For decades, technology leaders have struggled to balance agility, reliability, and security. The consequences of failure have never been greater whether it's the healthcare.gov debacle, cardholder data breaches, or missing the boat with Big Data in the cloud.And yet, high performers using DevOps principles, such as Google, Amazon, Facebook, Etsy, and Netflix, are routinely and reliably deploying code into production hundreds, or even thousands, of times per day.Following in the footsteps of The Phoenix Project, The DevOps Handbook shows leaders how to replicate these incredible outcomes, by showing how to integrate Product Management, Development, QA, IT Operations, and Information Security to elevate your company and win in the marketplace."Table of contentsPrefaceSpreading the Aha! MomentIntroductionPART I: THE THREE WAYS1. Agile, continuous delivery and the three ways2. The First Way: The Principles of Flow3. The Second Way: The Principle of Feedback4. The Third Way: The Principles of Continual LearningPART II: WHERE TO START5. Selecting which value stream to start with6. Understanding the work in our value stream…7. How to design our organization and architecture8. How to get great outcomes by integrating operations into the daily work for developmentPART III: THE FIRST WAY: THE TECHNICAL PRACTICES OF FLOW9. Create the foundations of our deployment pipeline10. Enable fast and reliable automated testing11. Enable and practice continuous integration12. Automate and enable low-risk releases13. Architect for low-risk releasesPART IV: THE SECOND WAY: THE TECHNICAL PRACTICES OF FEEDBACK14*. Create telemetry to enable seeing abd solving problems15. Analyze telemetry to better anticipate problems16. Enable feedbackso development and operation can safely deploy code17. Integrate hypothesis-driven development and A/B testing into our daily work18. Create review and coordination processes to increase quality of our current workPART V: THE THRID WAY: THE TECHNICAL PRACTICES OF CONTINUAL LEARNING19. Enable and inject learning into daily work20. Convert local discoveries into global improvements21. Reserve time to create organizational learning22. Information security as everyone’s job, every day23. Protecting the deployment pipelinePART VI: CONCLUSIONA call to actionConclusion to the DevOps HandbookAPPENDICES1. The convergence of Devops2. The theory of constraints and core chronic conflicts3. Tabular form of downward spiral4. The dangers of handoffs and queues5. Myths of industrial safety6. The Toyota Andon Cord7. COTS Software8. Post-mortem meetings9. The Simian Army10. Transparent uptimeAdditional ResourcesEndnotes

    You’ll learn how parallelism exploits multicore processors to speed up computation-heavy programs, and how concurrency enables you to write programs with threads for multiple interactions.Author Simon Marlow walks you through the process with lots of code examples that you can run, experiment with, and extend. Divided into separate sections on Parallel and Concurrent Haskell, this book also includes exercises to help you become familiar with the concepts presented:Express parallelism in Haskell with the Eval monad and Evaluation StrategiesParallelize ordinary Haskell code with the Par monadBuild parallel array-based computations, using the Repa libraryUse the Accelerate library to run computations directly on the GPUWork with basic interfaces for writing concurrent codeBuild trees of threads for larger and more complex programsLearn how to build high-speed concurrent network serversWrite distributed programs that run on multiple machines in a network

    With jokes, puns, and a rigorous problem solving based approach. You can download all the code samples used in the book from here: http://www.robmiles.com/s/Yellow-Book...

    Many exercises are presented to help reinforce the lessons learned, and answers to the exercises are given in a new appendix.Most of the remaining chapters are dedicated to the reference material, which describes in detail the standard features of Scheme included in the Revised$^5$ Report on Scheme and the ANSI/IEEE standard for Scheme.Numerous examples are presented throughout the introductory and reference portions of the text, and a unique set of extended example programs and applications, with additional exercises, are presented in the final chapter. Reinforcing the book's utility as a reference text are appendices that present the formal syntax of Scheme, a summary of standard forms and procedures, and a bibliography of Scheme resources.The Scheme Programming Language stands alone as an introduction to and essential reference for Scheme programmers. it is also useful as a supplementary text for any course that uses Scheme.The Scheme Programming Language is illustrated by artist Jean-Pierre Hébert, who writes Scheme programs to extend his ability to create sophisticated works of digital art.R. Kent Dybvig is Professor of Computer Science at Indiana University and principal developer of Chez Scheme.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    This introduction is ideal for beginners: it requires no previous programming experience and all concepts are explained from first principles via carefully chosen examples. Each chapter includes exercises that range from the straightforward to extended projects, plus suggestions for further reading on more advanced topics. The author is a leading Haskell researcher and instructor, well-known for his teaching skills. The presentation is clear and simple, and benefits from having been refined and class-tested over several years. The result is a text that can be used with courses, or for self-learning. Features include freely accessible Powerpoint slides for each chapter, solutions to exercises and examination questions (with solutions) available to instructors, and a downloadable code that's fully compliant with the latest Haskell release.

    Understanding the design, implementation, and workings of Mac OS X requires examination of several technologies that differ in their age, origins, philosophies, and roles. Mac OS X Internals: A Systems Approach is the first book that dissects the internals of the system, presenting a detailed picture that grows incrementally as you read. For example, you will learn the roles of the firmware, the bootloader, the Mach and BSD kernel components (including the process, virtual memory, IPC, and file system layers), the object-oriented I/O Kit driver framework, user libraries, and other core pieces of software. You will learn how these pieces connect and work internally, where they originated, and how they evolved. The book also covers several key areas of the Intel-based Macintosh computers.A solid understanding of system internals is immensely useful in design, development, and debugging for programmers of various skill levels. System programmers can use the book as a reference and to construct a better picture of how the core system works. Application programmers can gain a deeper understanding of how their applications interact with the system. System administrators and power users can use the book to harness the power of the rich environment offered by Mac OS X. Finally, members of the Windows, Linux, BSD, and other Unix communities will find the book valuable in comparing and contrasting Mac OS X with their respective systems. Mac OS X Internals focuses on the technical aspects of OS X and is so full of extremely useful information and programming examples that it will definitely become a mandatory tool for every Mac OS X programmer.

    Monkey has been specifically designed for this book: it's a language that looks a lot like C, has first class functions, closures, strings, hashes and arrays and its only implementation is the one we build in the book.In contrast to text books on interpreters & compilers, the focus of this book is working code. Code is not just found in the appendix -- no, nearly every page contains a snippet! And not only that, but also tests. The code presented in the book is fully tested and the test suite is included.For more information, check out: http://interpreterbook.com/

    Every piece of the web application stack, from HTTP requests to browser-side scripts, comes with important yet subtle security consequences. To keep users safe, it is essential for developers to confidently navigate this landscape.In The Tangled Web, Michal Zalewski, one of the world's top browser security experts, offers a compelling narrative that explains exactly how browsers work and why they're fundamentally insecure. Rather than dispense simplistic advice on vulnerabilities, Zalewski examines the entire browser security model, revealing weak points and providing crucial information for shoring up web application security. You'll learn how to:Perform common but surprisingly complex tasks such as URL parsing and HTML sanitization Use modern security features like Strict Transport Security, Content Security Policy, and Cross-Origin Resource Sharing Leverage many variants of the same-origin policy to safely compartmentalize complex web applications and protect user credentials in case of XSS bugs Build mashups and embed gadgets without getting stung by the tricky frame navigation policy Embed or host user-supplied content without running into the trap of content sniffing For quick reference, "Security Engineering Cheat Sheets" at the end of each chapter offer ready solutions to problems you're most likely to encounter. With coverage extending as far as planned HTML5 features, The Tangled Web will help you create secure web applications that stand the test of time.

    As in the original book, Dive Into Python, each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end.This book includes:Example programs completely rewritten to illustrate powerful new concepts now available in Python 3: sets, iterators, generators, closures, comprehensions, and much more A detailed case study of porting a major library from Python 2 to Python 3 A comprehensive appendix of all the syntactic and semantic changes in Python 3 This is the perfect resource for you if you need to port applications to Python 3, or if you like to jump into languages fast and get going right away.

    

    And in a perfect world, those who produce the best code are the most successful. But in our perfectly messy world, success also depends on how you work with people to get your job done.In this highly entertaining book, Brian Fitzpatrick and Ben Collins-Sussman cover basic patterns and anti-patterns for working with other people, teams, and users while trying to develop software. It's valuable information from two respected software engineers whose popular video series, "Working with Poisonous People," has attracted hundreds of thousands of viewers.You'll learn how to deal with imperfect people--those irrational and unpredictable beings--in the course of your work. And you'll discover why playing well with others is at least as important as having great technical skills. By internalizing the techniques in this book, you'll get more software written, be more influential, be happier in your career.

    Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.

    It is also a practical, modern introduction to scientific computing in Python, tailored for data-intensive applications. This is a book about the parts of the Python language and libraries you'll need to effectively solve a broad set of data analysis problems. This book is not an exposition on analytical methods using Python as the implementation language.Written by Wes McKinney, the main author of the pandas library, this hands-on book is packed with practical cases studies. It's ideal for analysts new to Python and for Python programmers new to scientific computing.Use the IPython interactive shell as your primary development environmentLearn basic and advanced NumPy (Numerical Python) featuresGet started with data analysis tools in the pandas libraryUse high-performance tools to load, clean, transform, merge, and reshape dataCreate scatter plots and static or interactive visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsMeasure data by points in time, whether it's specific instances, fixed periods, or intervalsLearn how to solve problems in web analytics, social sciences, finance, and economics, through detailed examples

    Erlang is gaining widespread adoption with the advent of multi-core processors and their new scalable approach to concurrency. With this guide you'll learn how to write complex concurrent programs in Erlang, regardless of your programming background or experience. Written by leaders of the international Erlang community -- and based on their training material -- Erlang Programming focuses on the language's syntax and semantics, and explains pattern matching, proper lists, recursion, debugging, networking, and concurrency. This book helps you:Understand the strengths of Erlang and why its designers included specific features Learn the concepts behind concurrency and Erlang's way of handling it Write efficient Erlang programs while keeping code neat and readable Discover how Erlang fills the requirements for distributed systems Add simple graphical user interfaces with little effort Learn Erlang's tracing mechanisms for debugging concurrent and distributed systems Use the built-in Mnesia database and other table storage features Erlang Programming provides exercises at the end of each chapter and simple examples throughout the book.