This is the fourth edition of "Distributed Systems." We have stayed close to the setup of the third edition, including examples of (part of) existing distributed systems close to where general principles are discussed. For example, we have included material on blockchain systems, and discuss their various components throughout the book. We have, again, used special boxed sections for material that can be skipped at first reading. The text has been thoroughly reviewed, revised, and updated. In particular, all the Python code has been updated to Python3, while at the same time the channel package has been almost completely revised and simplified. Additional material, including coding examples, figures, and slides, are available at www.distributed-systems.net.
You know the basics of Go and are eager to put your knowledge to work. This book is just what you need to apply Go to real-world situations. You'll build a distributed service that's highly available, resilient, and scalable. Along the way you'll master the techniques, tools, and tricks that skilled Go programmers use every day to build quality applications. Level up your Go skills today. Take your Go skills to the next level by learning how to design, develop, and deploy a distributed service. Start from the bare essentials of storage handling, then work your way through networking a client and server, and finally to distributing server instances, deployment, and testing. All this will make coding in your day job or side projects easier, faster, and more fun. Lay out your applications and libraries to be modular and easy to maintain. Build networked, secure clients and servers with gRPC. Monitor your applications with metrics, logs, and traces to make them debuggable and reliable. Test and benchmark your applications to ensure they're correct and fast. Build your own distributed services with service discovery and consensus. Write CLIs to configure your applications. Deploy applications to the cloud with Kubernetes and manage them with your own Kubernetes Operator. Dive into writing Go and join the hundreds of thousands who are using it to build software for the real world. What You Need: Go 1.11 and Kubernetes 1.12.
The Complete Guide to Optimizing Systems Performance Written by the winner of the 2013 LISA Award for Outstanding Achievement in System Administration Large-scale enterprise, cloud, and virtualized computing systems have introduced serious performance challenges. Now, internationally renowned performance expert Brendan Gregg has brought together proven methodologies, tools, and metrics for analyzing and tuning even the most complex environments. Systems Performance: Enterprise and the Cloud focuses on Linux(R) and Unix(R) performance, while illuminating performance issues that are relevant to all operating systems. You'll gain deep insight into how systems work and perform, and learn methodologies for analyzing and improving system and application performance. Gregg presents examples from bare-metal systems and virtualized cloud tenants running Linux-based Ubuntu(R), Fedora(R), CentOS, and the illumos-based Joyent(R) SmartOS(TM) and OmniTI OmniOS(R). He systematically covers modern systems performance, including the "traditional" analysis of CPUs, memory, disks, and networks, and new areas including cloud computing and dynamic tracing. This book also helps you identify and fix the "unknown unknowns" of complex performance: bottlenecks that emerge from elements and interactions you were not aware of. The text concludes with a detailed case study, showing how a real cloud customer issue was analyzed from start to finish. Coverage includes - Modern performance analysis and tuning: terminology, concepts, models, methods, and techniques - Dynamic tracing techniques and tools, including examples of DTrace, SystemTap, and perf - Kernel internals: uncovering what the OS is doing - Using system observability tools, interfaces, and frameworks - Understanding and monitoring application performance - Optimizing CPUs: processors, cores, hardware threads, caches, interconnects, and kernel scheduling - Memory optimization: virtual memory, paging, swapping, memory architectures, busses, address spaces, and allocators - File system I/O, including caching - Storage devices/controllers, disk I/O workloads, RAID, and kernel I/O - Network-related performance issues: protocols, sockets, interfaces, and physical connections - Performance implications of OS and hardware-based virtualization, and new issues encountered with cloud computing - Benchmarking: getting accurate results and avoiding common mistakes This guide is indispensable for anyone who operates enterprise or cloud environments: system, network, database, and web admins; developers; and other professionals. For students and others new to optimization, it also provides exercises reflecting Gregg's extensive instructional experience.
"This book is organized around three concepts fundamental to OS construction: virtualization (of CPU and memory), concurrency (locks and condition variables), and persistence (disks, RAIDS, and file systems"--Back cover.
This second edition of Distributed Systems, Principles & Paradigms, covers the principles, advanced concepts, and technologies of distributed systems in detail, including: communication, replication, fault tolerance, and security. Intended for use in a senior/graduate level distributed systems course or by professionals, this text systematically shows how distributed systems are designed and implemented in real systems.
What Is Distributed Ledger A distributed ledger is a database that is consensually shared and synchronized across multiple sites, institutions, or geographies, accessible by multiple people. It allows transactions to have public "witnesses." The participant at each node of the network can access the recordings shared across that network and can own an identical copy of it. Any changes, or additions, made to the ledger, are reflected, and copied to all participants in a matter of seconds or minutes. Blockchain is using the underlying technology of distributed ledgers. Bitcoin is using the underlying technology of Blockchain. Blockchain is a type of distributed ledger used by bitcoin. Blockchain is the latest buzz words in the market. Bitcoin is great, but the potential of the underlying technology is immense. Something that started as an evolution is soon going to cause a revolution. Investors are cashing in huge amount because they understand the fortune of this ingenious technology is very bright. Industry experts and tech enthusiasts are producing blockchain-based products every next day. So, wait not, and get industry-ready with this book which will describe distributed ledger in depth. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Distributed Ledger Chapter 2: Hyperledger Chapter 3: Confidential Consortium Framework Chapter 4: Eventual Consistency Chapter 5: ACID Chapter 6: CAP Theorem Chapter 7: Concurrency Control Chapter 8: Jakarta Transactions Chapter 9: Transactional NTFS Chapter 10: Two Phase Commit Protocol Chapter 11: CRUD Chapter 12: OSI Model (II) Answering the public top questions about distributed ledger. (III) Real world examples for the usage of distributed ledger in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technology in each industry to have 360-degree full understanding of distributed ledger' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of distributed ledger.
This book constitutes the proceedings of the 20th IFIP International Conference on Distributed Applications and Interoperable Systems, DAIS 2020, which was supposed to be held in Valletta, Malta, in June 2020, as part of the 15th International Federated Conference on Distributed Computing Techniques, DisCoTec 2020. The conference was held virtually due to the COVID-19 pandemic. The 10 full papers presented together with 1 short paper and 1 invited paper were carefully reviewed and selected from 17 submissions. The papers addressed challenges in multiple application areas, such as privacy and security, cloud and systems, fault-tolerance and reproducibility, machine learning for systems, and distributed algorithms.
The system design interview is considered to be the most complex and most difficult technical job interview by many. Those questions are intimidating, but don't worry. It's just that nobody has taken the time to prepare you systematically. We take the time. We go slow. We draw lots of diagrams and use lots of examples. You'll learn step-by-step, one question at a time.Don't miss out.What's inside?- An insider's take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 16 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.
Now that there’s software in everything, how can you make anything secure? Understand how to engineer dependable systems with this newly updated classic In Security Engineering: A Guide to Building Dependable Distributed Systems, Third Edition Cambridge University professor Ross Anderson updates his classic textbook and teaches readers how to design, implement, and test systems to withstand both error and attack. This book became a best-seller in 2001 and helped establish the discipline of security engineering. By the second edition in 2008, underground dark markets had let the bad guys specialize and scale up; attacks were increasingly on users rather than on technology. The book repeated its success by showing how security engineers can focus on usability. Now the third edition brings it up to date for 2020. As people now go online from phones more than laptops, most servers are in the cloud, online advertising drives the Internet and social networks have taken over much human interaction, many patterns of crime and abuse are the same, but the methods have evolved. Ross Anderson explores what security engineering means in 2020, including: How the basic elements of cryptography, protocols, and access control translate to the new world of phones, cloud services, social media and the Internet of Things Who the attackers are – from nation states and business competitors through criminal gangs to stalkers and playground bullies What they do – from phishing and carding through SIM swapping and software exploits to DDoS and fake news Security psychology, from privacy through ease-of-use to deception The economics of security and dependability – why companies build vulnerable systems and governments look the other way How dozens of industries went online – well or badly How to manage security and safety engineering in a world of agile development – from reliability engineering to DevSecOps The third edition of Security Engineering ends with a grand challenge: sustainable security. As we build ever more software and connectivity into safety-critical durable goods like cars and medical devices, how do we design systems we can maintain and defend for decades? Or will everything in the world need monthly software upgrades, and become unsafe once they stop?
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you’ll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition—updated for Cassandra 4.0—provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra’s nonrelational design, with special attention to data modeling. If you’re a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra’s speed and flexibility. Understand Cassandra’s distributed and decentralized structure Use the Cassandra Query Language (CQL) and cqlsh—the CQL shell Create a working data model and compare it with an equivalent relational model Develop sample applications using client drivers for languages including Java, Python, and Node.js Explore cluster topology and learn how nodes exchange data
