本书致力于说明开发Nginx模块的必备知识，第1版发行以后，深受广大读者的喜爱．然而由于Ng,nx功能繁多且性能强大，以致必须了解的基本技能也很庞杂，而第1版成书匆忙，缺失了几个进阶的技巧描述，因此第2版在此基础上进行了完善。
书中首先通过介绍官方Nginx的基本用法和配置规则，帮助读者了解一般Nginx模块的用法，然后重点介绍了女口何开发HTTP模块(含HTTP过滤模块)来得到定制化的Nginx，其中包括开发—个功能复杂的模块所需要了解的各种知识，并对内存池的实现细节及TCP协议进行了详细介绍；接着，综合Nginx框架代码分析了Nginx架构的设计理念和技巧，此外，还新增了如何在模块中支持HTTP变量，以及与slab共享内存等相关的内容，相信通过完善，可进一步帮助读者更好地开发出功能丰富、性能—流的Nginx模块。

This textbook examines database systems from the viewpoint of a software developer. This perspective makes it possible to investigate why database systems are the way they are. It is of course important to be able to write queries, but it is equally important to know how they are processed. We e.g. don’t want to just use JDBC; we also want to know why the API contains the classes and methods that it does. We need a sense of how hard is it to write a disk cache or logging facility. And what exactly is a database driver, anyway?
The first two chapters provide a brief overview of database systems and their use. Chapter 1 discusses the purpose and features of a database system and introduces the Derby and SimpleDB systems. Chapter 2 explains how to write a database application using Java. It presents the basics of JDBC, which is the fundamental API for Java programs that interact with a database. In turn, Chapters 3-11 examine the internals of a typical database engine. Each chapter covers a different database component, starting with the lowest level of abstraction (the disk and file manager) and ending with the highest (the JDBC client interface); further, the respective chapter explains the main issues concerning the component, and considers possible design decisions. As a result, the reader can see exactly what services each component provides and how it interacts with the other components in the system. By the end of this part, s/he will have witnessed the gradual development of a simple but completely functional system. The remaining four chapters then focus on efficient query processing, and focus on the sophisticated techniques and algorithms that can replace the simple design choices described earlier. Topics include indexing, sorting, intelligent buffer usage, and query optimization.
This text is intended for upper-level undergraduate or beginning graduate courses in Computer Science. It assumes that the reader is comfortable with basic Java programming; advanced Java concepts (such as RMI and JDBC) are fully explained in the text. The respective chapters are complemented by “end-of-chapter readings” that discuss interesting ideas and research directions that went unmentioned in the text, and provide references to relevant web pages, research articles, reference manuals, and books. Conceptual and programming exercises are also included at the end of each chapter. Students can apply their conceptual knowledge by examining the SimpleDB (a simple but fully functional database system created by the author and provided online) code and modifying it.

With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up.
Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment.

In the pages that follow we will give you a solid background into the
challenges of microservices, explain what a service mesh is, describe
how a service mesh works, and explore the current service mesh
landscape. Starting with Chapter 2, we’ll use Istio as our main ser‐
vice mesh implementation to explain how to set up and use a service
mesh. We’ll describe the Istio architecture and explore Istio’s observ‐
ability, traffic management and security capabilities.
You don’t have to understand and consume all service mesh features
at once. You can instead adopt features incrementally and still enjoy
some of the benefits service mesh offers. To that end, we take an

本书主要介绍神经网络与深度学习中的基础知识、主要模型（卷积神经网络、递归神经网络等）以及在计算机视觉、自然语言处理等领域的应用。

Data sets in large applications are often too massive to fit completely inside the computer's internal memory. The resulting input/output communication (or I/O) between fast internal memory and slower external memory (such as disks) can be a major performance bottleneck. Algorithms and Data Structures for External Memory surveys the state of the art in the design and analysis of external memory (or EM) algorithms and data structures, where the goal is to exploit locality and parallelism in order to reduce the I/O costs. A variety of EM paradigms are considered for solving batched and online problems efficiently in external memory. Algorithms and Data Structures for External Memory describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, databases, geographic information systems, and text and string processing. Algorithms and Data Structures for External Memory is an invaluable reference for anybody interested in, or conducting research in the design, analysis, and implementation of algorithms and data structures.

Summary
GANs in Action teaches you how to build and train your own Generative Adversarial Networks, one of the most important innovations in deep learning. In this book, you'll learn how to start building your own simple adversarial system as you explore the foundation of GAN architecture: the generator and discriminator networks.
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
About the Technology
Generative Adversarial Networks, GANs, are an incredible AI technology capable of creating images, sound, and videos that are indistinguishable from the "real thing." By pitting two neural networks against each other—one to generate fakes and one to spot them—GANs rapidly learn to produce photo-realistic faces and other media objects. With the potential to produce stunningly realistic animations or shocking deepfakes, GANs are a huge step forward in deep learning systems.
About the Book
GANs in Action teaches you to build and train your own Generative Adversarial Networks. You'll start by creating simple generator and discriminator networks that are the foundation of GAN architecture. Then, following numerous hands-on examples, you'll train GANs to generate high-resolution images, image-to-image translation, and targeted data generation. Along the way, you'll find pro tips for making your system smart, effective, and fast.
What's inside
Building your first GAN
Handling the progressive growing of GANs
Practical applications of GANs
Troubleshooting your system
About the Reader
For data professionals with intermediate Python skills, and the basics of deep learning-based image processing.

As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data.
Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you.
Delve into DNNs and discover how they could be tricked by adversarial input
Investigate methods used to generate adversarial input capable of fooling DNNs
Explore real-world scenarios and model the adversarial threat
Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data
Examine some ways in which AI might become better at mimicking human perception in years to come

Until recently, learning CoreDNS required reading the code or the skimpy documentation on the website. No longer. With this practical book, developers and operators working with Docker containers will understand how to use this standard DNS server with Kubernetes.
John Belamaric, senior staff software engineer at Google, and Cricket Liu, Chief DNS Architect at Infoblox, show you how to configure CoreDNS using real-world configuration examples for achieving specific purposes. You’ll learn the basics of DNS, including how DNS functions as a location broker in container environments, and how it ties in to Kubernetes.

Much in the same way that software transformed business in the past two decades, AI is set to redefine organizations and entire industries. Just as every company is a software company today, every company will soon be an AI company.
This practical guide explains how business and technical leaders can embrace this new breed of organization. Based on real customer experience, Microsoft’s David Carmona covers the journey necessary to become an AI Organization—from applying AI in your business today to the deep transformation that can empower your organization to redefine the industry.
You'll learn the core concepts of AI as they are applied to real business, explore and prioritize the most appropriate use cases for AI in your company, and drive the organizational and cultural change needed to transform your business with AI.

Tap into the wisdom of experts to learn what every engineering manager should know. With the 97 short and extremely useful tips for engineering managers, this book will help you expand your skills. You'll learn how to adopt new approaches to old problems, learn appropriate best practices, and hone your management skills through sound advice.
Managing people is hard, and the industry as a whole is bad at it. Many managers lack the experience, the tools, the texts, and the frameworks to do it well. From mentoring interns to working in senior management, this book will take you through the stages of management, and provide actionable advice on how to approach the obstacles that come up as a technical manager. All you need is a desire to learn new skills for managing more effectively.

There’s more to chaos engineering than deliberately breaking stuff in production. With this book, QA engineers as well as program and product managers will examine the theory, history, and implementation of this full-fledged software engineering discipline. Chaos experts Casey Rosenthal, Nora Jones, and Nathan Aschbacher will bring you up to speed on this practice for finding failures within your application, network, and infrastructure.
As the software industry continues to move toward microservices and other complex, distributed systems, fewer people are able to hold a working picture of the entire system in their minds. Complexity can’t be removed from these systems, but new methodologies allow engineers to navigate the complexity while optimizing for business goals such as feature velocity, performance, and fault tolerance. This book guides you through chaos engineering and demonstrates how this methodology can help you optimize for availability.

The approach to and understanding of software engineering at Google is unlike any other company. With this book, you’ll get a candid and insightful look at how software is constructed and maintained by some of the world’s leading practitioners.
Titus Winters, Tom Manshreck, and Hyrum K. Wright, software engineers and a technical writer at Google, reframe how software engineering is practiced and taught: from an emphasis on programming to an emphasis on software engineering, which roughly translates to programming over time.
You’ll learn:
Fundamental differences between software engineering and programming
How an organization effectively manages a living codebase and efficiently responds to inevitable change
Why culture (and recognizing it) is important, and how processes, practices, and tools come into play

The fascinating story of how Unix began and how it took over the world. Brian Kernighan was a member of the original group of Unix developers, the creator of several fundamental Unix programs, and the co-author of classic books like "The C Programming Language" and "The Unix Programming Environment."

What separates the traditional enterprise from the likes of Amazon, Netflix, and Etsy? Those companies have refined the art of cloud native development to maintain their competitive edge and stay well ahead of the competition. This practical guide shows Java/JVM developers how to build better software, faster, using Spring Boot, Spring Cloud, and Cloud Foundry.
Many organizations have already waded into cloud computing, test-driven development, microservices, and continuous integration and delivery. Authors Josh Long and Kenny Bastani fully immerse you in the tools and methodologies that will help you transform your legacy application into one that is genuinely cloud native.
In four sections, this book takes you through:
The Basics: learn the motivations behind cloud native thinking; configure and test a Spring Boot application; and move your legacy application to the cloud
Web Services: build HTTP and RESTful services with Spring; route requests in your distributed system; and build edge services closer to the data
Data Integration: manage your data with Spring Data, and integrate distributed services with Spring’s support for event-driven, messaging-centric architectures
Production: make your system observable; use service brokers to connect stateful services; and understand the big ideas behind continuous delivery

Quantum computers are poised to kick-start a new computing revolution—and you can join in right away. If you’re in software engineering, computer graphics, data science, or just an intrigued computerphile, this book provides a hands-on programmer’s guide to understanding quantum computing. Rather than labor through math and theory, you’ll work directly with examples that demonstrate this technology’s unique capabilities.
Quantum computing specialists Eric Johnston, Nic Harrigan, and Mercedes Gimeno-Segovia show you how to build the skills, tools, and intuition required to write quantum programs at the center of applications. You’ll understand what quantum computers can do and learn how to identify the types of problems they can solve.
This book includes three multichapter sections:
Programming for a QPU—Explore core concepts for programming quantum processing units, including how to describe and manipulate qubits and how to perform quantum teleportation.
QPU Primitives—Learn algorithmic primitives and techniques, including amplitude amplification, the Quantum Fourier Transform, and phase estimation.
QPU Applications—Investigate how QPU primitives are used to build existing applications, including quantum search techniques and Shor’s factoring algorithm.

In the last 60 years, the use of the notion of category has led to a remarkable unification and simplification of mathematics. Conceptual Mathematics, Second Edition, introduces the concept of ’category’ for the learning, development, and use of mathematics, to both beginning students and general readers, and to practicing mathematical scientists. The treatment does not presuppose knowledge of specific fields, but rather develops, from basic definitions, such elementary categories as discrete dynamical systems and directed graphs; the fundamental ideas are then illuminated by examples in these categories.

This is a bird’s-eye view of the booming blockchain industry, with real-life stories of how the technology is currently used. Ideal for business technology leaders familiar with blockchain, this report explains how this technology might fit within your enterprise and gives you a better sense of whether you’re too early, too late, or right on time.
Written by Sir John Hargrave, CEO of blockchain media company Media Shower, and blockchain consultant Evan Karnoupakis, this report explains how leading financial and technology companies are investing heavily in this new Internet of Money. And while bitcoin still leads the way, the race is on for "stablecoins" pegged to traditional currencies.
Divided into three sections, this report includes:
Blockchain in the economy: Understand the state of the digital asset market—bitcoin and altcoins—and how they’re reshaping the world economy.
Blockchain in the enterprise: Learn where blockchain adoption stands among industries and get hype-free snapshots of early use cases.
How to prepare: Explore practical recommendations for how corporate technology leaders can best prepare for entering the new world of blockchain.

Facebook recently announced Libra, an ambitious project to bring blockchain-based cryptocurrency technology to its users around the world. This large-scale project involves a consortium of organizations in technology and finance hoping to reimagine digital finance. With this report, you’ll explore the promises and challenges Facebook and its stakeholders face as Libra approaches its expected 2020 launch.
Once it arrives, Libra could have a huge impact on finance and consumer banking. What does it mean for average people using financial services? How could Libra impact the global finance and technology sectors? Author Daniel Cawrey (Mastering Blockchain) takes you through the issues and possibilities.
Learn how:
Libra will leverage blockchain, cryptocurrency, and smart contracts within Facebook’s existing platforms
A consortium of organizations across business, technology, and nonprofits will govern Libra
Facebook’s Calibra digital wallet will work within this ecosystem
Libra took ideas from Bitcoin and the greater blockchain community
The system needs to scale to billions of users if it is to work across many devices and networks
Libra could help people with little or no access to the banking system

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques.
This textbook provides a technical perspective on natural language processing―methods for building computer software that understands, generates, and manipulates human language. It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation.
The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.