Patterns of Distributed Systems
Enterprises today rely on a range of distributed software handling data storage,messaging, system management, and compute capability.
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Patterns of Distributed Systems
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. 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. 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.
Features:
- Review the building blocks of consensus algorithms, like Paxo’s and Raft, for ensuring replica consistency in distributed systems
- Understand the use of logical timestamps in databases, a fundamental concept for data versioning
- Explore commonly used partitioning schemes, with an in-depth look at the intricacies of two-phase-commit protocol
- Analyze mechanisms used in implementing cluster coordination tasks, such as group membership, failure detection, and enabling robust cluster coordination
- Learn techniques for establishing effective network communication between cluster nodes.
- Along with enterprise architects and data architects, software developers working with cloud services such as Amazon S3, Amazon EKS, and Azure Cosmos DB or GCP Cloud Spanner will find this set of patterns to be indispensable.
| Book | |
|---|---|
| Author | Joshi |
| Pages | 456 |
| Year | 2024 |
| ISBN | 9789361590528 |
| Publisher | Pearson |
| Language | English |
| Uncategorized | |
| Edition | 1/e |
| Weight | 550 g |
| Dimensions | 23.5 x 17.2 x 1.8 cm |
| Binding | Paperback |