Patterns of Distributed Systems
- Length: 390 pages
- Edition: 1
- Language: English
- Publisher: Addison-Wesley Professional
- Publication Date: 2023-09-25
- ISBN-10: 0138221987
- ISBN-13: 9780138221980
- Sales Rank: #0 (See Top 100 Books)
get link Learn How to Better Understand Distributed System Design and Solve Common Problems
https://aalamsalon.com/m5r8ajaswo Enterprises today rely on a range of distributed software handling data storage, messaging, system management, and compute capability. Distributed system designs need to be implemented in some programming language, and there are common problems that these implementations need to solve. These problems have common recurring solutions. A patterns approach is very suitable to describe these implementation aspects.
https://reggaeportugal.com/b0vaca8 Patterns by nature are generic enough to cover a broad range of products from cloud services like Amazon S3 to message brokers like Apache Kafka to infrastructure frameworks like Kubernetes to databases like MongoDB or Actor frameworks like Akka. At the same time the pattern structure is specific enough to be able to show real code. The beauty of this approach is that even if the code structure is shown in one programming language (Java in this case), the structure applies to many other programming languages. Patterns also form a “system of names,” with each name having specific meaning in terms of the code structure.
https://kirkmanandjourdain.com/n6b978i The set of patterns presented in Patterns of Distributed Systems will be useful to all developers–even if they are not directly involved in building these kinds of systems, and mostly use them as a black box. Learning these patterns will help readers develop a deeper understanding of the challenges presented by distributed systems and will also help them choose appropriate cloud services and products. Coverage includes Patterns of Data Replication, Patterns of Data Partitioning, Patterns of Distributed Time, Patterns of Cluster Management, and Patterns of Communication Between Nodes.
https://lavozdelascostureras.com/s5lkfafqf0 The patterns approach used here will help you
- Learn what a distributed system is and why distributed systems are needed
- Understand the implementation of a wide range of systems such as databases, in-memory data grids, message brokers, and various cloud services
- Prepare you to confidently traverse through open source codebases and discover how patterns and solutions map to real world systems like Kafka and Kubernetes
Tramadol Online Cheapest Cover Page Title Page Contents Table of Contents Part I: Narratives Chapter 1. Why Distribute? The four fundamental resources Queuing and its impact on system throughput Partitioning - Divide and Conquer Chapter 2. Overview of the Patterns Keeping data resilient on a single server Competing Updates Dealing with the leader failing Multiple failures need a Generation Clock Log entries cannot be committed until they are accepted by a Quorum Followers commit based on a High-Water Mark Leaders use a series of queues to remain responsive to many clients Followers can handle read requests to reduce load on the leader A large amount of data can be partitioned over multiple nodes Partitions can be replicated for resilience Two phases are needed to maintain consistency across partitions In a distributed system, time is complicated A Consistent Core can manage the membership of a data cluster Gossip Dissemination can be used to manage a cluster without a centralized controller Part II: Patterns of Data Replication Chapter 3. Write-Ahead Log Problem Solution Examples Chapter 4. Segmented Log Problem Solution Examples Chapter 5. Low-Water Mark Problem Solution Examples Chapter 6. Leader and Followers Problem Solution Examples Chapter 7. HeartBeat Problem Solution Examples Chapter 8. Paxos Problem Solution Examples Chapter 9. Replicated Log Problem Solution Examples Chapter 10. Quorum Problem Solution Examples Chapter 11. Generation Clock Problem Solution Examples Chapter 12. High-Water Mark Problem Solution Examples Chapter 13. Singular Update Queue Problem Solution Examples Chapter 14. Request Waiting List Problem Solution Examples Chapter 15. Idempotent Receiver Problem Solution Examples Chapter 16. Follower Reads Problem Solution Examples Chapter 17. Versioned Value Problem Solution Examples Chapter 18. Version Vector Problem Solution Examples Part III: Patterns of Data Partitioning Chapter 19. Fixed Partitions Problem Solution Examples Chapter 20. Key-Range Partitions Problem Solution Examples Chapter 21. Two Phase Commit Problem Solution Examples Part IV: Patterns of Distributed Time Chapter 22. Lamport Clock Problem Solution Examples Chapter 23. Hybrid Clock Problem Solution Examples Chapter 24. Clock-Bound Wait Problem Solution Examples Part V: Patterns of Cluster Management Chapter 25. Consistent Core Problem Solution Examples Chapter 26. Lease Problem Solution Examples Chapter 27. State Watch Problem Solution Examples Chapter 28. Gossip Dissemination Problem Solution Examples Chapter 29. Emergent Leader Problem Solution Examples Part VI: Patterns of communication between nodes Chapter 30. Single Socket Channel Problem Solution Examples Chapter 31. Request Batch Problem Solution Examples Chapter 32. Request Pipeline Problem Solution Examples Bibliography
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