Automated web performance analysis, with a special focus on prediction

ABSTRACT

Today the performance of web systems is getting ever more important, as the number of users and competitors is still increasing. Therefore performance analysis tools gain importance too. There are currently several tools on the market that ensure and test for adequate performance. There are a number of simulation tools and monitoring tools, but only few that automatise and combine both approaches.

This paper outlines a system that is capable of (a) automatically creating a web performance simulation and (b) conducting trend analysis of the system under test (SUT). The system requires input information like monitoring points and static-information about the SUT. Based on this information a simulation model of the system is generated. Then the simulation model is refined stepwise e.g. by adding or removing connections between the model components or adjusting the parameters until the aimed accuracy is achieved. By using this simulation model the prediction module creates an analysis of the SUT, and thereby provides as much information as possible about the current state of the system and potential trends. This predictive information can be used for pro-active server tuning or other performance optimisations.

The special focus of this work is on the adjustment and prediction parts of the system described here. For all the other parts existing tools and techniques will be used wherever possible.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.4 Model Validation and Analysis

Additional Classification:
  I. Computing Methodologies
  I.6 SIMULATION AND MODELING
      I.6.7 Simulation Support Systems

Keywords:
adjustment, performance simulation, prediction, queuing-network-simulation, time-series-analysis