1. 1 Economical and Robust Provisioning of N-Tier Cloud Workloads: A Multi-level Control Approach Pengcheng Xiong 1, Zhikui Wang 2, Simon Malkowski 1, Qingyang Wang 1, Deepal Jayasinghe 1, Calton Pu 1 1 Georgia Institute of Technology 2 HP Labs Email: xiong@gatech.edu

2. Overview  Motivation  Background  Resource partition controller  Application controller  Conclusions 2

3. Overview  Motivation  Background  Resource partition controller  Application controller  Conclusions 3

4. Applications in a typical Cloud environment

5. Different feedback controller design for a single/multi-tiered application (1) 5 Zhu et al, ACC 2006

6. Different feedback controller design for a single/multi-tiered application (2) 6 Wang et al, FeBID 2007 T UC T FB T FF

7. Different controllability under different workload generator (1) 7 Schroeder et al, NSDI 2006

8. Different controllability under different workload generator (2) 8 Xiong et al, NOMS 2010

9. Goals  Economical –We want to meet the performance requirement for the N-tier web application with the minimum total resources.  Robust –We want to be robust to different time-varying workload types, e.g., open, closed, semi-open. 9

10. Overview  Motivation  Background  Resource partition controller  Application controller  Conclusions 10

11. Control Architecture 11

12. Test bed  Experiment Environment –Apache, Tomcat, Mysql –Xen hypervisor  Workload Generator –RUBiS “Browsing mix” workload that has 10 transaction types, e.g., Home, Browse, ViewItem. (just like eBay) –Workload types (open, closed, semi-open) –Workload intensity 12

13. Overview  Motivation  Background  Resource partition controller  Application controller  Conclusions 13

14. System modeling 14

15. Optimal resource partition  Solution 1(Shares)  Solution 2(Util.)  Our solution(Opt.)

16. Evaluation of resource partition controller 16

17. Overview  Motivation  Background  Resource partition controller  Application controller  Conclusions 17

18. Application controller design 18  System model between the RTT and S –System identification method based on ARMA model  Controller design –Root-locus method based on control theory

19. System identification 19

20. Controller design 20  ARX01 model  Proportional-integral (PI) controller  The closed model transfer function

21. Performance controller(setting=35ms) 21 Util has MORE fluctuation than Opt.

22. Performance controller(setting=200ms) 22

23. Conclusions  We propose economical and robust provisioning for Cloud resources for N-tier web applications through a multi-level control approach.  Experimental results show that our solution outperforms other existing approaches –Almost the same performance but save up to 20% CPU resources. –Robust to deal with different workload styles. 23

24. 24 Thanks