AWS Security is an invaluable guide that you’ll want to have on hand when you’re facing any cloud security problem. With a cookbook-style delivery, it’s filled with well-documented examples and procedures you can apply to common AWS security issues. This book covers best practices for access policies, data protection, auditing, continuous monitoring, and incident response. You’ll also explore several deliberately insecure applications, including a social media site and a mobile app, learning the exploits and vulnerabilities commonly used to attack them and the security practices to counter those attacks. With this practical primer, you’ll be well prepared to evaluate your system’s security, detect threats, and respond with confidence.
what's inside
Securely grant access to AWS resources to coworkers and customers
Develop policies for ensuring proper access controls
Lock-down network controls using VPCs
Record audit logs and use them to identify attacks
Track and assess the security of an AWS account
Common attacks and vulnerabilities

AI is complicated, but cloud providers have stepped in to make it easier, offering free (or affordable) state-of-the-art models and training tools to get you started. In this book, AI novices will learn how to use Google’s AI-powered cloud services to do everything from analyzing text, images, and video to creating a chatbot.
Author Micheal Lanham takes you step-by-step through building models, training them, and then expanding on them to accomplish increasingly complex tasks. If you have a good grasp of math and the Python language, this book will get you up and running with Google Cloud Platform, whether you’re looking to build a simple business AI application or an AI assistant.
Learn key concepts for data science, machine learning, and deep learning
Explore tools like Video AI, AutoML Tables, the Cloud Inference API, the Recommendations AI API, and BigQuery ML
Perform image recognition using CNNs, transfer learning, and GANs
Build a simple language processor using embeddings, RNNs, and Bidirectional Encoder
Representations from Transformers (BERT)
Use Dialogflow to build a chatbot
Analyze video with automatic video indexing, face detection, and TF Hub

In this fully updated and new edition, you'll get hands-on practice with the basics, including setting up cloud-based virtual machines, deploying web servers, and using hosted data stores. As you work through the book's 21 carefully planned lessons, you'll explore big-picture concerns like security, scaling, and automation.
Learn Azure in a Month of Lunches, Second Edition teaches you the most important skills you'll need to write, deploy, and run cloud-based applications in Azure.

Organizations today often struggle when trying to balance business requirements with ever-increasing volumes of data. Yet the need to take advantage of real-time data continues to grow among the most competitive digital industries. Conventional system architectures may not be up to the task. With this practical guide, you’ll learn how to leverage large-scale data usage across the business units in your organization using the principles of event-driven microservices.
Author Adam Bellemare from Flipp takes you through the process of building a complete microservice-powered organization. You’ll reconsider how data is produced, accessed, and used across your organization. Discover powerful yet simple patterns for unlocking the value of this data. Incorporate event-driven design and architectural principles into your own systems. And completely rethink how your organization delivers value by unlocking real-time access to data at scale.
You’ll learn:
How to leverage event-driven architectures to deliver exceptional business value
The role of microservices in supporting event-driven design
Architectural patterns to ensure success both within and between teams in your organization
Application patterns for developing powerful event-driven microservices

Improve the performance of relational databases with indexes designed for today's hardware
Over the last few years, hardware and software have advanced beyond all recognition, so it's hardly surprising that relational database performance now receives much less attention. Unfortunately, the reality is that the improved hardware hasn't kept pace with the ever-increasing quantity of data processed today. Although disk packing densities have increased enormously, making storage costs extremely low and sequential read very fast, random reads are still painfully slow. Many of the old design recommendations are therefore no longer valid-the optimal point of indexing has come a long way. Consequently many of the old problems haven't actually gone away-they have simply changed their appearance.
This book provides an easy but effective approach to the design of indexes and tables. Using lots of examples and case studies, the authors describe how the DB2, Oracle, and SQL Server optimizers determine how to access data, and how CPU and response times for the resulting access paths can be quickly estimated. This enables comparisons to be made of the various designs, and helps you choose available choices for the most appropriate design.
This book is intended for anyone who wants to understand the issues of SQL performance or how to design tables and indexes effectively. With this title, readers with many years of experience of relational systems will be able to better grasp the implications that have been brought into play by the introduction of new hardware.
An Instructor's Manual presenting detailed solutions to all the problems in the book is available online from the Wiley editorial department.
An Instructor Support FTP site is also available.

对于嵌入式工程师来说，进入更高阶段后，学习Linux设备驱动开发无疑就是职业生涯的一次“重生”。这是因为Linux设备驱动开发不仅仅涉及操作系统的转换，开发方式的转换，更重要的是思维上的转变。对于Linux这样一个复杂系统，如何从复杂的代码中抓住设备驱动开发的关键是任何一个Linux设备驱动开发者入门时需要面对的挑战。除了知识、工具之外，往往还需要思路上的指导。本书不但帮助Linux设备驱动开发的初学者厘清必要的概念，还从具体的实例、设备驱动开发的指导原则循序渐进地引导读者渐入学习佳境。为了让读者能够达到Linux设备驱动开发的至臻境界，作者更是从软件工程的角度抽象出设备驱动开发的一般思想。毫无疑问，本书将成为读者学习Linux设备驱动开发过程中的一座“灯塔”。

As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSe. We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today's WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today's WSCs on a single board. Table of Contents: Introduction / Workloads and Software Infrastructure / Hardware Building Blocks / Datacenter Basics / Energy and Power Efficiency / Modeling Costs / Dealing with Failures and Repairs / Closing Remarks

Enterprise Java Microservices teaches you to design and build JVM-based microservices applications. You'll start by learning how microservices designs compare to traditional Java EE applications. Always practical, author Ken Finnigan introduces big-picture concepts along with the tools and techniques you'll need to implement them. You'll discover ecosystem components like Netflix Hystrix for fault tolerance and master the Just enough Application Server (JeAS) approach. To ensure smooth operations, you'll also examine monitoring, security, testing, and deploying to the cloud.

GraphQL is a new way of structuring and building web services, and the result is transformational. Find out how to offer a more tailored, cohesive experience to your users, easily aggregate data from different data sources, and improve your back end’s maintainability with Absinthe’s declarative approach to defining how your API works.
Build a GraphQL-based API from scratch using Absinthe, starting from core principles. Learn the type system and how to expand your schema to suit your application’s needs. Discover a growing ecosystem of tools and utilities to understand, debug, and document your API. Take it to production, but do it safely with solid best practices in mind. Find out how complexity analysis and persisted queries can let you support your users flexibly, but responsibly too. Along the way, discover how Elixir makes all the difference for a high performance, fault-tolerant API. Use asynchronous and batching execution, or write your own custom add-ons to extend Absinthe. Go live with subscriptions, delivering data over websockets on top of Elixir (and Erlang/OTP’s) famous solid performance and real-time capabilities.
Transform your applications with the powerful combination of Elixir and GraphQL, using Absinthe.

Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment.
Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility.
Understand Cassandra’s distributed and decentralized structure
Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell
Create a working data model and compare it with an equivalent relational model
Develop sample applications using client drivers for languages including Java, Python, and Node.js
Explore cluster topology and learn how nodes exchange data

PostGIS in Action, Third Edition teaches you to solve real-world geodata problems. It first gives you a background in vector-, raster-, and topology-based GIS and then quickly moves into analyzing, viewing, and mapping data. You'll learn how to optimize queries for maximum speed, simplify geometries for greater efficiency, and create custom functions for your own applications. You'll also learn how to apply your existing GIS knowledge to PostGIS and integrate with other GIS tools. Fully updated to the latest versions of PostGIS and PostgreSQL, this Third Edition covers new PostGIS features including Foreign Data Wrappers, Database as a Service, parallelization of queries, and new JSON and Vector Tiles functions that help in creating web mapping applications.
what's inside
An introduction to spatial databases
Geometry, geography, raster, and topology spatial types, functions, and queries
Applying PostGIS to real-world problems
Extending PostGIS to web and desktop applications
Updated for PostGIS 3 and PostgreSQL 12

Practical SQL is an approachable and fast-paced guide to SQL (Structured Query Language), the standard programming language for defining, organizing, and exploring data in relational databases. The book focuses on using SQL to find the story your data tells, with the popular open-source database PostgreSQL and the pgAdmin interface as its primary tools.
You’ll first cover the fundamentals of databases and the SQL language, then build skills by analyzing data from the U.S. Census and other federal and state government agencies. With exercises and real-world examples in each chapter, this book will teach even those who have never programmed before all the tools necessary to build powerful databases and access information quickly and efficiently.
You’ll learn how to:
Create databases and related tables using your own data
Define the right data types for your information
Aggregate, sort, and filter data to find patterns
Use basic math and advanced statistical functions
Identify errors in data and clean them up
Import and export data using delimited text files
Write queries for geographic information systems (GIS)
Create advanced queries and automate tasks
Learning SQL doesn’t have to be dry and complicated. Practical SQL delivers clear examples with an easy-to-follow approach to teach you the tools you need to build and manage your own databases.
This book uses PostgreSQL, but the SQL syntax is applicable to many database applications, including Microsoft SQL Server and MySQL.

With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library.
Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you'll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!

Knative in Action shows you how to build more complex and capable serverless applications with Knative. You’ll start by getting up to speed with the basics of serverless computing, Knative’s design concepts, and the tricky problems that the toolkit works to simplify. Next, Knative expert Jacques Chester takes you through how to use Knative Serving to build your systems, baking in autoscaling, auto-updating, and easy deployment right from the start. From there you’ll learn how to use Knative Eventing to wire together disparate systems into an elegant, functional whole. Finally, you'll learn how Knative can be used to smooth your shipping pipeline, from initial development right through to monitoring your software in production.
what's inside
Deploying a service with Knative Serving
Connecting systems with Knative Eventing
Autoscaling for differing server loads
Developing, shipping, and operating software with Knative

Objects are the central concept of languages like Java, Python, C#. Applying best practices for object design means that your code will be easy to read, write, and maintain. Object Design Style Guide captures dozens of techniques for creating pro-quality OO code that can stand the test of time. Examples are in an instantly-familiar pseudocode, teaching techniques you can apply to any OO language, from C++ to PHP.

Object-oriented programming (OOP) is the foundation of modern programming languages, including C++, Java, C#, Visual Basic .NET, Ruby, Objective-C, and Swift. Objects also form the basis for many web technologies such as JavaScript, Python, and PHP.
It is of vital importance to learn the fundamental concepts of object orientation before starting to use object-oriented development environments. OOP promotes good design practices, code portability, and reuse–but it requires a shift in thinking to be fully understood. Programmers new to OOP should resist the temptation to jump directly into a particular programming language or a modeling language, and instead first take the time to learn what author Matt Weisfeld calls “the object-oriented thought process.”
Written by a developer for developers who want to improve their understanding of object-oriented technologies, The Object-Oriented Thought Process provides a solutions-oriented approach to object-oriented programming. Readers will learn to understand the proper uses of inheritance and composition, the difference between aggregation and association, and the important distinction between interfaces and implementations.
While programming technologies have been changing and evolving over the years, object-oriented concepts remain a constant–no matter what the platform. This revised edition focuses on the OOP technologies that have survived the past 20 years and remain at its core, with new and expanded coverage of design patterns, avoiding dependencies, and the SOLID principles to help make software designs understandable, flexible, and maintainable.

Need simple solutions to specific challenges with Java 8 and Java 9? This book of practical recipes provides a quick, easy reference for developers who prefer useful examples over detailed explanations. Modern Java Recipes shows you how to solve a wide range of problems using the newest features of Java.Learn functional programming with lambdas, method references, and streamsAdopt the new static and default methods in interfacesWork with the new set of functional interfaces added to the languageUse collectors and comparators to search, filter, and sort dataEmploy the new Optional type and use it correctlyUnderstand the new java.time package to handle Date and Time functionality, including time zone adjustmentsUse the Java Read-Eval-Print-Loop in Java 9Employ the new Jigsaw mechanism to modularize deployables

内容介绍
这是一部从工作原理和工程实践两个维度深入剖析JVM的著作，是计算机领域公认的经典，繁体版在台湾也颇受欢迎。
自2011年上市以来，前两个版本累计印刷36次，销量超过30万册，两家主要网络书店的评论近90000条，内容上近乎零差评，是原创计算机图书领域不可逾越的丰碑。
第3版在第2版的基础上做了重大修订，内容更丰富、实战性更强：根据新版JDK对内容进行了全方位的修订和升级，围绕新技术和生产实践新增逾10万字，包含近50%的全新内容，并对第2版中含糊、瑕疵和错误内容进行了修正。
全书一共13章，分为五大部分：
第一部分（第1章）走近Java
系统介绍了Java的技术体系、发展历程、虚拟机家族，以及动手编译JDK，了解这部分内容能对学习JVM提供良好的指引。
第二部分（第2~5章）自动内存管理
详细讲解了Java的内存区域与内存溢出、垃圾收集器与内存分配策略、虚拟机性能监控与故障排除等与自动内存管理相关的内容，以及10余个经典的性能优化案例和优化方法；
第三部分（第6~9章）虚拟机执行子系统
深入分析了虚拟机执行子系统，包括类文件结构、虚拟机类加载机制、虚拟机字节码执行引擎，以及多个类加载及其执行子系统的实战案例；
第四部分（第10~11章）程序编译与代码优化
详细讲解了程序的前、后端编译与优化，包括前端的易用性优化措施，如泛型、主动装箱拆箱、条件编译等的内容的深入分析；以及后端的性能优化措施，如虚拟机的热点探测方法、HotSpot 的即时编译器、提前编译器，以及各种常见的编译期优化技术；
第五部分（第12~13章）高效并发
主要讲解了Java实现高并发的原理，包括Java的内存模型、线程与协程，以及线程安全和锁优化。
全书以实战为导向，通过大量与实际生产环境相结合的案例分析和展示了解决各种Java技术难题的方案和技巧。

How can you use data in a way that protects individual privacy, but still ensures that data analytics will be useful and meaningful? With this practical book, data architects and engineers will learn how to implement and deploy anonymization solutions within a data collection pipeline. You’ll establish and integrate secure, repeatable anonymization processes into your data flows and analytics in a sustainable manner.
Luk Arbuckle and Khaled El Emam from Privacy Analytics explore end-to-end solutions for anonymizing data, based on data collection models and use cases enabled by real business needs. These examples come from some of the most demanding data environments, using approaches that have stood the test of time.

Core Kubernetes is a reference guide designed to teach operators, SREs, and developers how to improve reliability and performance of Kubernetes-based systems. In it, Kubernetes experts Chris Love and Jay Vyas provide a guided tour through all major aspects of Kubernetes, from managing iptables to setting up dynamically scaled clusters that respond to changes in load. You’ll understand the unique security concerns of container-based applications, discover tips to minimize costly unused capacity, and get pro tips for maximizing performance. This awesome collection of undocumented internals, expert techniques, and practical guidance has invaluable information you won’t find anywhere else.
what's inside
Kubernetes base components
Kubernetes networking
Storage and the Container Storage Interface
External load balancing and ingress
Kubernetes security
Different ways of creating a Kubernetes cluster
Configuring Kubernetes to use a GPU