Mastering Distributed Tracing
Mastering Distributed Tracing

Author: Yuri Shkuro

Publisher: Packt Publishing Ltd

Published: 2019-02-28

Total Pages: 445

ISBN-13: 1788627598

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Understand how to apply distributed tracing to microservices-based architectures Key FeaturesA thorough conceptual introduction to distributed tracingAn exploration of the most important open standards in the spaceA how-to guide for code instrumentation and operating a tracing infrastructureBook Description Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems. What you will learnHow to get started with using a distributed tracing systemHow to get the most value out of end-to-end tracingLearn about open standards in the spaceLearn about code instrumentation and operating a tracing infrastructureLearn where distributed tracing fits into microservices as a core functionWho this book is for Any developer interested in testing large systems will find this book very revealing and in places, surprising. Every microservice architect and developer should have an insight into distributed tracing, and the book will help them on their way. System administrators with some development skills will also benefit. No particular programming language skills are required, although an ability to read Java, while non-essential, will help with the core chapters.

Mastering Distributed Algorithms
Mastering Distributed Algorithms

Author: Roger Wattenhofer

Publisher:

Published: 2020-03-23

Total Pages: 262

ISBN-13:

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About the book: The Internet is a distributed system, but so are wireless communication, cloud or parallel computing, multi-core systems, mobile networks. Also an ant colony, a brain, or even the human society can be modeled as distributed systems. In this book we will be highlighting common themes and techniques. In particular, we study some of the fundamental issues underlying the design of distributed systems, for example, communication, coordination, fault-tolerance, locality, parallelism, symmetry breaking, synchronization, and uncertainty.About the author: Roger Wattenhofer is a professor at ETH Zurich. Before joining ETH Zurich, he was at Brown University and Microsoft Research. His research interests include fault-tolerant distributed systems, efficient network algorithms, and cryptocurrencies such as Bitcoin. He has published more than 300 scientific articles. In 2017, he published the book Blockchain Science.

Distributed Algorithms
Distributed Algorithms

Author: Wan Fokkink

Publisher: MIT Press

Published: 2013-12-06

Total Pages: 242

ISBN-13: 0262026775

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A comprehensive guide to distributed algorithms that emphasizes examples and exercises rather than mathematical argumentation.

Mastering Distributed Computing
Mastering Distributed Computing

Author: Cybellium Ltd

Publisher: Cybellium Ltd

Published:

Total Pages: 179

ISBN-13:

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Uncover the Art of Seamless Distributed Computing with "Mastering Distributed Computing" In the dynamic realm of modern computing, the ability to harness the power of distributed systems is paramount. "Mastering Distributed Computing" is your definitive guide to mastering the art of seamlessly orchestrating distributed resources for optimal performance and scalability. Whether you're an experienced software engineer or a newcomer to the world of distributed computing, this book equips you with the knowledge and skills needed to navigate the intricacies of distributed systems. About the Book: "Mastering Distributed Computing" takes you on an enlightening journey through the intricacies of distributed computing, from foundational concepts to advanced techniques. From distributed architectures to consensus algorithms, this book covers it all. Each chapter is meticulously designed to provide both a deep understanding of the concepts and practical applications in real-world scenarios. Key Features: · Foundational Principles: Build a strong foundation by understanding the core principles of distributed systems, including scalability, fault tolerance, and data consistency. · Distributed Architectures: Explore a range of distributed architectures, including client-server, peer-to-peer, microservices, and serverless, understanding their strengths and applications. · Consistency and Replication: Dive into the complexities of data consistency and replication strategies, including eventual consistency, strong consistency, and distributed databases. · Distributed Algorithms: Master fundamental distributed algorithms, such as leader election, distributed locking, and distributed transactions, for coordinating actions across nodes. · Scaling Strategies: Discover strategies for scaling distributed systems horizontally and vertically, ensuring optimal performance as workloads grow. · Fault Tolerance: Understand mechanisms for building fault-tolerant systems, including redundancy, replication, and failure detection and recovery. · Real-World Use Cases: Gain insights from real-world examples spanning industries, from finance and e-commerce to social media and beyond. · Cloud and Edge Computing: Explore the role of distributed computing in cloud environments and edge computing scenarios, and their impact on modern applications. · Security and Privacy: Explore best practices for securing distributed systems, data encryption, access control, and compliance. Who This Book Is For: "Mastering Distributed Computing" is designed for software engineers, architects, developers, and anyone passionate about effective distributed system design. Whether you're seeking to enhance your skills or embark on a journey toward becoming a distributed computing expert, this book provides the insights and tools to navigate the complexities of distributed systems. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Mastering Cloud Computing
Mastering Cloud Computing

Author: Rajkumar Buyya

Publisher: Newnes

Published: 2013-04-05

Total Pages: 469

ISBN-13: 0124095399

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Mastering Cloud Computing is designed for undergraduate students learning to develop cloud computing applications. Tomorrow's applications won't live on a single computer but will be deployed from and reside on a virtual server, accessible anywhere, any time. Tomorrow's application developers need to understand the requirements of building apps for these virtual systems, including concurrent programming, high-performance computing, and data-intensive systems. The book introduces the principles of distributed and parallel computing underlying cloud architectures and specifically focuses on virtualization, thread programming, task programming, and map-reduce programming. There are examples demonstrating all of these and more, with exercises and labs throughout. - Explains how to make design choices and tradeoffs to consider when building applications to run in a virtual cloud environment - Real-world case studies include scientific, business, and energy-efficiency considerations

Distributed Computing with Go
Distributed Computing with Go

Author: V.N. Nikhil Anurag

Publisher: Packt Publishing Ltd

Published: 2018-02-28

Total Pages: 241

ISBN-13: 1787127702

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A tutorial leading the aspiring Go developer to full mastery of Golang's distributed features. Key Features This book provides enough concurrency theory to give you a contextual understanding of Go concurrency It gives weight to synchronous and asynchronous data streams in Golang web applications It makes Goroutines and Channels completely familiar and natural to Go developers Book Description Distributed Computing with Go gives developers with a good idea how basic Go development works the tools to fulfill the true potential of Golang development in a world of concurrent web and cloud applications. Nikhil starts out by setting up a professional Go development environment. Then you’ll learn the basic concepts and practices of Golang concurrent and parallel development. You’ll find out in the new few chapters how to balance resources and data with REST and standard web approaches while keeping concurrency in mind. Most Go applications these days will run in a data center or on the cloud, which is a condition upon which the next chapter depends. There, you’ll expand your skills considerably by writing a distributed document indexing system during the next two chapters. This system has to balance a large corpus of documents with considerable analytical demands. Another use case is the way in which a web application written in Go can be consciously redesigned to take distributed features into account. The chapter is rather interesting for Go developers who have to migrate existing Go applications to computationally and memory-intensive environments. The final chapter relates to the rather onerous task of testing parallel and distributed applications, something that is not usually taught in standard computer science curricula. What you will learn Gain proficiency with concurrency and parallelism in Go Learn how to test your application using Go's standard library Learn industry best practices with technologies such as REST, OpenAPI, Docker, and so on Design and build a distributed search engine Learn strategies on how to design a system for web scale Who this book is for This book is for developers who are familiar with the Golang syntax and have a good idea of how basic Go development works. It would be advantageous if you have been through a web application product cycle, although it’s not necessary.

Distributed Algorithms for Message-Passing Systems
Distributed Algorithms for Message-Passing Systems

Author: Michel Raynal

Publisher: Springer Science & Business Media

Published: 2013-06-29

Total Pages: 518

ISBN-13: 3642381235

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Distributed computing is at the heart of many applications. It arises as soon as one has to solve a problem in terms of entities -- such as processes, peers, processors, nodes, or agents -- that individually have only a partial knowledge of the many input parameters associated with the problem. In particular each entity cooperating towards the common goal cannot have an instantaneous knowledge of the current state of the other entities. Whereas parallel computing is mainly concerned with 'efficiency', and real-time computing is mainly concerned with 'on-time computing', distributed computing is mainly concerned with 'mastering uncertainty' created by issues such as the multiplicity of control flows, asynchronous communication, unstable behaviors, mobility, and dynamicity. While some distributed algorithms consist of a few lines only, their behavior can be difficult to understand and their properties hard to state and prove. The aim of this book is to present in a comprehensive way the basic notions, concepts, and algorithms of distributed computing when the distributed entities cooperate by sending and receiving messages on top of an asynchronous network. The book is composed of seventeen chapters structured into six parts: distributed graph algorithms, in particular what makes them different from sequential or parallel algorithms; logical time and global states, the core of the book; mutual exclusion and resource allocation; high-level communication abstractions; distributed detection of properties; and distributed shared memory. The author establishes clear objectives per chapter and the content is supported throughout with illustrative examples, summaries, exercises, and annotated bibliographies. This book constitutes an introduction to distributed computing and is suitable for advanced undergraduate students or graduate students in computer science and computer engineering, graduate students in mathematics interested in distributed computing, and practitioners and engineers involved in the design and implementation of distributed applications. The reader should have a basic knowledge of algorithms and operating systems.

Distributed Computing with Python
Distributed Computing with Python

Author: Francesco Pierfederici

Publisher: Packt Publishing Ltd

Published: 2016-04-12

Total Pages: 171

ISBN-13: 1785887041

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Harness the power of multiple computers using Python through this fast-paced informative guide About This Book You'll learn to write data processing programs in Python that are highly available, reliable, and fault tolerant Make use of Amazon Web Services along with Python to establish a powerful remote computation system Train Python to handle data-intensive and resource hungry applications Who This Book Is For This book is for Python developers who have developed Python programs for data processing and now want to learn how to write fast, efficient programs that perform CPU-intensive data processing tasks. What You Will Learn Get an introduction to parallel and distributed computing See synchronous and asynchronous programming Explore parallelism in Python Distributed application with Celery Python in the Cloud Python on an HPC cluster Test and debug distributed applications In Detail CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications. This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more. Style and Approach This example based, step-by-step guide will show you how to make the best of your hardware configuration using Python for distributing applications.

Distributed Systems for System Architects
Distributed Systems for System Architects

Author: Paulo Veríssimo

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 636

ISBN-13: 1461516633

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The primary audience for this book are advanced undergraduate students and graduate students. Computer architecture, as it happened in other fields such as electronics, evolved from the small to the large, that is, it left the realm of low-level hardware constructs, and gained new dimensions, as distributed systems became the keyword for system implementation. As such, the system architect, today, assembles pieces of hardware that are at least as large as a computer or a network router or a LAN hub, and assigns pieces of software that are self-contained, such as client or server programs, Java applets or pro tocol modules, to those hardware components. The freedom she/he now has, is tremendously challenging. The problems alas, have increased too. What was before mastered and tested carefully before a fully-fledged mainframe or a closely-coupled computer cluster came out on the market, is today left to the responsibility of computer engineers and scientists invested in the role of system architects, who fulfil this role on behalf of software vendors and in tegrators, add-value system developers, R&D institutes, and final users. As system complexity, size and diversity grow, so increases the probability of in consistency, unreliability, non responsiveness and insecurity, not to mention the management overhead. What System Architects Need to Know The insight such an architect must have includes but goes well beyond, the functional properties of distributed systems.