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Distributed .NET with Microsoft Orleans

You're reading from   Distributed .NET with Microsoft Orleans Build robust and highly scalable distributed applications without worrying about complex programming patterns

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Product type Paperback
Published in May 2022
Publisher Packt
ISBN-13 9781801818971
Length 262 pages
Edition 1st Edition
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Authors (2):
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Bhupesh Guptha Muthiyalu Bhupesh Guptha Muthiyalu
Author Profile Icon Bhupesh Guptha Muthiyalu
Bhupesh Guptha Muthiyalu
Suneel Kumar Kunani Suneel Kumar Kunani
Author Profile Icon Suneel Kumar Kunani
Suneel Kumar Kunani
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Table of Contents (17) Chapters Close

Preface 1. Section 1 - Distributed Applications Architecture
2. Chapter 1: An Introduction to Distributed Applications FREE CHAPTER 3. Chapter 2: Cloud Architecture and Patterns for Distributed Applications 4. Section 2 - Working with Microsoft Orleans
5. Chapter 3: Introduction to Microsoft Orleans 6. Chapter 4: Understanding Grains and Silos 7. Chapter 5: Persistence in Grains 8. Chapter 6: Scheduling and Notifying in Orleans 9. Chapter 7: Engineering Fundamentals in Orleans 10. Section 3 - Building Patterns in Orleans
11. Chapter 8: Advanced Concepts in Orleans 12. Chapter 9: Design Patterns in Orleans 13. Section 4 - Hosting and Deploying Orleans Applications to Azure
14. Chapter 10: Deploying an Orleans Application in Azure Kubernetes 15. Chapter 11: Deploying an Orleans Application to Azure App Service 16. Other Books You May Enjoy

Streaming in Orleans

In typical request and response scenarios, a client sends the request to the server and the service does some processing on it and sends a response to the client. The client would be waiting for the response from the service while the service was processing it. In the event of any failures, the client will retry sending the call to the service or will do some other action such as sending an email or raising an alert.

Event stream processing is a popular paradigm for durability and performance in different kinds of applications, such as gaming, IoT, high-frequency trading, or fraud detection.

An event stream processor actively tracks and processes a stream of events in an application so that insights and risks can be identified and appropriate action can be taken. Examples of such interactions are monitoring the production line, event processing from IoT devices, smart patient care in hospitals, monitoring of traffic, and so on.

There are many technologies...

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