Poorly performing enterprise applications are the weakest links in a corporation's management chain, causing delays and disruptions of critical business functions. This groundbreaking book frames enterprise application performance engineering not as an art but as applied science built on model-based methodological foundation. The book introduces queuing models of enterprise application that visualize, demystify, explain, and solve system performance issues. Analysis of these models will help to discover and clarify unapparent connections and correlations among workloads, hardware architecture, and software parameters.
Solving Enterprise Applications Performance Puzzles
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Book Description
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Editorial Reviews
Review
Solving Enterprise Applications Performance Puzzles : Queuing Models to the Rescue by Leonid Grinshpan is a pretty interesting book about application of queuing models to solving enterprise performance and I believe the book fills a few gaps in practical application of queuing theory. Another good name for this book could be “Building queuing models by example”.
I spent a lot of time trying to use queuing models to solve practical performance issues and would testify that it is pretty challenging. There are a few areas where it was developed a little further (for example, around capacity planning of existing systems), but if you trying to do something else – you won’t find much help. You have a lot of books about systems performance, you have a lot of books about queuing theory with simple examples, but not much in between to solve practical tasks. And here Leonid’s book may help, especially if you are new in this area.
Chapter 1, Queuing Networks as Applications Models, is an introduction into the topic. It discusses how queuing theory may be used to model enterprise applications. A lot of analogues are used to introduce the subject.
Chapter 2, Building and Solving Application Models, is an overview of the whole process, including short discussions about essentials of queuing theory and using of tools to solve models.
Chapter 3, Workload Characterization and Transaction Profiling, discusses what input data for models are and how to gather them.
Chapter 4, Servers, CPUs, and Other Building Blocks of Application Scalability, discusses scalability, bottlenecks, how to identify bottlenecks and ways to fix them (mostly on CPU and I/O examples).
Chapter 5, Operating System Overheads, discusses main components of operating systems, where overheads come from, how to measure them, and their impact on transaction time.
Chapter 6, Software Bottlenecks, is devoted to software bottlenecks, which are rarely discussed in application to queuing models – while in practice software bottlenecks happen all the time. Memory bottlenecks and thread optimizations and their modeling are discussed in details. Multiple other software bottlenecks are also reviewed.
Chapter 7, Performance and Capacity of Virtual Systems, is an overview of performance issues related to virtualization , their explanation with queuing theory, and a methodology of virtual machine sizing.
Chapter 8, Model-Based Application Sizing: Say Good-Bye to guessing, explains why to use model-based sizing and discusses it step-by-step from gathering input data to model deliverables and what-if scenarios.
Chapter 9, Modeling Different Application Configurations, discusses several specials cases including geographical distribution of users, cross-platform modeling, remote terminal services, load balancing, and parallelization of transactions.
The book covers a lot of topics. However, to avoid disappointments, I’d like to point out what this book is not:
- It is not a textbook about queuing theory. The section 2.2 Essentials of Queuing Networks Theory has 5 pages in it.
- It is not a book about tools to solve queuing models. Available tools are listed and there are references, but they are just mentioned as a way to solve models (with one tool used as an illustration of the process). You don’t need to know any tool to read the book (but you will need one when you try to solve your own models).
- It is not a comprehensive book about enterprise application performance. There is plenty of important information and practical recommendations about enterprise application performance in the book, but it is shared as needed to build models and analyze their results.
So the book is exactly what the title says: a practical book about building queuing models to investigate enterprise applications performance issues.
- Alexander Podelko, Oracle
From the Back Cover
A groundbreaking scientific approach to solving enterprise applications performance problems
Enterprise applications are the information backbone of today's corporations, supporting vital business functions such as operational management, supply chain maintenance, customer relationship administration, business intelligence, accounting, procurement logistics, and more. Acceptable performance of enterprise applications is critical for a company's day-to-day operations as well as for its profitability.
Unfortunately, troubleshooting poorly performing enterprise applications has traditionally relied upon a trial-and-error series of actions rather than a systematic, scientific methodology.
Written by the Consulting Technical Director of Oracle Corporation, one of the largest enterprise software providers in the world, this groundbreaking book frames enterprise applications performance engineering as an applied science built on a model-based foundation. Readers will discover how queuing models of enterprise applications can be used to visualize, demystify, explain, and help to solve the performance issues of many applications. The author demonstrates how these queuing models help discover the critical connections among users' workloads, hardware architecture, and software parameters.
Without resorting to complex mathematics, Solving Enterprise Applications Performance Puzzles covers such important topics as:
Queuing networks as application models
Building and solving application models
User's workload characterization
Servers, CPUs, and other building blocks of application scalability
Software bottlenecks
Performance and capacity of virtual systems
Model-based application sizing
Throughout the book, readers will find tables and charts summarizing and visualizing important data. In addition, readers will find plenty of illustrations to help them better understand the core drivers of application performance.
Solving Enterprise Applications Performance Puzzles offers performance engineers, programmers, and systems analysts a new perspective on why enterprise applications can underperform and fail to support businesses. It puts forward a scientific approach for discovering the underlying problems and correcting them.
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Most Helpful Customer Reviews
2 of 3 people found the following review helpful
By Jeff Buzen
Format:Paperback
Complex multi-user applications play a critical role in today's world. This book provides a very useful starting point for anyone interested in analyzing the performance of such software applications and the hardware systems that host them.
In many cases, the first step is to identify the key factors that shape overall performance and develop a queuing model that reflects the way these factors interact. This can be a daunting task, and it's not always clear how to begin. The book focuses on this very important issue. The author's extensive experience with real world industrial-strength applications is evident in the examples he utilizes to illustrate his main points.
For practitioners such as the author, the mathematical details of model solution and evaluation are less important since they are incorporated into readily available software packages (both open source and commercial). The author does include a brief survey of some mathematical results from queuing theory, but this is neither the main focus nor the strongest part of this book.
In many cases, the first step is to identify the key factors that shape overall performance and develop a queuing model that reflects the way these factors interact. This can be a daunting task, and it's not always clear how to begin. The book focuses on this very important issue. The author's extensive experience with real world industrial-strength applications is evident in the examples he utilizes to illustrate his main points.
For practitioners such as the author, the mathematical details of model solution and evaluation are less important since they are incorporated into readily available software packages (both open source and commercial). The author does include a brief survey of some mathematical results from queuing theory, but this is neither the main focus nor the strongest part of this book.
1 of 2 people found the following review helpful
5.0 out of 5 stars
Successful book on predicting application performance using models: performance engineering is not an art!
May 22, 2012
By michael kok
Format:Kindle Edition|Amazon Verified Purchase
Summary
This unique book is a complement to the existing literature on performance modeling. The focus of this book is on applying performance models rather than their construction. The book addresses model centric methodology for application performance engineering through several practical examples. The overall application performance itself is analyzed. The book is especially interesting for IT professionals who seek an introduction on the subject of performance modeling.
In the past few years I have provided an introduction in applying performance modeling with the mBrace method to a few dozen professionals. Often the trainees asked for more background without "the mathematics" . This is the book that fulfills that need. I am enthusiastic about this book and will include it in our introductory course.
Review
The request for this review came via the NLCMG, the Dutch chapter of the Computer Measurement Group. As a practitioner, here is my opinion of this book:
Everyone may not agree, but as far as I am concerned you cannot do without models in application performance engineering. Performance models enable us to understand an application's performance and to predict it under varying conditions. They are the tools for interpreting performance data to obtain a good overall view on the performance of an application. In many books on this subject, the focus is on the construction and internal components of models. Dr. Leonid Grinshpan focuses on applying them which makes this a lot more accessible for many performance practitioners.
The author's goal is to teach his methodology for model centric application performance engineering. The main focus of the method is to control the performance of an application in all phases of its lifecycle.
In the preface, the author quickly does away with the idea of performance engineering being an art. His method eliminates the guesswork and trial and error for solving performance problems. Moreover he promises the reader there will be minimal model internals or mathematics.
The author uses many simple but important examples: applications with only a few transaction types and two or three servers in the infrastructure chain. These examples are adequate in order to develop a thorough understanding yet, the book remains accessible to readers.
Some highlights
This book neatly builds step by step the required framework of knowledge. It takes transaction response time (the author prefers the term "transaction time") and resource utilization as central metrics.
The reader can experiment with the method. The instrumentation used is accessible for free: a toolset for modeling, Java Modeling Tools (JMT), released as open source software by the Politecnico di Milano. It is used in many examples. Moreover Perfmon for Windows and prstat for UNIX for creating transaction profiles.
Knowledge of the components of models, such as queuing theory is desirable but not necessary for applying performance models. There is a small section on introductory queuing theory for the reader who is interested in the subject. The reader who is not interested can skip it without losing the core of the book.
Some important subjects treated
-Mapping system architecture into a model. This is demonstrated step by step per resource type: CPU, memory, disks, and network.
-Workload categorization and transaction profiling. Workload categorization: determination of the workload of an application in terms of numbers of users, their think times and transaction frequencies. Transaction profiling: practical hints for determining the resource usage of the application (service demands) with the help of standard available loggings. Practical examples show how a model can be set up with this data.
-Several scenarios with performance models such as application sizing are extensively treated
-The treatment of software resources is one very strong point of the book. Software resources are a source of many performance problems that aren't fully understood. Without performance models, it is very difficult to show their performance impact and gain an understanding of them. The book provides a useful introduction.
This unique book is a complement to the existing literature on performance modeling. The focus of this book is on applying performance models rather than their construction. The book addresses model centric methodology for application performance engineering through several practical examples. The overall application performance itself is analyzed. The book is especially interesting for IT professionals who seek an introduction on the subject of performance modeling.
In the past few years I have provided an introduction in applying performance modeling with the mBrace method to a few dozen professionals. Often the trainees asked for more background without "the mathematics" . This is the book that fulfills that need. I am enthusiastic about this book and will include it in our introductory course.
Review
The request for this review came via the NLCMG, the Dutch chapter of the Computer Measurement Group. As a practitioner, here is my opinion of this book:
Everyone may not agree, but as far as I am concerned you cannot do without models in application performance engineering. Performance models enable us to understand an application's performance and to predict it under varying conditions. They are the tools for interpreting performance data to obtain a good overall view on the performance of an application. In many books on this subject, the focus is on the construction and internal components of models. Dr. Leonid Grinshpan focuses on applying them which makes this a lot more accessible for many performance practitioners.
The author's goal is to teach his methodology for model centric application performance engineering. The main focus of the method is to control the performance of an application in all phases of its lifecycle.
In the preface, the author quickly does away with the idea of performance engineering being an art. His method eliminates the guesswork and trial and error for solving performance problems. Moreover he promises the reader there will be minimal model internals or mathematics.
The author uses many simple but important examples: applications with only a few transaction types and two or three servers in the infrastructure chain. These examples are adequate in order to develop a thorough understanding yet, the book remains accessible to readers.
Some highlights
This book neatly builds step by step the required framework of knowledge. It takes transaction response time (the author prefers the term "transaction time") and resource utilization as central metrics.
The reader can experiment with the method. The instrumentation used is accessible for free: a toolset for modeling, Java Modeling Tools (JMT), released as open source software by the Politecnico di Milano. It is used in many examples. Moreover Perfmon for Windows and prstat for UNIX for creating transaction profiles.
Knowledge of the components of models, such as queuing theory is desirable but not necessary for applying performance models. There is a small section on introductory queuing theory for the reader who is interested in the subject. The reader who is not interested can skip it without losing the core of the book.
Some important subjects treated
-Mapping system architecture into a model. This is demonstrated step by step per resource type: CPU, memory, disks, and network.
-Workload categorization and transaction profiling. Workload categorization: determination of the workload of an application in terms of numbers of users, their think times and transaction frequencies. Transaction profiling: practical hints for determining the resource usage of the application (service demands) with the help of standard available loggings. Practical examples show how a model can be set up with this data.
-Several scenarios with performance models such as application sizing are extensively treated
-The treatment of software resources is one very strong point of the book. Software resources are a source of many performance problems that aren't fully understood. Without performance models, it is very difficult to show their performance impact and gain an understanding of them. The book provides a useful introduction.
1 of 2 people found the following review helpful
5.0 out of 5 stars
Solving Enterprise Applications Performance Puzzles : Queuing Models to the Rescue
March 12, 2012
Format:Paperback
It is a pretty interesting book about application of queuing models to solving enterprise performance and I believe the book fills a few gaps in practical application of queuing theory. Another good name for this book could be "Building queuing models by example".
I spent a lot of time trying to use queuing models to solve practical performance issues and would testify that it is pretty challenging. There are a few areas where it was developed a little further (for example, around capacity planning of existing systems), but if you trying to do something else - you won't find much help. You have a lot of books about systems performance, you have a lot of books about queuing theory with simple examples, but not much in between to solve practical tasks. And here Leonid's book may help, especially if you are new in this area.
Chapter 1, Queuing Networks as Applications Models, is an introduction into the topic. It discusses how queuing theory may be used to model enterprise applications. A lot of analogues are used to introduce the subject.
Chapter 2, Building and Solving Application Models, is an overview of the whole process, including short discussions about essentials of queuing theory and using of tools to solve models.
Chapter 3, Workload Characterization and Transaction Profiling, discusses what input data for models are and how to gather them.
Chapter 4, Servers, CPUs, and Other Building Blocks of Application Scalability, discusses scalability, bottlenecks, how to identify bottlenecks and ways to fix them (mostly on CPU and I/O examples).
Chapter 5, Operating System Overheads, discusses main components of operating systems, where overheads come from, how to measure them, and their impact on transaction time.
Chapter 6, Software Bottlenecks, is devoted to software bottlenecks, which are rarely discussed in application to queuing models - while in practice software bottlenecks happen all the time. Memory bottlenecks and thread optimizations and their modeling are discussed in details. Multiple other software bottlenecks are also reviewed.
Chapter 7, Performance and Capacity of Virtual Systems, is an overview of performance issues related to virtualization , their explanation with queuing theory, and a methodology of virtual machine sizing.
Chapter 8, Model-Based Application Sizing: Say Good-Bye to guessing, explains why to use model-based sizing and discusses it step-by-step from gathering input data to model deliverables and what-if scenarios.
Chapter 9, Modeling Different Application Configurations, discusses several specials cases including geographical distribution of users, cross-platform modeling, remote terminal services, load balancing, and parallelization of transactions.
The book covers a lot of topics. However, to avoid disappointments, I'd like to point out what this book is not:
- It is not a textbook about queuing theory. The section 2.2 Essentials of Queuing Networks Theory has 5 pages in it.
- It is not a book about tools to solve queuing models. Available tools are listed and there are references, but they are just mentioned as a way to solve models (with one tool used as an illustration of the process). You don't need to know any tool to read the book (but you will need one when you try to solve your own models).
- It is not a comprehensive book about enterprise application performance. There is plenty of important information and practical recommendations about enterprise application performance in the book, but it is shared as needed to build models and analyze their results.
So the book is exactly what the title says: a practical book about building queuing models to investigate enterprise applications performance issues.
I spent a lot of time trying to use queuing models to solve practical performance issues and would testify that it is pretty challenging. There are a few areas where it was developed a little further (for example, around capacity planning of existing systems), but if you trying to do something else - you won't find much help. You have a lot of books about systems performance, you have a lot of books about queuing theory with simple examples, but not much in between to solve practical tasks. And here Leonid's book may help, especially if you are new in this area.
Chapter 1, Queuing Networks as Applications Models, is an introduction into the topic. It discusses how queuing theory may be used to model enterprise applications. A lot of analogues are used to introduce the subject.
Chapter 2, Building and Solving Application Models, is an overview of the whole process, including short discussions about essentials of queuing theory and using of tools to solve models.
Chapter 3, Workload Characterization and Transaction Profiling, discusses what input data for models are and how to gather them.
Chapter 4, Servers, CPUs, and Other Building Blocks of Application Scalability, discusses scalability, bottlenecks, how to identify bottlenecks and ways to fix them (mostly on CPU and I/O examples).
Chapter 5, Operating System Overheads, discusses main components of operating systems, where overheads come from, how to measure them, and their impact on transaction time.
Chapter 6, Software Bottlenecks, is devoted to software bottlenecks, which are rarely discussed in application to queuing models - while in practice software bottlenecks happen all the time. Memory bottlenecks and thread optimizations and their modeling are discussed in details. Multiple other software bottlenecks are also reviewed.
Chapter 7, Performance and Capacity of Virtual Systems, is an overview of performance issues related to virtualization , their explanation with queuing theory, and a methodology of virtual machine sizing.
Chapter 8, Model-Based Application Sizing: Say Good-Bye to guessing, explains why to use model-based sizing and discusses it step-by-step from gathering input data to model deliverables and what-if scenarios.
Chapter 9, Modeling Different Application Configurations, discusses several specials cases including geographical distribution of users, cross-platform modeling, remote terminal services, load balancing, and parallelization of transactions.
The book covers a lot of topics. However, to avoid disappointments, I'd like to point out what this book is not:
- It is not a textbook about queuing theory. The section 2.2 Essentials of Queuing Networks Theory has 5 pages in it.
- It is not a book about tools to solve queuing models. Available tools are listed and there are references, but they are just mentioned as a way to solve models (with one tool used as an illustration of the process). You don't need to know any tool to read the book (but you will need one when you try to solve your own models).
- It is not a comprehensive book about enterprise application performance. There is plenty of important information and practical recommendations about enterprise application performance in the book, but it is shared as needed to build models and analyze their results.
So the book is exactly what the title says: a practical book about building queuing models to investigate enterprise applications performance issues.
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