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

This classroom-tested textbook provides an accessible introduction to the design, formal modeling, and analysis of distributed computer systems. The book uses Maude, a rewriting logic-based language and simulation and model checking tool, which offers a simple and intuitive modeling formalism that is suitable for modeling distributed systems in an attractive object-oriented and functional programming style. Topics and features: introduces classical algebraic specification and term rewriting theory, including reasoning about termination, confluence, and equational properties; covers object-oriented modeling of distributed systems using rewriting logic, as well as temporal logic to specify requirements that a system should satisfy; provides a range of examples and case studies from different domains, to help the reader to develop an intuitive understanding of distributed systems and their design challenges; examples include classic distributed systems such as transport protocols, cryptographic protocols, and distributed transactions, leader election, and mutual execution algorithms; contains a wealth of exercises, including larger exercises suitable for course projects, and supplies executable code and supplementary material at an associated website. This self-contained textbook is designed to support undergraduate courses on formal methods and distributed systems, and will prove invaluable to any student seeking a reader-friendly introduction to formal specification, logics and inference systems, and automated model checking techniques.

Future requirements for computing speed, system reliability, and cost-effectiveness entail the development of alternative computers to replace the traditional von Neumann organization. As computing networks come into being, one of the latest dreams is now possible - distributed computing. Distributed computing brings transparent access to as much computer power and data as the user needs for accomplishing any given task - simultaneously achieving high performance and reliability. The subject of distributed computing is diverse, and many researchers are investigating various issues concerning the structure of hardware and the design of distributed software. Distributed System Design defines a distributed system as one that looks to its users like an ordinary system, but runs on a set of autonomous processing elements (PEs) where each PE has a separate physical memory space and the message transmission delay is not negligible. With close cooperation among these PEs, the system supports an arbitrary number of processes and dynamic extensions. Distributed System Design outlines the main motivations for building a distributed system, including: inherently distributed applications performance/cost resource sharing flexibility and extendibility availability and fault tolerance scalability Presenting basic concepts, problems, and possible solutions, this reference serves graduate students in distributed system design as well as computer professionals analyzing and designing distributed/open/parallel systems. Chapters discuss: the scope of distributed computing systems general distributed programming languages and a CSP-like distributed control description language (DCDL) expressing parallelism, interprocess communication and synchronization, and fault-tolerant design two approaches describing a distributed system: the time-space view and the interleaving view mutual exclusion and related issues, including election, bidding, and self-stabilization prevention and detection of deadlock reliability, safety, and security as well as various methods of handling node, communication, Byzantine, and software faults efficient interprocessor communication mechanisms as well as these mechanisms without specific constraints, such as adaptiveness, deadlock-freedom, and fault-tolerance virtual channels and virtual networks load distribution problems synchronization of access to shared data while supporting a high degree of concurrency

Designing Distributed Control Systems presents 80 patterns for designing distributed machine control system software architecture (forestry machinery, mining drills, elevators, etc.). These patterns originate from state-of-the-art systems from market-leading companies, have been tried and tested, and will address typical challenges in the domain, such as long lifecycle, distribution, real-time and fault tolerance. Each pattern describes a separate design problem that needs to be solved. Solutions are provided, with consequences and trade-offs. Each solution will enable piecemeal growth of the design. Finding a solution is easy, as the patterns are divided into categories based on the problem field the pattern tackles. The design process is guided by different aspects of quality, such as performance and extendibility, which are included in the pattern descriptions. The book also contains an example software architecture designed by leading industry experts using the patterns in the book. The example system introduces the reader to the problem domain and demonstrates how the patterns can be used in a practical system design process. The example architecture shows how useful a toolbox the patterns provide for both novices and experts, guiding the system design process from its beginning to the finest details. Designing distributed machine control systems with patterns ensures high quality in the final product. High-quality systems will improve revenue and guarantee customer satisfaction. As market need changes, the desire to produce a quality machine is not only a primary concern, there is also a need for easy maintenance, to improve efficiency and productivity, as well as the growing importance of environmental values; these all impact machine design. The software of work machines needs to be designed with these new requirements in mind. Designing Distributed Control Systems presents patterns to help tackle these challenges. With proven methodologies from the expert author team, they show readers how to improve the quality and efficiency of distributed control systems.

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.

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

Designing a New Class of Distributed Systems closely examines the Distributed Intelligent Managed Element (DIME) Computing Model, a new model for distributed systems, and provides a guide to implementing Distributed Managed Workflows with High Reliability, Availability, Performance and Security. The book also explores the viability of self-optimizing, self-monitoring autonomous DIME-based computing systems. Designing a New Class of Distributed Systems is designed for practitioners as a reference guide for innovative distributed systems design. Researchers working in a related field will also find this book valuable.