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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
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Dynamic Content Online shopping Amazon, BestBuy News snippets http://news.google.com/ Current weather conditions Real-time stock tickers
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Dynamic Content Generation 3-Tier Structure: Web Server: Static web pages App Server: CGI / Java servlets Database Server: Backend Data Store http Database Server Web Server App Server
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Major Problems Overloaded Web Sites: The “Slashdot Effect” Unanticipated load causes site to crash Unresponsive Web Sites: The “Abandoned Shopping Cart’’ Unacceptable delays lead to reduced usage
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Admission Control 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 Load Throughput Actual Ideal
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Why Self-Tuning ? Parameter Setting Lots of experimentation Workload characterization Re-done for every system change
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Outline Motivation & Background The ‘Yaksha’ Controller Architecture Modeling Design Self-Tuning Experimental Environment Experimental Results Summary and Conclusions
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The ‘Yaksha’ Controller Architecture 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 http Database Server Web Server App Server Yaksha Clients
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Reference Input = Desired Response/Sojourn times = Incoming job acceptance probability Modeling Web Server Controller + –
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Modeling System Abstraction M/GI/1 Processor Sharing Queue Linearization approximation Open loop transfer function
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Proportional Integral (PI) Control Zero steady state error Closed loop transfer function Design
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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
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Self-Tuning ‘Pure gain’ open loop transfer function Effective arrival rate ‘Tuned’ transfer function Running average for p a
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Parameter Setting Parameters w/o Self-Tuning Expected input rate Expected connection drop rate Target response time Parameters with Self-Tuning Target response time
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Outline Motivation & Background The ‘Yaksha’ Controller Experimental Environment Setup & Methodology Software & Hardware Experimental Results Summary and Conclusions
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Experimental Setup Workload Generator SQL Database ServerWeb/App Server Lightweight Proxy Controller
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http TomcatMySQL SQL Emulated Clients Emulated Clients Remote Browser Emulator Session duration Think time Markov model Load is a function of the number of clients
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Software Workload GeneratorTPC-W 1.0.1 Lightweight ProxyTinyproxy 1.6.1 Web/App ServerTomcat 4.1.27 Database ServerMySQL 4.1.0 Workload Generator SQL Database ServerWeb/App Server Lightweight Proxy Controller
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Hardware CPUIntel Pentium 1.7 GHz Memory512 MB Disk12 GB, 12 ms, 5400 RPM Network100 Mbps Ethernet http Tinyproxy/ Tomcat MySQL SQL TPC-W Client
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Outline Motivation & Background The ‘Yaksha’ Controller Experimental Environment Experimental Results Response time control Throughput control Self-tuning Model validation Summary and Conclusions
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Results: Response time control
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Results: Throughput control
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Results: Self-tuning
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Results: Model Validation
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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
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Thank You!
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Related Work Admission Control for Static Content Web Servers: 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
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Results: Throughput control - P a
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