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Embracing Microservices Design

You're reading from   Embracing Microservices Design A practical guide to revealing anti-patterns and architectural pitfalls to avoid microservices fallacies

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Product type Paperback
Published in Oct 2021
Publisher Packt
ISBN-13 9781801818384
Length 306 pages
Edition 1st Edition
Concepts
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Authors (3):
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Ovais Mehboob Ahmed Khan Ovais Mehboob Ahmed Khan
Author Profile Icon Ovais Mehboob Ahmed Khan
Ovais Mehboob Ahmed Khan
Timothy Oleson Timothy Oleson
Author Profile Icon Timothy Oleson
Timothy Oleson
Nabil Siddiqui Nabil Siddiqui
Author Profile Icon Nabil Siddiqui
Nabil Siddiqui
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: Overview of Microservices, Design, and Architecture Pitfalls
2. Chapter 1: Setting Up Your Mindset for a Microservices Endeavor FREE CHAPTER 3. Chapter 2: Failing to Understand the Role of DDD 4. Chapter 3: Microservices Architecture Pitfalls 5. Chapter 4: Keeping the Replatforming Brownfield Applications Trivial 6. Section 2: Overview of Data Design Pitfalls, Communication, and Cross-Cutting Concerns
7. Chapter 5: Data Design Pitfalls 8. Chapter 6: Communication Pitfalls and Prevention 9. Chapter 7: Cross-Cutting Concerns 10. Section 3: Testing Pitfalls and Evaluating Microservices Architecture
11. Chapter 8: Deployment Pitfalls 12. Chapter 9: Skipping Testing 13. Chapter 10: Evaluating Microservices Architecture 14. Assessments 15. Other Books You May Enjoy

Geode pattern

The geode pattern should be used when your applications have users distributed over a wide area and you want to deliver a highly scalable solution. The geode pattern entails distributing a set of backend services over several geographical nodes, each of which can handle any request from any client in any location. When building scalable solutions, data scaling is as important as application scaling. Many companies consider scaling out their frontend apps and sharing a single instance of the data that's been deployed to a central remote location. As a canonical practice, data should be closer to where the application is deployed. The geode pattern improves latency and performance by distributing the traffic based on the shortest path to the closest geode, where each geode is behind the load balancer, such as Azure Front Door or Traffic Manager.

The key difference between the geode pattern and deployment stamps is that with deployment stamps, the data can be fragmented...

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