Simulation-Based Analysis of a Platform as a Service Infrastructure Performance from a User Perspective
This paper describes analysis of a real-world case where growing up Platform as a Service (PaaS) provider faced and solved problems with scaling cloud-based infrastructure. Scientific, Petri net-based method was used to asses decisions taken by Heroku – the PaaS manager – and legitimacy of claims of the PaaS clients caused by not satisfying efficiency of the new solutions. Exhaustive information provided in the Internet by both parties of the conflict were used in order to create model of the application and infrastructure corresponding to the real case. The model was then used to perform reliable simulations and show that while the client’s claims were well founded, but growth of the PaaS infrastructure forced and justified changes in the management algorithms.
KeywordsPaaS Performance Model Simulation Petri nets TCPN
The equipment used for this research was purchased within the project no RPPK.01.03.00-18-003/10, which was co-financed by the European Union from the European Regional Development Fund within Regional Operational Program for the Podkarpackie Region for 2007–2013.
Author expresses his gratitude to dr Dariusz Rzońca for his valuable remarks that helped to improve this paper.
- 3.Takefusa, A., Tatebe, O., Matsuoka, S., Morita, Y.: Performance analysis of scheduling and replication algorithms on grid datafarm architecture for high-energy physics applications. In: Proceedings of the 12th IEEE International Symposium on High Performance Distributed Computing (HPDC-2012), pp. 34–43 (2003)Google Scholar
- 4.Ranganathan, K., Foster, I.: Decoupling computation and data scheduling in distributed data-intensive applications. In: Proceedings of 11th IEEE International Symposium on High Performance Distributed Computing (HPDC-2011), Edinburgh, July 2002Google Scholar
- 5.Dobre, C., Pop, F., Cristea, V.: New trends in large scale distributed systems simulation. In: Internatioal Conference on Parallel Processing Workshops ICPPW, pp. 182–189 (2009)Google Scholar
- 7.Sulistio, A., Yeo, C.S., Buyya, R.: Simulation of Parallel and Distributed Systems: A Taxonomy and Survey of Tools. http://www.cs.mu.oz.au/~raj/papers/simtools.pdf
- 8.Zhou, J., Zhou, B., Li, S.: Automated model-based performance testing for PaaS cloud services. In: Computer Software and Applications Conference Workshops (COMPSACW), pp. 644–649, July 2014Google Scholar
- 9.Zhang, W., Huang, X., Chen, N., Wang, W., Zhong, H.: PaaS-oriented performance modeling for cloud computing. In: Computer Software and Applications Conference (COMPSAC), pp. 395–404, July 2012Google Scholar
- 12.Rząsa, W.: Timed colored petri net based estimation of efficiency of the grid applications. Ph.D. AGH University of Science and Technology, Kraków, Poland (2011)Google Scholar
- 14.Dec, G., Rząsa, W.: Modeling multilayer distributed web application with TCPN (Modelowanie wielowarstwowej rozproszonej aplikacji www z zastosowaniem TCPN). In: Trybus, L., Samolej, S. (eds.) Projektowanie, analiza i implementacja systemów czasu rzeczywistego, pp. 137–148. WKŁ, Warszawa (2011). (in Polish)Google Scholar
- 16.Somers, J.: Heroku’s Ugly Secret. http://genius.com/James-somers-herokus-ugly-secret-annotated
- 17.Heroku HTTP Routing. https://devcenter.heroku.com/articles/http-routing
- 18.Apdex specification. http://apdex.org/index.php/category/specification/
- 19.Apdex: Measuring user satisfaction. https://docs.newrelic.com/docs/apm/new-relic-apm/apdex/apdex-measuring-user-satisfaction
- 20.Routing Performance Update. https://blog.heroku.com/archives/2013/2/16/routing_performance_update