In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems. You will focus on: Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing

In many systems, scalability becomes the primary driver as the user base grows. Attractive features and high utility breed success, which brings more requests to handle and more data to manage. But organizations reach a tipping point when design decisions that made sense under light loads suddenly become technical debt. This practical book covers design approaches and technologies that make it possible to scale an application quickly and cost-effectively. Author Ian Gorton takes software architects and developers through the foundational principles of distributed systems. You'll explore the essential ingredients of scalable solutions, including replication, state management, load balancing, and caching. Specific chapters focus on the implications of scalability for databases, microservices, and event-based streaming systems. You will focus on: Foundations of scalable systems: Learn basic design principles of scalability, its costs, and architectural tradeoffs Designing scalable services: Dive into service design, caching, asynchronous messaging, serverless processing, and microservices Designing scalable data systems: Learn data system fundamentals, NoSQL databases, and eventual consistency versus strong consistency Designing scalable streaming systems: Explore stream processing systems and scalable event-driven processing

Learning to build distributed systems is hard, especially if they are large scale. 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 that brings together the core theoretical and practical concepts of distributed systems so that you don't have to spend hours connecting the dots. This book will guide you through the fundamentals of large-scale distributed systems, with just enough details and external references to dive deeper. This is the guide I wished existed when I first started out, based on my experience building large distributed systems that scale to millions of requests per second and billions of devices. If you are a developer working on the backend of web or mobile applications (or would like to be!), this book is for you. When building distributed applications, you need to be familiar with the network stack, data consistency models, scalability and reliability patterns, observability best practices, and much more. Although you can build applications without knowing much of that, you will end up spending hours debugging and re-architecting them, learning hard lessons that you could have acquired in a much faster and less painful way. However, if you have several years of experience designing and building highly available and fault-tolerant applications that scale to millions of users, this book might not be for you. As an expert, you are likely looking for depth rather than breadth, and this book focuses more on the latter since it would be impossible to cover the field otherwise. The second edition is a complete rewrite of the previous edition. Every page of the first edition has been reviewed and where appropriate reworked, with new topics covered for the first time.

Without established design patterns to guide them, developers have had to build distributed systems from scratch, and most of these systems are very unique indeed. Today, the increasing use of containers has paved the way for core distributed system patterns and reusable containerized components. This practical guide presents a collection of repeatable, generic patterns to help make the development of reliable distributed systems far more approachable and efficient. Author Brendan Burns—Director of Engineering at Microsoft Azure—demonstrates how you can adapt existing software design patterns for designing and building reliable distributed applications. Systems engineers and application developers will learn how these long-established patterns provide a common language and framework for dramatically increasing the quality of your system. Understand how patterns and reusable components enable the rapid development of reliable distributed systems Use the side-car, adapter, and ambassador patterns to split your application into a group of containers on a single machine Explore loosely coupled multi-node distributed patterns for replication, scaling, and communication between the components Learn distributed system patterns for large-scale batch data processing covering work-queues, event-based processing, and coordinated workflows

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

Job titles like “Technical Architect” and “Chief Architect” nowadays abound in software industry, yet many people suspect that “architecture” is one of the most overused and least understood terms in professional software development. Gorton’s book tries to resolve this dilemma. It concisely describes the essential elements of knowledge and key skills required to be a software architect. The explanations encompass the essentials of architecture thinking, practices, and supporting technologies. They range from a general understanding of structure and quality attributes through technical issues like middleware components and service-oriented architectures to recent technologies like model-driven architecture, software product lines, aspect-oriented design, and the Semantic Web, which will presumably influence future software systems. This second edition contains new material covering enterprise architecture, agile development, enterprise service bus technologies, RESTful Web services, and a case study on how to use the MeDICi integration framework. All approaches are illustrated by an ongoing real-world example. So if you work as an architect or senior designer (or want to someday), or if you are a student in software engineering, here is a valuable and yet approachable knowledge source for you.

Every day, companies struggle to scale critical applications. As traffic volume and data demands increase, these applications become more complicated and brittle, exposing risks and compromising availability. With the popularity of software as a service, scaling has never been more important. Updated with an expanded focus on modern architecture paradigms such as microservices and cloud computing, this practical guide provides techniques for building systems that can handle huge quantities of traffic, data, and demand—without affecting the quality your customers expect. Architects, managers, and directors in engineering and operations organizations will learn how to build applications at scale that run more smoothly and reliably to meet the needs of customers. Learn how scaling affects the availability of your services, why that matters, and how to improve it Dive into a modern service-based application architecture that ensures high availability and reduces the effects of service failures Explore the Single Team Owned Service Architecture paradigm (STOSA)—a model for scaling your development organization in tandem with your application Understand, measure, and mitigate risk in your systems Use the cloud to build highly scalable applications