance degradation whose cause is hard to diagnose. Thediagnosis task is all the more daunting because enterpriseenvironments have isolated administration teams and tools for eachsubsystem.This project is developing an integrated tool called DIADS thatautomates complex administrative tasks like problem diagnosis, what-ifanalysis, orchestrating disaster recovery, and online tuning when adatabase is used as a subsystem in a larger system. DIADS contains twotechnical innovations. Problem diagnosis involves reconstructingsystem behavior at various points of time using historic and currentmonitoring data collected from the system. However, the amount andquality of monitoring data available from production systems isconstrained by the need to keep monitoring overhead low. DIADS uses anabstraction called Annotated Plan Graph to represent and reason aboutdatabase behavior in the context of a larger system. Annotated PlanGraphs are generated from light-weight monitoring data.The other innovation in DIADS is a suite of workflows foradministrative tasks that combine machine-learning techniques withdomain knowledge from system experts. For example, for problemdiagnosis, the machine-learning part of the workflow provides coretechniques to handle large and noisy streams of monitoring data, whilethe domain-knowledge part acts as checks-and-balances to guide thediagnosis in the right direction. This unique design enables DIADS tofunction effectively even in the presence of multiple concurrentproblems as well as noisy monitoring data prevalent in productionenvironments. DIADS is being prototyped for research and educationalpurposes in a datacenter setting with PostgreSQL databases and anenterprise-level storage area network. For further information see the project web page at http://www.cs.duke.edu/~shivnath/diads.html