The characterization of distributed n-tier application performance is an important and challenging problem due to their complex structure and the significant variations in their workload. Theoretical models have difficulties with such wide range of environmental and workload settings. Experimental approaches using manual scripts are error-prone, time consuming, and expensive. We use code generation techniques and tools to create and run the scripts for large-scale experimental observation of n-tier benchmarking application performance measurements over a wide range of parameter settings and software/hardware combinations. Our experiments show the feasibility of experimental observations as a sound basis for performance characterization, by studying in detail the performance achieved by (up to 3) database servers and (up to 12) application servers in the RUBiS benchmark with a workload of up to 2700 concurrent users.
['Calton Pu', 'Akhil Sahai', 'Jason Parekh', 'Gueyoung Jung', 'Ji Bae', 'You-Kyung Cha', 'Timothy Garcia', 'Danesh Irani', 'Jae Lee', 'Qifeng Lin']
An Observation-Based Approach to Performance Characterization of Distributed n-Tier Applications