This is a short, occasionally funny, book on how to solve and avoid application and/or computer performance problems. I wrote it to give back the knowledge, insights, tips, and tricks I was given over the last 25 years of my computing career. It shows practical ways to use key performance laws and gives well tested advice on how (and when) to do performance monitoring, capacity planning, load testing, and performance modeling. It works for any application or collection of computers because it teaches you how to decipher whatever meters they give you and how to discover more about those meters than the documentation reveals. This book covers the things that will always be true no matter what technology you are using. It will continue to be useful 20 years from now when today's technology, if it runs at all, will look as quaint as a mechanical cuckoo clock. There is no complex math required; yet it allows you to easily use some fairly advanced techniques. Simple arithmetic, and a spreadsheet program, is all that is required of you. Lastly, it helps with the human side of performance. It shows you how to get the help you need and how to present your findings (good or bad) all the way up to the CIO level.

Practical, real-world solutions are given to potential problems covering the entire system life cycle. This book describes how to map real-life systems (databases, data centers, and e-commerce applications) into analytic performance models. The authors elaborate upon these models and use them to help the reader better understand performance issues.

The Complete Guide to Optimizing Systems Performance Written by the winner of the 2013 LISA Award for Outstanding Achievement in System Administration Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux(R) and Unix(R) performance, while illuminating performance issues that are relevant to all operating systems. You'll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). He systematically covers modern systems performance, including the "traditional" analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the "unknown unknowns" of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes - Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques - Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf - Kernel internals: uncovering what the OS is doing - Using system observability tools, interfaces, and frameworks - Understanding and monitoring application performance - Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling - Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators - File system I/O, including caching - Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O - Network-related performance issues: protocols, sockets, interfaces, and physical connections - Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing - Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg's extensive instructional experience.

How prepared are you to build fast and efficient web applications? This eloquent book provides what every web developer should know about the network, from fundamental limitations that affect performance to major innovations for building even more powerful browser applications—including HTTP 2.0 and XHR improvements, Server-Sent Events (SSE), WebSocket, and WebRTC. Author Ilya Grigorik, a web performance engineer at Google, demonstrates performance optimization best practices for TCP, UDP, and TLS protocols, and explains unique wireless and mobile network optimization requirements. You’ll then dive into performance characteristics of technologies such as HTTP 2.0, client-side network scripting with XHR, real-time streaming with SSE and WebSocket, and P2P communication with WebRTC. Deliver superlative TCP, UDP, and TLS performance Speed up network performance over 3G/4G mobile networks Develop fast and energy-efficient mobile applications Address bottlenecks in HTTP 1.x and other browser protocols Plan for and deliver the best HTTP 2.0 performance Enable efficient real-time streaming in the browser Create efficient peer-to-peer videoconferencing and low-latency applications with real-time WebRTC transports

Sets out the fundamental techniques used in analyzing and understanding the performance of computer systems.

Written with computer scientists and engineers in mind, this book brings queueing theory decisively back to computer science.

General-purpose graphics processing units (GPGPU) have emerged as an important class of shared memory parallel processing architectures, with widespread deployment in every computer class from high-end supercomputers to embedded mobile platforms. Relative to more traditional multicore systems of today, GPGPUs have distinctly higher degrees of hardware multithreading (hundreds of hardware thread contexts vs. tens), a return to wide vector units (several tens vs. 1-10), memory architectures that deliver higher peak memory bandwidth (hundreds of gigabytes per second vs. tens), and smaller caches/scratchpad memories (less than 1 megabyte vs. 1-10 megabytes). In this book, we provide a high-level overview of current GPGPU architectures and programming models. We review the principles that are used in previous shared memory parallel platforms, focusing on recent results in both the theory and practice of parallel algorithms, and suggest a connection to GPGPU platforms. We aim to provide hints to architects about understanding algorithm aspect to GPGPU. We also provide detailed performance analysis and guide optimizations from high-level algorithms to low-level instruction level optimizations. As a case study, we use n-body particle simulations known as the fast multipole method (FMM) as an example. We also briefly survey the state-of-the-art in GPU performance analysis tools and techniques.

As computers become more complex, the number and complexity of the tasks facing the computer architect have increased. Computer performance often depends in complex way on the design parameters and intuition that must be supplemented by performance studies to enhance design productivity. This book introduces computer architects to computer system performance models and shows how they are relatively simple, inexpensive to implement, and sufficiently accurate for most purposes. It discusses the development of performance models based on queuing theory and probability. The text also shows how they are used to provide quick approximate calculations to indicate basic performance tradeoffs and narrow the range of parameters to consider when determining system configurations. It illustrates how performance models can demonstrate how a memory system is to be configured, what the cache structure should be, and what incremental changes in cache size can have on the miss rate. A particularly deep knowledge of probability theory or any other mathematical field to understand the papers in this volume is not required.

A web application involves many specialists, but it takes people in web ops to ensure that everything works together throughout an application's lifetime. It's the expertise you need when your start-up gets an unexpected spike in web traffic, or when a new feature causes your mature application to fail. In this collection of essays and interviews, web veterans such as Theo Schlossnagle, Baron Schwartz, and Alistair Croll offer insights into this evolving field. You'll learn stories from the trenches--from builders of some of the biggest sites on the Web--on what's necessary to help a site thrive. Learn the skills needed in web operations, and why they're gained through experience rather than schooling Understand why it's important to gather metrics from both your application and infrastructure Consider common approaches to database architectures and the pitfalls that come with increasing scale Learn how to handle the human side of outages and degradations Find out how one company avoided disaster after a huge traffic deluge Discover what went wrong after a problem occurs, and how to prevent it from happening again Contributors include: John Allspaw Heather Champ Michael Christian Richard Cook Alistair Croll Patrick Debois Eric Florenzano Paul Hammond Justin Huff Adam Jacob Jacob Loomis Matt Massie Brian Moon Anoop Nagwani Sean Power Eric Ries Theo Schlossnagle Baron Schwartz Andrew Shafer

This book is written for computer engineers and scientists active in the development of software and hardware systems. It supplies the understanding and tools needed to effectively evaluate the performance of individual computer and communication systems. It covers the theoretical foundations of the field as