CAREER: Querying and Controlling Systems

Duke University, Durham NC

Investigators

Abstract

The increasing complexity, scale, and dynamics of networked computing systems make it hard for users and system administrators to understand and control these systems. A significant fraction of time and money is spent tackling unexpected system performance problems or tuning large systems with many components, the performance of which depends on thousands of dependencies and parameters. This problem is tackled by the Ques project using innovative data management techniques. Ques treats a computing system as a rich source of data about system configuration and activity, available typically as continuous, rapid, and time-varying data streams. System administrators are given the ability to pose a broad range of system management queries over this data. Ques addresses challenges in developing simple and intuitive ways to express these queries, processing the queries automatically and efficiently using query execution plans, and controlling systems based on statistical and performance models learned from system data. A fully functional prototype of Ques is developed and deployed in a real world setting. The ideas from Ques are incorporated into two new courses for graduate and undergraduate students at Duke. Automated plan generation algorithms for complex system management queries will have a major impact towards making systems more manageable by human administrators. The source code of Ques will be released publicly and the technology will be migrated potentially to industrial strength system management products. Results from Ques will be disseminated via the project Web site (http://www.cs.duke.edu/~shivnath/ques.html).