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.This book is divided into four sections: Introduction--Learn what site reliability engineering is and why it differs from conventional IT industry practicesPrinciples--Examine the patterns, behaviors, and areas of concern that influence the work of a site reliability engineer (SRE)Practices--Understand the theory and practice of an SRE's day-to-day work: building and operating large distributed computing systemsManagement--Explore Google's best practices for training, communication, and meetings that your organization can use

    As for the latter, are you a programmer and curious about being your own boss? Where do you turn for information? Until now, online and traditional literature havent caught up with the reality of the post-dot com bust.Micro-ISV: From Vision to Reality explains what works and why in today's emerging micro-ISV sector. Currently, thousands of programmers build and deliver great solutions ISV-style, earning success and revenues much larger than you might guess. Written by and for micro-ISVs, with help from some of the leaders of the field, this book takes you beyond just daydreaming to running your own business. It thoroughly explores how it is indeed possible to launch and maintain a small and successful ISV business, and is an ideal read if you're interested in getting started.

    Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment.Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility.Understand the tenets of Cassandra's column-oriented structureLearn how to write, update, and read Cassandra dataDiscover how to add or remove nodes from the cluster as your application requiresExamine a working application that translates from a relational model to Cassandra's data modelUse examples for writing clients in Java, Python, and C#Use the JMX interface to monitor a cluster's usage, memory patterns, and moreTune memory settings, data storage, and caching for better performance

    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

    The book teaches MATLAB as a technical programming language showing students how to write clean, efficient, and well-documented programs. It makes no pretense at being a complete description of all of MATLAB's hundreds of functions. Instead, it teaches students how to locate any desired function with MATLAB's extensive on line help facilities. Overall, students develop problem-solving skills and are equipped for future courses and careers using the power of MATLAB.

    This practical guide shows you how to design and maintain infrastructure capable of managing the full lifecycle of these implementations.Engineers Justin Garrison (Walt Disney Animation Studios) and Kris Nova (Dies, Inc.) reveal hard-earned lessons on architecting infrastructure for massive scale and best in class monitoring, alerting, and troubleshooting. The authors focus on Cloud Native Computing Foundation projects and explain where each is crucial to managing modern applications.Understand the fundamentals of cloud native application design, and how it differs from traditional application designLearn how cloud native infrastructure is different from traditional infrastructureManage application lifecycles running on cloud native infrastructure, using Kubernetes for application deployment, scaling, and upgradesMonitor cloud native infrastructure and applications, using fluentd for logging and prometheus + graphana for visualizing dataDebug running applications and learn how to trace a distributed application and dig deep into a running system with OpenTracing

    But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You'll follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.Discover how microservices allow you to align your system design with your organization's goalsLearn options for integrating a service with the rest of your systemTake an incremental approach when splitting monolithic codebasesDeploy individual microservices through continuous integrationExamine the complexities of testing and monitoring distributed servicesManage security with user-to-service and service-to-service modelsUnderstand the challenges of scaling microservice architectures

    He explains why invisible and unmanaged queues are the underlying root cause of poor product development performance. He shows why these queues form and how they undermine the speed, quality, and efficiency in product development.

    But with so many distributed databases and tools available today, it’s often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.Throughout the book, you’ll explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You’ll discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed.This book examines:Storage engines: Explore storage classification and taxonomy, and dive into B-Tree-based and immutable log structured storage engines, with differences and use-cases for eachDistributed systems: Learn step-by-step how nodes and processes connect and build complex communication patterns, from UDP to reliable consensus protocolsDatabase clusters: Discover how to achieve consistent models for replicated data

    This book is neither a step-by-step tutorial nor a reference book. Instead, our goal is to bring a diverse set of software engineering topics together into a single narrative, help readers understand the most important ideas through concrete examples and a learn-by-doing approach, and teach readers enough about each topic to get them started in the field. Courseware for doing the work in the book is available as a virtual machine image that can be downloaded or deployed in the cloud. A free MOOC (massively open online course) at saas-class.org follows the book's content and adds programming assignments and quizzes. See http://saasbook.info for details.

    By scale, we mean having numbers of users in the millions and being built by large engineering teams.For mobile engineers, this book is a blueprint for modern app engineering approaches. For non-mobile engineers and managers, it is a resource with which to build empathy and appreciation for the complexity of world-class mobile engineering.

    It's not that there is a lack of information out there. You can find academic papers, engineering blogs, and even books on the subject. The problem is that the available information is spread out all over the place, and if you were to put it on a spectrum from theory to practice, you would find a lot of material at the two ends, but not much in the middle.That is why I decided to write a book to teach the fundamentals of distributed systems so that you don’t have to spend countless hours scratching your head to understand how everything fits together. This is the guide I wished existed when I first started out, and it's based on my experience building large distributed systems that scale to millions of requests per second and billions of devices.If you develop the back-end of web or mobile applications (or would like to!), this book is for you. When building distributed systems, you need to be familiar with the network stack, data consistency models, scalability and reliability patterns, and much more. Although you can build applications without knowing any of that, you will end up spending hours debugging and re-designing their architecture, learning lessons that you could have acquired in a much faster and less painful way.

    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

    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

    Lambda enables users to develop code that executes in response to events - API calls, file uploads, schedules, etc - and upload it without worrying about managing traditional server metrics such as disk space, memory, or CPU usage. With its "per execution" cost model, Lambda can enable organizations to save hundreds or thousands of dollars on computing costs. With in-depth walkthroughs, large screenshots, and complete code samples, the reader is guided through the step-by-step process of creating new functions, responding to infrastructure events, developing API backends, executing code at specified intervals, and much more. Introduction to AWS Computing Evolution of the Computing Workload Lambda Background The Internals The Basics Functions Languages Resource Allocation Getting Set Up Hello World Uploading the Function Working with Events AWS Events Custom Events The Context Object Properties Methods Roles and Permissions Policies Trust Relationships Console Popups Cross Account Access Dependencies and Resources Node Modules OS Dependencies OS Resources OS Commands Logging Searching Logs Testing Your Function Lambda Console Tests Third-Party Testing Libraries Simulating Context Hello S3 Object The Bucket The Role The Code The Event The Trigger Testing When Lambda Isn’t the Answer Host Access Fine-Tuned Configuration Security Long-Running Tasks Where Lambda Excels AWS Event-Driven Tasks Scheduled Events (Cron) Offloading Heavy Processing API Endpoints Infrequently Used Services Real-World Use Cases S3 Image Processing Shutting Down Untagged Instances Triggering CodeDeploy with New S3 Uploads Processing Inbound Email Enforcing Security Policies Detecting Expiring Certificates Utilizing the AWS API Execution Environment The Code Pipeline Cold vs. Hot Execution What is Saved in Memory Scaling and Container Reuse From Development to Deployment Application Design Development Patterns Testing Deployment Monitoring Versioning and Aliasing Costs Short Executions Long-Running Processes High-Memory Applications Free Tier Calculating Pricing CloudFormation Reusable Template with Minimum Permissions Cross Account Access CloudWatch Alerts AWS API Gateway API Gateway Event Creating the Lambda Function Creating a New API, Resource, and Method Initial Configuration Mapping Templates Adding a Query String Using HTTP Request Information Within Lambda Deploying the API Additional Use Cases Lambda Competitors Iron.io StackHut WebTask.io Existing Cloud Providers The Future of Lambda More Resources Conclusion