Distributed Net With Microsoft Orleans
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Distributed .NET with Microsoft Orleans
Author: Bhupesh Guptha Muthiyalu
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-05-27
Adopt an effortless approach to avoid the hassles of complex concurrency and scaling patterns when building distributed applications in .NET Key Features • Explore the Orleans cross-platform framework for building robust, scalable, and distributed applications • Handle concurrency, fault tolerance, and resource management without complex programming patterns • Work with essential components such as grains and silos to write scalable programs with ease Book Description Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications. Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail. By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure. What you will learn • Get to grips with the different cloud architecture patterns that can be leveraged for building distributed applications • Manage state and build a custom storage provider • Explore Orleans key design patterns and understand when to reuse them • Work with different classes that are created by code generators in the Orleans framework • Write unit tests for Orleans grains and silos and create mocks for different parts of the system • Overcome traditional challenges of latency and scalability while building distributed applications Who this book is for This book is for .NET developers and software architects looking for a simplified guide for creating distributed applications, without worrying about complex programming patterns. Intermediate web developers who want to build highly scalable distributed applications will also find this book useful. A basic understanding of .NET Classic or .NET Core with C# and Azure will be helpful.
The Actor Model in Distributed Computing
"The Actor Model in Distributed Computing" "The Actor Model in Distributed Computing" is a comprehensive and authoritative exploration of one of the most influential paradigms in concurrent and distributed systems. This book meticulously traces the theoretical foundations and evolution of the actor model, contrasting its core concepts—such as encapsulated state and asynchronous messaging—with alternative concurrency approaches like shared memory and process calculi. Through clear exposition, readers are empowered to grasp the model’s intrinsic expressiveness, modularity, and the contexts in which it excels, while becoming aware of its practical limitations. Delving beyond fundamentals, the book offers an in-depth examination of engineering robust actor-based systems. It details essential programming constructs and architectural patterns, from actor creation, supervision, and message queuing, to sophisticated mechanisms for distribution transparency, state migration, and fault tolerance in large-scale deployments. Topics such as scheduling, load balancing, system optimization, and the unique challenges of memory and resource management are handled with both breadth and technical rigor, making the work an invaluable resource for practitioners and architects seeking to maximize reliability and performance. "The Actor Model in Distributed Computing" stands out for its practical guidance and broad ecosystem coverage. Readers will find comparative reviews of leading actor frameworks—including Erlang, Akka, and Orleans—alongside security best practices, formal verification techniques, and recipes for testing and monitoring distributed actor systems. The closing chapters illuminate advanced topics and current research frontiers, like distributed transactions, cloud-native deployments, and the future of actors in edge and serverless computing. With its blend of foundational theory and pragmatic design-oriented insight, this book is essential reading for anyone building next-generation distributed applications.
Transactions on Large-Scale Data- and Knowledge-Centered Systems LIII
Author: Abdelkader Hameurlain
language: en
Publisher: Springer Nature
Release Date: 2023-02-08
The LNCS journal Transactions on Large-scale Data and Knowledge-centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g. computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. This, the 53rd issue of Transactions on Large-scale Data and Knowledge-centered Systems, contains six fully revised selected regular papers. Topics covered include time series management from edge to cloud, segmentation for time series representation, similarity research, semantic similarity in a taxonomy, linked data semantic distance, linguistics-informed natural language processing, graph neural network, protected features, imbalanced data, causal consistency in distributed databases, actor model, and elastic horizontal scalability.