Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords?
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.
Peer under the hood of the systems you already use, and learn how to use and operate them more effectively
Make informed decisions by identifying the strengths and weaknesses of different tools
Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity
Understand the distributed systems research upon which modern databases are built
Peek behind the scenes of major online services, and learn from their architectures

Git is the version control system developed by Linus Torvalds for Linux kernel development. It took the open source world by storm since its inception in 2005, and is used by small development shops and giants like Google, Red Hat, and IBM, and of course many open source projects.
* A book by Git experts to turn you into a Git expert
* Introduces the world of distributed version control
* Shows how to build a Git development workflow
What you’ll learn
* Use Git as a programmer or a project leader.
* Become a fluent Git user.
* Use distributed features of Git to the full.
* Acquire the ability to insert Git in the development workflow.
* Migrate programming projects from other SCMs to Git.
* Learn how to extend Git.
This book is for all open source developers: you are bound to encounter it somewhere in the course of your working life. Proprietary software developers will appreciate Git’s enormous scalability, since it is used for the Linux project, which comprises thousands of developers and testers.

This text identifies, examines, and illustrates fundamental concepts in computer system design that are common across operating systems, networks, database systems, distributed systems, programming languages, software engineering, security, fault tolerance, and architecture. Through carefully analyzed case studies from each of these disciplines, it demonstrates how to apply these concepts to tackle practical system design problems.
To support the focus on design, the text identifies and explains abstractions that have proven successful in practice such as, remote procedure call, client/service organization, file systems, data integrity, consistency, and authenticated messages. Most computer systems are built using a handful of such abstractions. The text describes how these abstractions are implemented, demonstrates how they are used in different systems, and prepares the reader to apply them in future designs.
Features:

Concepts of computer system design guided by fundamental principles.
Cross-cutting approach that identifies abstractions common to networking, operating systems, transaction systems, distributed systems, architecture, and software engineering.
Case studies that make the abstractions real: naming (DNS and the URL); file systems (the UNIX file system); clients and services (NFS); virtualization (virtual machines); scheduling (disk arms); security (TLS).
Numerous pseudocode fragments that provide concrete examples of abstract concepts.
Extensive support. The authors and MIT OpenCourseWare provide on-line, free of charge, open educational resources, including additional chapters, course syllabi, board layouts and slides, lecture videos, and an archive of lecture schedules, class assignments, and design projects.

这是一本从架构视角讲解如何构建大型分布式系统的著作，是超级畅销书《深入理解Java虚拟机》的作者周志明多年架构和研发经验的总结，得到了多位行业资深架构专家的联袂推荐。
全书共16章，分为演进中的架构、架构师的视角、分布式的基石、不可变基础设施和技术方法论五部分。
第一部分 演进中的架构（第1章）
着重介绍了软件开发历史中多种主流架构风格出现的契机、解决的问题以及带来的新缺陷。
第二部分 架构师的视角（第2~5章）
总结了一名架构师应该在架构设计时思考哪些问题，有哪些主流的解决方案和行业标准做法，各种方案有什么优缺点，不同的解决方法会带来什么不同的影响，等等。
第三部分 分布式的基石（第6~10章）
重点讨论了“不同架构风格是应该在技术规范上统一，还是由应用系统自行解决”这个问题，给出了解决思路、方法和常见工具。
第四部分 不可变基础设施（第11~15章）
重点讲解了基础设施不变性的目的、原理与实现途径，包括虚拟化容器、容器间网络、持久化存储、资源与调度、服务网格等内容。
第五部分 技术方法论（第16章）
面向技术决策者集中讨论了与分布式、微服务、架构等相关的理论话题，将解决问题的能力归纳、总结、升华为方法论。
全书以实践为导向，一个案例贯穿全书，同时给出了基于Spring Boot、Spring Cloud、Kubernetes、Istio、AWS Lambda 五种架构风格的样例工程。

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way.
Expanded from Tyler Akidau’s popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You’ll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax.
You’ll explore:
How streaming and batch data processing patterns compare
The core principles and concepts behind robust out-of-order data processing
How watermarks track progress and completeness in infinite datasets
How exactly-once data processing techniques ensure correctness
How the concepts of streams and tables form the foundations of both batch and streaming data processing
The practical motivations behind a powerful persistent state mechanism, driven by a real-world example
How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

Go is an open-source programming language that makes it easy to build clean, reliable, and efficient software. It has been winning converts from dynamic language enthusiasts as well as users of traditional compiled languages. The former appreciate the robustness and efficiency that Go's lightweight type system brings to their code; the latter find Go's simplicity and fast tools a refreshing change. Thanks to its well-designed standard libraries and its excellent support for concurrent programming, Go is fast becoming the language of choice for distributed systems.<br /> <br /><strong>The Go Programming Language</strong> is the definitive book on Go for the working programmer. It assumes no prior knowledge of Go, nor any other specific programming language, so you'll find it an accessible guide whether you come from JavaScript, Ruby, Python, Java, or C++.<br /> <br />The book will quickly get you started using Go effectively from the beginning, and by the end, you will know how to use it well to write clear, idiomatic and efficient programs to solve real-world problems. You'll understand not just how to use its standard libraries, but how they work, and how to apply the same design techniques to your own projects.<br /> <br />The earlier chapters will introduce you to the basic concepts of Go programming---numbers, strings, functions---while at the same time presenting important computer science concepts like recursion, and useful examples of graphics, UTF-8, and error handling. The chapters on methods and interfaces will show you a new way to think about object-oriented programming; the chapter on concurrency explains why concurrency is so important in modern programming, and how Go helps you handle it well. You'll also learn about Go's pragmatic but effective approach to testing; how to build, test, and manage projects using the go tool, and the art of metaprogramming using reflection.<br /> <br />The book contains hundreds of interesting and practical examples that cover the whole language and a wide range of applications. The code samples from the book are available for download from gopl.io.

Kubernetes in Action teaches you to use Kubernetes to deploy container-based distributed applications. You'll start with an overview of Docker and Kubernetes before building your first Kubernetes cluster. You'll gradually expand your initial application, adding features and deepening your knowledge of Kubernetes architecture and operation. As you navigate this comprehensive guide, you'll explore high-value topics like monitoring, tuning, and scaling.
Kubernetes is Greek for "helmsman," your guide through unknown waters. The Kubernetes container orchestration system safely manages the structure and flow of a distributed application, organizing containers and services for maximum efficiency. Kubernetes serves as an operating system for your clusters, eliminating the need to factor the underlying network and server infrastructure into your designs.

The overwhelming majority of a software system’s lifespan is spent in use, not in design or implementation. So, why does conventional wisdom insist that software engineers focus primarily on the design and development of large-scale computing systems?
In this collection of essays and articles, key members of Google’s Site Reliability Team explain how and why their commitment to the entire lifecycle has enabled the company to successfully build, deploy, monitor, and maintain some of the largest software systems in the world. You’ll learn the principles and practices that enable Google engineers to make systems more scalable, reliable, and efficient—lessons directly applicable to your organization.

Learn You a Haskell for Great Good! is a fun, illustrated guide to learning Haskell, a functional programming language that's growing in popularity. Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.
About the Author
Miran Lipovaca is a computer science student in Ljubljana, Slovenia. His online tutorial, "Learn You a Haskell for Great Good!," is widely regarded as the best way to learn Haskell.

在当今整个中国社会都处于互联网转型的浪潮中，不管是政府职能单位、业务规模庞大的央企，还是面临最激烈竞争的零售行业都处于一个重要的转折点，这个转折对企业业务模式带来了冲击，当然也给企业的信息中心部门带来了挑战：如何构建IT系统架构更好地满足互联网时代下企业业务发展的需要。阿里巴巴的共享服务理念以及企业级互联网架构建设的思路，给这些企业带来了不少新的思路，这也是我最终决定写这本书的最主要原因。本书从阿里巴巴启动中台战略说起，详细阐述了共享服务理念给企业业务发展带来的业务价值。接着会分享阿里巴巴在建设共享服务体系时如何进行技术框架的选择，哪些重要的技术平台支撑起了共享服务体系，这也是迄今为止对阿里巴巴集团中间件体系对外最全面系统的介绍。除了技术层面之外，本书还分享了阿里巴巴内部的一些经验和实践，如组织的架构和体制如何更好地支持共享服务体系的持续发展。

Although salary surveys worldwide regularly identify software architect as one of the top ten best jobs, no decent guides exist to help developers become architects. Until now. This practical guide provides the first comprehensive overview of software architecture’s many aspects. You’ll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics.
Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You’ll focus on architecture principles with examples that apply across all technology stacks.

《大规模分布式存储系统：原理解析与架构实战》是分布式系统领域的经典著作，由阿里巴巴高级技术专家“阿里日照”（OceanBase核心开发人员）撰写，阳振坤、章文嵩、杨卫华、汪源、余锋（褚霸）、赖春波等来自阿里、新浪、网易和百度的资深技术专家联袂推荐。理论方面，不仅讲解了大规模分布式存储系统的核心技术和基本原理，而且对谷歌、亚马逊、微软和阿里巴巴等国际型大互联网公司的大规模分布式存储系统进行了分析；实战方面，首先通过对阿里巴巴的分布式数据库OceanBase的实现细节的深入剖析完整地展示了大规模分布式存储系统的架构与设计过程，然后讲解了大规模分布式存储技术在云计算和大数据领域的实践与应用。
《大规模分布式存储系统：原理解析与架构实战》内容分为四个部分：基础篇——分布式存储系统的基础知识，包含单机存储系统的知识，如数据模型、事务与并发控制、故障恢复、存储引擎、压缩/解压缩等；分布式系统的数据分布、复制、一致性、容错、可扩展性等。范型篇——介绍谷歌、亚马逊、微软、阿里巴巴等著名互联网公司的大规模分布式存储系统架构，涉及分布式文件系统、分布式键值系统、分布式表格系统以及分布式数据库技术等。实践篇——以阿里巴巴的分布式数据库OceanBase为例，详细介绍分布式数据库内部实现，以及实践过程中的经验。专题篇——介绍分布式系统的主要应用：云存储和大数据，这些是近年来的热门领域，本书介绍了云存储平台、技术与安全，以及大数据的概念、流式计算、实时分析等。

《Paxos到Zookeeper：分布式一致性原理与实践》从分布式一致性的理论出发，向读者简要介绍几种典型的分布式一致性协议，以及解决分布式一致性问题的思路，其中重点讲解了Paxos和ZAB协议。同时，本书深入介绍了分布式一致性问题的工业解决方案——ZooKeeper，并着重向读者展示这一分布式协调框架的使用方法、内部实现及运维技巧，旨在帮助读者全面了解ZooKeeper，并更好地使用和运维ZooKeeper。全书共8章，分为五部分：第一部分（第1章）主要介绍了计算机系统从集中式向分布式系统演变过程中面临的挑战，并简要介绍了ACID、CAP和BASE等经典分布式理论；第二部分（第2～4章）介绍了2PC、3PC和Paxos三种分布式一致性协议，并着重讲解了ZooKeeper中使用的一致性协议——ZAB协议；第三部分（第5～6章）介绍了ZooKeeper的使用方法，包括客户端API的使用以及对ZooKeeper服务的部署与运行，并结合真实的分布式应用场景，总结了ZooKeeper使用的最佳实践；第四部分（第7章）对ZooKeeper的架构设计和实现原理进行了深入分析，包含系统模型、Leader选举、客户端与服务端的工作原理、请求处理，以及服务器角色的工作流程和数据存储等；第五部分（第8章）介绍了ZooKeeper的运维实践，包括配置详解和监控管理等，重点讲解了如何构建一个高可用的ZooKeeper服务。

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。

本书以图配文，详细说明了服务器端网络架构的基础技术和设计要点。基础设计是服务器端网络架构最重要的一个阶段。本书就立足于基础设计的设计细分项目，详细介绍各细分项目的相关技术和设计要点。全书共分为5章，分别讲述进行物理设计、逻辑设计、安全设计和负载均衡设计、高可用性设计以及管理设计时所必需的技术和设计要点。

本书的内容主要包含以下几部分：1） 架构设计基础，包括架构设计相关概念、历史、原则、基本方法，让架构设计不再神秘；2） 架构设计流程，通过一个虚拟的案例，描述了一个通用的架构设计流程，让架构设计不再依赖天才的创作，而是有章可循；3） 架构设计专题：包括高性能架构设计、高可用架构设计、可扩展架构设计，这些模式可以直接参考和应用；4） 架构设计实战，包括重构、开源方案引入、架构发展路径、互联网架构模板等

每个应用程序都会产生数据，包括日志消息、度量指标、用户活动记录、响应消息等。如何移动数据，几乎变得与数据本身一样重要。如果你是架构师、开发者或者产品工程师，同时也是Apache Kafka新手，那么这本实践指南将会帮助你成为流式平台上处理实时数据的专家。
本书由出身于LinkedIn的Kafka核心作者和一线技术人员共同执笔，详细介绍了如何部署Kafka集群、开发可靠的基于事件驱动的微服务，以及基于Kafka平台构建可伸缩的流式应用程序。通过详尽示例，你将会了解到Kafka的设计原则、可靠性保证、关键API，以及复制协议、控制器和存储层等架构细节。
● 了解发布和订阅消息模型以及该模型如何被应用在大数据生态系统中
● 学习使用Kafka生产者和消费者来生成消息和读取消息
● 了解Kafka保证可靠性数据传递的模式和场景需求
● 使用Kafka构建数据管道和应用程序的最佳实践
● 在生产环境中管理Kafka，包括监控、调优和维护
● 了解Kafka的关键度量指标
● 探索Kafka如何成为流式处理利器

The accelerating deployment of large-scale web, cloud, Big Data, and virtualized computing systems has introduced serious new challenges in performance optimization. Until now, however, little reliable, practical information has been available to IT professionals who are responsible for running these systems efficiently and cost-effectively.
Systems Performance: Enterprise and the Cloud is the solution. Internationally renowned performance optimization expert Brendan Gregg brings together state-of-the-art techniques and tools for analysis and tuning of large-scale web/cloud computing environments.
Gregg focuses on Linux/Unix/Solaris performance issues, while offering proven methodologies and discussing key issues that apply to all enterprise operating systems. Coverage includes:
Modern performance analysis and capacity planning, including key issues such as latency and dynamic tracing
New performance and reliability challenges associated with cloud computing
Methodology, concepts, terminology, tools, and metrics
Key tradeoffs, including problems of load vs. architecture
Tuning operating systems, CPUs, memory, file systems, disks, networks, and busses
Tuning virtualized systems
Programming language issues related to performance — including application profiling for C, C++, Java, and node.js
Benchmarking strategies and pitfalls, including custom microbenchmarking

《深入理解Kafka：核心设计与实践原理》从Kafka的基础概念切入，循序渐进地转入对其内部原理的剖析。《深入理解Kafka：核心设计与实践原理》主要阐述了Kafka中生产者客户端、消费者客户端、主题与分区、日志存储、原理解析、监控管理、应用扩展及流式计算等内容。虽然Kafka的内核使用Scala语言编写，但《深入理解Kafka：核心设计与实践原理》基本以Java语言作为主要的示例语言，方便大多数读者的理解。虽然《深入理解Kafka：核心设计与实践原理》没有明确的界定，但总体上可以划分为三个部分：基础篇、原理篇和扩展篇，前4章为基础篇，包括基础概念、生产者、消费者，以及主题与分区，学习完这4章的内容完全可以应对绝大多数的开发场景。第5章至第8章为原理篇，包括对日志存储、协议设计、控制器、组协调器、事务、一致性、可靠性等内容的探究，学习完这4章的内容可以让读者对Kafka有一个深刻的认知。最后4章从应用扩展层面来做讲解，可以归类为扩展篇，主要内容包括监控、应用工具、应用扩展（延时队列、重试队列、死信队列、消息轨迹等）、与Spark的集成等，让读者可以对Kafka的生态有一个更加全面的认知。
《深入理解Kafka：核心设计与实践原理》定位为一本实战与原理相结合的书，既适合Kafka的初学者，也适合于对Kafka有一定深度认知的老手。