PseudoApp: Performance prediction for application migration to cloud

To migrate an existing application to cloud, a user needs to estimate and compare the performance and resource consumption of the application running in different clouds, in order to select the best service provider and the right virtual machine size. However, it is prohibitively expensive to install a complex application in multiple new environments solely for the purpose of performance benchmarking. Performance modeling is more practical but the accuracy is limited by system factors that are hard to model. We propose a new technique called PseudoApp to address these challenges. Our solution creates a pseudo-application to mimic the resource consumption of a real application. A pseudo-application runs the same set of distributed components and executes the same sequence of system calls as those of the real application. By benchmarking a simple and easyto-install PseudoApp in different cloud environments, a user can accurately obtain the performance and resource consumption of the real application. We apply PseudoApp to Apache and TPC-W and find that PseudoApp accurately predicts their performance with 2-8% error in throughput.

[1]  Jose Renato Santos,et al.  JustRunIt: Experiment-Based Management of Virtualized Data Centers , 2009, USENIX Annual Technical Conference.

[2]  Sally A. McKee,et al.  Efficiently exploring architectural design spaces via predictive modeling , 2006, ASPLOS XII.

[3]  Kristof Beyls,et al.  Reuse Distance as a Metric for Cache Behavior. , 2001 .

[4]  Christopher Stewart,et al.  A Dollar from 15 Cents: Cross-Platform Management for Internet Services , 2008, USENIX Annual Technical Conference.

[5]  The Force.com Multitenant Architecture Understanding the Design of Salesforce.com's Internet Application Development Platform , .

[6]  Chun Zhang,et al.  vPath: Precise Discovery of Request Processing Paths from Black-Box Observations of Thread and Network Activities , 2009, USENIX Annual Technical Conference.

[7]  Lieven Eeckhout,et al.  Performance prediction based on inherent program similarity , 2006, 2006 International Conference on Parallel Architectures and Compilation Techniques (PACT).

[8]  Louis P. Slothouber,et al.  A Model of Web Server Performance , 1996 .

[9]  Wei Jin,et al.  USENIX Association Proceedings of USITS ’ 03 : 4 th USENIX Symposium on Internet Technologies and Systems , 2003 .

[10]  Alan Fekete,et al.  Application migration to cloud: a taxonomy of critical factors , 2011, SECLOUD '11.

[11]  Christopher Stewart,et al.  Performance modeling and system management for multi-component online services , 2005, NSDI.

[12]  Gregory R. Ganger,et al.  Modeling the relative fitness of storage , 2007, SIGMETRICS '07.

[13]  John M. Mellor-Crummey,et al.  Cross-architecture performance predictions for scientific applications using parameterized models , 2004, SIGMETRICS '04/Performance '04.