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

Dynamic Content Online shopping News snippets Amazon, BestBuy News snippets http://news.google.com/ Current weather conditions Real-time stock tickers

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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 4.1.27 Database Server MySQL 4.1.0

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

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

Results: Response time control

Results: Throughput control

Results: Self-tuning

Results: Self-tuning

Results: Model Validation

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

Thank You!

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

Results: Throughput control - Pa