You will be able to look over the shoulder of major coding and design experts to see problems through their eyes.This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to break rules. Beautiful Code is an opportunity for master coders to tell their story. All author royalties will be donated to Amnesty International.

    Vaughn Vernon couples guided approaches to implementation with modern architectures, highlighting the importance and value of focusing on the business domain while balancing technical considerations.Building on Eric Evans’ seminal book, Domain-Driven Design, the author presents practical DDD techniques through examples from familiar domains. Each principle is backed up by realistic Java examples–all applicable to C# developers–and all content is tied together by a single case study: the delivery of a large-scale Scrum-based SaaS system for a multitenant environment.The author takes you far beyond “DDD-lite” approaches that embrace DDD solely as a technical toolset, and shows you how to fully leverage DDD’s “strategic design patterns” using Bounded Context, Context Maps, and the Ubiquitous Language. Using these techniques and examples, you can reduce time to market and improve quality, as you build software that is more flexible, more scalable, and more tightly aligned to business goals.

    

    This hands-on second edition, expanded and thoroughly updated for Terraform version 0.12 and beyond, shows you the fastest way to get up and running.Gruntwork cofounder Yevgeniy (Jim) Brikman walks you through code examples that demonstrate Terraform's simple, declarative programming language for deploying and managing infrastructure with a few commands. Veteran sysadmins, DevOps engineers, and novice developers will quickly go from Terraform basics to running a full stack that can support a massive amount of traffic and a large team of developers.Explore changes from Terraform 0.9 through 0.12, including backends, workspaces, and first-class expressionsLearn how to write production-grade Terraform modulesDive into manual and automated testing for Terraform codeCompare Terraform to Chef, Puppet, Ansible, CloudFormation, and Salt StackDeploy server clusters, load balancers, and databasesUse Terraform to manage the state of your infrastructureCreate reusable infrastructure with Terraform modulesUse advanced Terraform syntax to achieve zero-downtime deployment

    And considering that the "one man" is Neal Stephenson, "the hacker Hemingway" (Newsweek) -- acclaimed novelist, pragmatist, seer, nerd-friendly philosopher, and nationally bestselling author of groundbreaking literary works (Snow Crash, Cryptonomicon, etc., etc.) -- the word is well worth hearing. Mostly well-reasoned examination and partial rant, Stephenson's In the Beginning... was the Command Line is a thoughtful, irreverent, hilarious treatise on the cyber-culture past and present; on operating system tyrannies and downloaded popular revolutions; on the Internet, Disney World, Big Bangs, not to mention the meaning of life itself.

    Salesforce.com (more than 50%) and Twitter (more than 75% fall into this category. Ebay gets more than 8 billion API calls a month. Facebook and Google, have dozens of APIs that enable both free services and e-commerce, get more than 5 billion API calls each day. Other companies like NetFlix have expanded their service of streaming movies over the the web to dozens of devices using API. At peak times, more than 20 percent of all traffic is accounted for by Netflix through its APIs. Companies like Sears and E-Trade are opening up their catalogs and other services to allow developers and entrepreneurs to create new marketing experiences. Making an API work to create a new channel is not just a matter of technology. An API must be considered in terms of business strategy, marketing, and operations as well as the technical aspects of programming. This book, written by Greg Brail, CTO of Apigee, and Brian Mulloy, VP of Products, captures the knowledge of all these areas gained by Apigee, the leading company in supporting the rollout of high traffic APIs.

    The book will teach you about the most important services on AWS. You will also learn about best practices regarding automation, security, high availability, and scalability.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyPhysical data centers require lots of equipment and take time and resources to manage. If you need a data center, but don't want to build your own, Amazon Web Services may be your solution. Whether you're analyzing real-time data, building software as a service, or running an e-commerce site, AWS offers you a reliable cloud-based platform with services that scale. All services are controllable via an API which allows you to automate your infrastructure.About the BookAmazon Web Services in Action introduces you to computing, storing, and networking in the AWS cloud. The book will teach you about the most important services on AWS. You will also learn about best practices regarding security, high availability and scalability.You'll start with a broad overview of cloud computing and AWS and learn how to spin-up servers manually and from the command line. You'll learn how to automate your infrastructure by programmatically calling the AWS API to control every part of AWS. You will be introduced to the concept of Infrastructure as Code with the help of AWS CloudFormation.You will learn about different approaches to deploy applications on AWS. You'll also learn how to secure your infrastructure by isolating networks, controlling traffic and managing access to AWS resources. Next, you'll learn options and techniques for storing your data. You will experience how to integrate AWS services into your own applications by the use of SDKs. Finally, this book teaches you how to design for high availability, fault tolerance, and scalability.What's InsideOverview of cloud concepts and patternsManage servers on EC2 for cost-effectivenessInfrastructure automation with Infrastructure as Code (AWS CloudFormation)Deploy applications on AWSStore data on AWS: SQL, NoSQL, object storage and block storageIntegrate Amazon's pre-built servicesArchitect highly available and fault tolerant systemsAbout the ReaderWritten for developers and DevOps engineers moving distributed applications to the AWS platform.About the AuthorsAndreas Wittig and Michael Wittig are software engineers and consultants focused on AWS and web development.Table of ContentsPART 1 GETTING STARTEDWhat is Amazon Web Services?A simple example: WordPress in five minutesPART 2 BUILDING VIRTUAL INFRASTRUCTURE WITH SERVERS AND NETWORKINGUsing virtual servers: EC2Programming your infrastructure: the command line, SDKs, and CloudFormationAutomating deployment: CloudFormation, Elastic Beanstalk, and OpsWorksSecuring your system: IAM, security groups, and VPCPART 3 STORING DATA IN THE CLOUDStoring your objects: S3 and GlacierStoring your data on hard drives: EBS and instance storeUsing a relational database service: RDSProgramming for the NoSQL database service: DynamoDBPART 4 ARCHITECTING ON AWSAchieving high availability: availability zones, auto-scaling, and CloudWatchDecoupling your infrastructure: ELB and SQSDesigning for fault-toleranceScaling up and down: auto-scaling and CloudWatch

    This practical introduction illuminates new features and capabilities, with scenarios demonstrating how the platform can meet the needs of your business.Based on beta software, this book provides the early, high-level information you need to begin preparing now for deployment and management. Topics include:Virtualization and cloud solutions Availability Provisioning and storage management Security and scalability Infrastructure options Server administration

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    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.

    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

    The aim of The Node Beginner Book is to get you started with developing applications for Node.js, teaching you everything you need to know about advanced JavaScript along the way on 59 pages.

    The authors also include examples covering a variety of different integration technologies, such as JMS, MSMQ, TIBCO ActiveEnterprise, Microsoft BizTalk, SOAP, and XSL. A case study describing a bond trading system illustrates the patterns in practice, and the book offers a look at emerging standards, as well as insights into what the future of enterprise integration might hold. This book provides a consistent vocabulary and visual notation framework to describe large-scale integration solutions across many technologies. It also explores in detail the advantages and limitations of asynchronous messaging architectures. The authors present practical advice on designing code that connects an application to a messaging system, and provide extensive information to help you determine when to send a message, how to route it to the proper destination, and how to monitor the health of a messaging system. If you want to know how to manage, monitor, and maintain a messaging system once it is in use, get this book.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Want to impress your coworkers and write the fastest, most efficient, stable code you ever have? Don't reinvent the wheel. Reuse decades of research into battle-tested, highly optimized, and proven techniques available on any Unix system.This book will teach you what you need to know so that you can write your own servers, debug your entire stack when things go awry, and understand how things are working under the hood.http://www.jstorimer.com/products/wor...