%0 Conference Proceedings
%T Predico: A System for What-if Analysis in Complex Data Center Applications
%+ University of Massachusetts Medical School [Worcester] (UMASS)
%+ Tata Research Development and Design Center (TRDDC)
%A Singh, Rahul
%A Shenoy, Prashant
%A Natu, Maitreya
%A Sadaphal, Vaishali
%A Vin, Harrick
%Z Part 3: Storage and Performance Management
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 12th International Middleware Conference (MIDDLEWARE)
%C Lisbon, Portugal
%Y Fabio Kon
%Y Anne-Marie Kermarrec
%I Springer
%3 Middleware 2011
%V LNCS-7049
%P 123-142
%8 2011-12-12
%D 2011
%R 10.1007/978-3-642-25821-3_7
%Z Computer Science [cs]
%Z Computer Science [cs]/Networking and Internet Architecture [cs.NI]Conference papers
%X Modern data center applications are complex distributed systems with tens or hundreds of interacting software components. An important management task in data centers is to predict the impact of a certain workload or reconfiguration change on the performance of the application. Such predictions require the design of “what-if” models of the application that take as input hypothetical changes in the application’s workload or environment and estimate its impact on performance.We present Predico, a workload-based what-if analysis system that uses commonly available monitoring information in large scale systems to enable the administrators to ask a variety of workload-based “what-if” queries about the system. Predico uses a network of queues to analytically model the behavior of large distributed applications. It automatically generates node-level queueing models and then uses model composition to build system-wide models. Predico employs a simple what-if query language and an intelligent query execution algorithm that employs on-the-fly model construction and a change propagation algorithm to efficiently answer queries on large scale systems. We have built a prototype of Predico and have used traces from two large production applications from a financial institution as well as real-world synthetic applications to evaluate its what-if modeling framework. Our experimental evaluation validates the accuracy of Predico’s node-level resource usage, latency and workload-models and then shows how Predico enables what-if analysis in two different applications.
%G English
%Z TC 6
%Z WG 6.1
%2 https://inria.hal.science/hal-01597773/document
%2 https://inria.hal.science/hal-01597773/file/978-3-642-25821-3_7_Chapter.pdf
%L hal-01597773
%U https://inria.hal.science/hal-01597773
%~ LORIA2
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC6
%~ IFIP-WG6-1
%~ IFIP-MIDDLEWARE
%~ IFIP-LNCS-7049