sd0 cpu kps tps serv us sy wt id 25 3 6 19 3 0 78 32 4 7 13 4 0 83 28 2 7 20 3 0 77 18 2 8 24 2 0 74 29 3 9 18 5 0 77 33 4 12 23 3 0 74 35 4 8 25 5 0 70 25 4 10 32 4 0 64 26 3 11 28 4 0 68 34 4 12 22 6 0 72 11.
You are planning a load testing experiment of an e-commerce site. During the experiment, virtual users (i.e., programs that behave like real users and submit requests to the site) send requests to the site with an average think time of 5 seconds. How many virtual users you should have in the experiment to achieve a throughput of 20 requests/sec with an average response time of 2 seconds?
12.
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• Table of Contents
Performance by Design: Computer Capacity Planning by Example
By Daniel A. Menascé, Virgilio A.F. Almeida, Lawrence W. Dowdy
Publisher: Prentice Hall PTR Pub Date: January 05, 2004
ISBN: 0-13-090673-5 Pages: 552
Individual organizations and society as a whole could face major breakdowns if IT systems do not meet their Quality of Service (QoS) requirements on performance, availability, security, and maintainability. Corporations stand to lose valuable income, and public interests could be put at great risk. System designers and analysts usually do not take QoS requirements into account when designing and/or analyzing computer systems, due mainly to their lack of awareness about the issues that affect
performance and the lack of a framework to reason about performance. This book describes how to map real-life systems (e.g., databases, data centers, e-commerce applications) into analytic performance models. The authors elaborate upon these models, and use them to help the reader thoroughly analyze and better understand potential performance issues.
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Bibliography
[1] P. J. Denning and J. P. Buzen, "The Operational analysis of queueing network models," Computing
Surveys, vol. 10, No. 3, September 1978, pp. 225-261.
[2] J. C. Little, "A Proof of the queueing formula L = lW," Operations Research, vol. 9, 1961, pp. 383–387.
[3] R. R. Muntz and J. W. Wong, "Asymptotic properties of closed queuing network models," Proc. 8th
Princeton Conf. Information Sciences and Systems , 1974.
• Table of Contents
Performance by Design: Computer Capacity Planning by Example
By Daniel A. Menascé, Virgilio A.F. Almeida, Lawrence W. Dowdy
Publisher: Prentice Hall PTR Pub Date: January 05, 2004
ISBN: 0-13-090673-5 Pages: 552
Individual organizations and society as a whole could face major breakdowns if IT systems do not meet their Quality of Service (QoS) requirements on performance, availability, security, and maintainability. Corporations stand to lose valuable income, and public interests could be put at great risk. System designers and analysts usually do not take QoS requirements into account when designing and/or analyzing computer systems, due mainly to their lack of awareness about the issues that affect
performance and the lack of a framework to reason about performance. This book describes how to map real-life systems (e.g., databases, data centers, e-commerce applications) into analytic performance models. The authors elaborate upon these models, and use them to help the reader thoroughly analyze and better understand potential performance issues.
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Chapter 4. Performance Engineering
Methodology
Section 4.1. Introduction
Section 4.2. Performance Engineering Section 4.3. Motivating Example
Section 4.4. A Model-based Methodology Section 4.5. Workload Model
Section 4.6. Performance Models
Section 4.7. Specifying Performance Objectives Section 4.8. Concluding Remarks
Section 4.9. Exercises Bibliography
< Day Day Up >
• Table of Contents
Performance by Design: Computer Capacity Planning by Example
By Daniel A. Menascé, Virgilio A.F. Almeida, Lawrence W. Dowdy
Publisher: Prentice Hall PTR Pub Date: January 05, 2004
ISBN: 0-13-090673-5 Pages: 552
Individual organizations and society as a whole could face major breakdowns if IT systems do not meet their Quality of Service (QoS) requirements on performance, availability, security, and maintainability. Corporations stand to lose valuable income, and public interests could be put at great risk. System designers and analysts usually do not take QoS requirements into account when designing and/or analyzing computer systems, due mainly to their lack of awareness about the issues that affect
performance and the lack of a framework to reason about performance. This book describes how to map real-life systems (e.g., databases, data centers, e-commerce applications) into analytic performance models. The authors elaborate upon these models, and use them to help the reader thoroughly analyze and better understand potential performance issues.
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4.1 Introduction
Here is a central question: how can one plan, design, develop, deploy and operate IT services that meet the ever increasing demands for performance, availability, reliability, security, and cost? Or, being more specific, is a given IT system properly designed and sized for a given load condition? Can the insurance claims management system meet the performance requirement of subsecond response time? Is the infrastructure of a government agency scalable and can it cope with the new online security policies required for financial transactions? Can the security mechanisms be implemented without sacrificing user-perceived performance? Is the reservations system for cruise lines able to respond to the anticipated peak of consumer inquiries that occurs after a TV advertisement campaign?
By breaking down the complexity of an IT system, one can analyze the functionality of each component, evaluate service requirements, and design and operate systems that will meet user's expectations. In other words, the answer to the above questions requires a deep understanding of the system architecture and its infrastructure. This chapter presents the basic steps of a methodology for performance
engineering that are needed to fulfill the major performance needs of IT services.
• Table of Contents
Performance by Design: Computer Capacity Planning by Example
By Daniel A. Menascé, Virgilio A.F. Almeida, Lawrence W. Dowdy
Publisher: Prentice Hall PTR Pub Date: January 05, 2004
ISBN: 0-13-090673-5 Pages: 552
Individual organizations and society as a whole could face major breakdowns if IT systems do not meet their Quality of Service (QoS) requirements on performance, availability, security, and maintainability. Corporations stand to lose valuable income, and public interests could be put at great risk. System designers and analysts usually do not take QoS requirements into account when designing and/or analyzing computer systems, due mainly to their lack of awareness about the issues that affect
performance and the lack of a framework to reason about performance. This book describes how to map real-life systems (e.g., databases, data centers, e-commerce applications) into analytic performance models. The authors elaborate upon these models, and use them to help the reader thoroughly analyze and better understand potential performance issues.
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4.2 Performance Engineering
It has been a common practice in many systems projects to consider performance requirements only at the final stages of the software development process. As a consequence, many systems exhibit
performance failures that lead to delays and financial losses to companies and users [25]. Performance
engineering analyzes the expected performance characteristics of a system during the different phases of
its lifecycle. Performance engineering 1) develops practical strategies that help predict the level of performance a system can achieve and 2) provides recommendations to realize the optimal performance level. Both tasks rely on the following activities that form the basis of a methodology.
Understand the key factors that affect a system's performance. Measure the system and understand its workload.
Develop and validate a workload model that captures the key characteristics of the actual workload. Develop and validate an analytical model that accurately predicts the performance of the system. Use the models to predict and optimize the performance of the system.
Performance engineering can be viewed as a collection of methods for the support of the development of performance-oriented systems throughout the entire lifecycle [7]. The phases of the system lifecycle define the workflow, procedures, actions, and techniques that are used by analysts to produce and maintain IT systems. Figure 4.1 provides an overview of a performance-based methodology for system design and analysis. This methodology is based on models that are used to provide QoS assurances to IT systems. These models are: workload model, performance model, availability model, reliability model, and cost model. At the early stages of a project, the information and data available to develop the models are approximate at best.