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 schoolingUnderstand why it's important to gather metrics from both your application and infrastructureConsider common approaches to database architectures and the pitfalls that come with increasing scaleLearn how to handle the human side of outages and degradationsFind out how one company avoided disaster after a huge traffic delugeDiscover what went wrong after a problem occurs, and how to prevent it from happening againContributors include:John AllspawHeather ChampMichael ChristianRichard CookAlistair CrollPatrick DeboisEric FlorenzanoPaul HammondJustin HuffAdam JacobJacob LoomisMatt MassieBrian MoonAnoop NagwaniSean PowerEric RiesTheo SchlossnagleBaron SchwartzAndrew Shafer

    The blades start moving in 60 seconds. What do you do? If you want to work at Google, or any of America's best companies, you need to have an answer to this and other puzzling questions. Are You Smart Enough to Work at Google? guides readers through the surprising solutions to dozens of the most challenging interview questions. The book covers the importance of creative thinking, ways to get a leg up on the competition, what your Facebook page says about you, and much more. Are You Smart Enough to Work at Google? is a must-read for anyone who wants to succeed in today's job market.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    It examines Stallman's unique personality and how that personality has been at turns a driving force and a drawback in terms of the movement's overall success.Free as in Freedom examines one man's 20-year attempt to codify and communicate the ethics of 1970s era "hacking" culture in such a way that later generations might easily share and build upon the knowledge of their computing forebears. The book documents Stallman's personal evolution from teenage misfit to prescient adult hacker to political leader and examines how that evolution has shaped the free software movement. Like Alan Greenspan in the financial sector, Richard Stallman has assumed the role of tribal elder within the hacking community, a community that bills itself as anarchic and averse to central leadership or authority. How did this paradox come about? Free as in Freedom provides an answer. It also looks at how the latest twists and turns in the software marketplace have diminished Stallman's leadership role in some areas while augmenting it in others.Finally, Free as in Freedom examines both Stallman and the free software movement from historical viewpoint. Will future generations see Stallman as a genius or crackpot? The answer to that question depends partly on which side of the free software debate the reader currently stands and partly upon the reader's own outlook for the future. 100 years from now, when terms such as "computer," "operating system" and perhaps even "software" itself seem hopelessly quaint, will Richard Stallman's particular vision of freedom still resonate, or will it have taken its place alongside other utopian concepts on the 'ash-heap of history?'

    Simultaneously becoming more user friendly and more powerful as a back-end system, Linux has achieved new plateaus: the newer filesystems have solidified, new commands and tools have appeared and become standard, and the desktop--including new desktop environments--have proved to be viable, stable, and readily accessible to even those who don't consider themselves computer gurus. Whether you're using Linux for personal software projects, for a small office or home office (often termed the SOHO environment), to provide services to a small group of colleagues, or to administer a site responsible for millions of email and web connections each day, you need quick access to information on a wide range of tools. This book covers all aspects of administering and making effective use of Linux systems. Among its topics are booting, package management, and revision control. But foremost in Linux in a Nutshell are the utilities and commands that make Linux one of the most powerful and flexible systems available.Now in its fifth edition, Linux in a Nutshell brings users up-to-date with the current state of Linux. Considered by many to be the most complete and authoritative command reference for Linux available, the book covers all substantial user, programming, administration, and networking commands for the most common Linux distributions.Comprehensive but concise, the fifth edition has been updated to cover new features of major Linux distributions. Configuration information for the rapidly growing commercial network services and community update services is one of the subjects covered for the first time.But that's just the beginning. The book covers editors, shells, and LILO and GRUB boot options. There's also coverage of Apache, Samba, Postfix, sendmail, CVS, Subversion, Emacs, vi, sed, gawk, and much more. Everything that system administrators, developers, and power users need to know about Linux is referenced here, and they will turn to this book again and again.

    "More concretely," the authors explain, "it is the controlled manipulation of mathematical formulas, using a collection of techniques for solving problems."

    It is truly cutting-edge. As the only book on the subject, Rootkits will be of interest to any Windows security researcher or security programmer. It's detailed, well researched and the technical information is excellent. The level of technical detail, research, and time invested in developing relevant examples is impressive. In one word: Outstanding."--Tony Bautts, Security Consultant; CEO, Xtivix, Inc. "This book is an essential read for anyone responsible for Windows security. Security professionals, Windows system administrators, and programmers in general will want to understand the techniques used by rootkit authors. At a time when many IT and security professionals are still worrying about the latest e-mail virus or how to get all of this month's security patches installed, Mr. Hoglund and Mr. Butler open your eyes to some of the most stealthy and significant threats to the Windows operating system. Only by understanding these offensive techniques can you properly defend the networks and systems for which you are responsible."--Jennifer Kolde, Security Consultant, Author, and Instructor "What's worse than being owned? Not knowing it. Find out what it means to be owned by reading Hoglund and Butler's first-of-a-kind book on rootkits. At the apex the malicious hacker toolset--which includes decompilers, disassemblers, fault-injection engines, kernel debuggers, payload collections, coverage tools, and flow analysis tools--is the rootkit. Beginning where Exploiting Software left off, this book shows how attackers hide in plain sight."Rootkits are extremely powerful and are the next wave of attack technology. Like other types of malicious code, rootkits thrive on stealthiness. They hide away from standard system observers, employing hooks, trampolines, and patches to get their work done. Sophisticated rootkits run in such a way that other programs that usually monitor machine behavior can't easily detect them. A rootkit thus provides insider access only to people who know that it is running and available to accept commands. Kernel rootkits can hide files and running processes to provide a backdoor into the target machine."Understanding the ultimate attacker's tool provides an important motivator for those of us trying to defend systems. No authors are better suited to give you a detailed hands-on understanding of rootkits than Hoglund and Butler. Better to own this book than to be owned."--Gary McGraw, Ph.D., CTO, Cigital, coauthor of Exploiting Software (2004) and Building Secure Software (2002), both from Addison-Wesley "Greg and Jamie are unquestionably the go-to experts when it comes to subverting the Windows API and creating rootkits. These two masters come together to pierce the veil of mystery surrounding rootkits, bringing this information out of the shadows. Anyone even remotely interested in security for Windows systems, including forensic analysis, should include this book very high on their must-read list."--Harlan Carvey, author of Windows Forensics and Incident Recovery (Addison-Wesley, 2005) Rootkits are the ultimate backdoor, giving hackers ongoing and virtually undetectable access to the systems they exploit. Now, two of the world's leading experts have written the first comprehensive guide to rootkits: what they are, how they work, how to build them, and how to detect them. Rootkit.com's Greg Hoglund and James Butler created and teach Black Hat's legendary course in rootkits. In this book, they reveal never-before-told offensive aspects of rootkit technology--learn how attackers can get in and stay in for years, without detection. Hoglund and Butler show exactly how to subvert the Windows XP and Windows 2000 kernels, teaching concepts that are easily applied to virtually any modern operating system, from Windows Server 2003 to Linux and UNIX. They teach rootkit programming techniques that can be used for a wide range of software, from white hat security tools to operating system drivers and debuggers. After reading this book, readers will be able to Understand the role of rootkits in remote command/control and software eavesdropping Build kernel rootkits that can make processes, files, and directories invisible Master key rootkit programming techniques, including hooking, runtime patching, and directly manipulating kernel objects Work with layered drivers to implement keyboard sniffers and file filters Detect rootkits and build host-based intrusion prevention software that resists rootkit attacks

    If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions. With all the data available today, machine learning applications are limited only by your imagination.You'll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Muller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book.With this book, you'll learn:Fundamental concepts and applications of machine learningAdvantages and shortcomings of widely used machine learning algorithmsHow to represent data processed by machine learning, including which data aspects to focus onAdvanced methods for model evaluation and parameter tuningThe concept of pipelines for chaining models and encapsulating your workflowMethods for working with text data, including text-specific processing techniquesSuggestions for improving your machine learning and data science skills

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    Through four years of groundbreaking research, Dr. Nicole Forsgren, Jez Humble, and Gene Kim set out to find a way to measure software delivery performance—and what drives it—using rigorous statistical methods. This book presents both the findings and the science behind that research. Readers will discover how to measure the performance of their teams, and what capabilities they should invest in to drive higher performance.