1. Abhinav Kamra, Vishal Misra CS Department Columbia University
Yaksha: A Self-Tuning Controller for Managing the Performance of 3-Tiered Web Sites
Abhinav Kamra, Vishal Misra
CS Department
Columbia University
Erich Nahum
IBM TJ Watson
Research Center

2. Dynamic Content Online shopping News snippets
Amazon, BestBuy
News snippets
Current weather conditions
Real-time stock tickers

3. Dynamic Content Generation
Web
Server
App Server
Database
Server
http
3-Tier Structure:
Web Server: Static web pages
App Server: CGI / Java servlets
Database Server: Backend Data Store

4. Major Problems Overloaded Web Sites: Unresponsive Web Sites:
The “Slashdot Effect”
Unanticipated load causes site to crash
Unresponsive Web Sites:
The “Abandoned Shopping Cart’’
Unacceptable delays lead to reduced usage

5. Admission Control To prevent overload, perform admission control:
Throughput
Actual
Ideal
To prevent overload, perform admission control:
Notion of capacity in the system
Identify the job ahead of time & amount of work generated
Only let jobs in if they won’t overload system
Once you reach full capacity:
Make jobs wait
Drop jobs

6. Why Self-Tuning ? Parameter Setting Re-done for every system change
Lots of experimentation
Workload characterization
Re-done for every system change

7. Outline Motivation & Background The ‘Yaksha’ Controller
Architecture
Modeling
Design
Self-Tuning
Experimental Environment
Experimental Results
Summary and Conclusions

8. The ‘Yaksha’ Controller Architecture
Web
Server
App
Server
Database
Server
Clients
http
Intercepts HTTP requests
Decides whether to accept or reject new connections
Maintains several measurement-based estimates:
Per connection Response and Sojourn times
Per customer-class based estimates
Per query-type based estimates

9. Modeling Reference Input S = Desired Response/Sojourn times+ S
Controller
Web Server –
Reference Input
= Desired Response/Sojourn times
= Incoming job acceptance probability

10. Modeling System Abstraction Open loop transfer function
M/GI/1 Processor Sharing Queue
Linearization approximation
Open loop transfer function

11. Design Proportional Integral (PI) Control
Zero steady state error
Closed loop transfer function

12. Design (contd.) Setting system parameters
Fix controller time constant to 10 sec
Fix phase margin at 45 degrees
Bilinear transform to convert to digital form

13. Self-Tuning ‘Pure gain’ open loop transfer function
Effective arrival rate
‘Tuned’ transfer function
Running average for pa

14. Parameter Setting Parameters w/o Self-Tuning
Expected input rate
Expected connection drop rate
Target response time
Parameters with Self-Tuning

15. Motivation & Background The ‘Yaksha’ Controller
Outline
Motivation & Background
The ‘Yaksha’ Controller
Experimental Environment
Setup & Methodology
Software & Hardware
Experimental Results
Summary and Conclusions

16. Experimental Setup Database Server Web/App Server Lightweight Proxy
Workload Generator
SQL
Database Server
Web/App Server
Lightweight Proxy
Controller

17. Emulated Clients Emulated Clients Tomcat MySQL http SQL
Remote Browser Emulator
Session duration
Think time
Markov model
Load is a function of the number of clients

18. Software Workload Generator TPC-W 1.0.1 Lightweight Proxy
SQL
Database Server
Web/App Server
Lightweight Proxy
Controller
Workload Generator
TPC-W 1.0.1
Lightweight Proxy
Tinyproxy 1.6.1
Web/App Server
Tomcat
Database Server
MySQL 4.1.0

19. Hardware http SQL TPC-W Client Tinyproxy/ Tomcat MySQL CPU
Intel Pentium 1.7 GHz
Memory
512 MB
Disk
12 GB, 12 ms, 5400 RPM
Network
100 Mbps Ethernet

20. Outline Motivation & Background The ‘Yaksha’ Controller
Experimental Environment
Experimental Results
Response time control
Throughput control
Self-tuning
Model validation
Summary and Conclusions

21. Results: Response time control

22. Results: Throughput control

23. Results: Self-tuning

24. Results: Self-tuning

25. Results: Model Validation

26. Summary & Future Work Presented the ‘Yaksha’ Control System
PI admission control for http connections
Overload prevention
Response time bounds
Self-Tuning Control
Future Work
Throughput maximization

27. Thank You!

28. Related Work Admission Control for Static Content Web Servers: Control
Bhatti99, Li00, Voigt01, Pradhan02
Provide throughput/response time/BW guarantees
Control
Tarek01, Tarek02, Hellerstein01, Hellerstein02, Welsh03
Control theory for resource management
Admission control for Apache, Lotus notes
Dynamic Content:
Dynaserver project at Rice
TPC-W Benchmarks

29. Results: Throughput control - Pa