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MuleSoft Platform Architect's Guide

You're reading from   MuleSoft Platform Architect's Guide A practical guide to using Anypoint Platform's capabilities to architect, deliver, and operate APIs

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781805126188
Length 498 pages
Edition 1st Edition
Concepts
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Authors (2):
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Jim Andrews Jim Andrews
Author Profile Icon Jim Andrews
Jim Andrews
Jitendra Bafna Jitendra Bafna
Author Profile Icon Jitendra Bafna
Jitendra Bafna
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Table of Contents (21) Chapters Close

Preface 1. Chapter 1: What is the MuleSoft Platform? FREE CHAPTER 2. Chapter 2: Platform Foundation Components and the Underlying Architecture 3. Chapter 3: Leveraging Catalyst and the MuleSoft Knowledge Hub 4. Chapter 4: An Introduction to Application Networks 5. Chapter 5: Speeding with Accelerators 6. Chapter 6: Aligning Desired Business Outcomes to Functional Requirements 7. Chapter 7: Microservices, Application Networks, EDA, and API-led Design 8. Chapter 8: Non-Functional Requirements Influence in Shaping the API Architecture 9. Chapter 9: Hassle-free Deployment with Anypoint iPaaS (CloudHub 1.0) 10. Chapter 10: Hassle-Free Deployment with Anypoint iPaaS (CloudHub 2.0) 11. Chapter 11: Containerizing the Runtime Plane with Runtime Fabric 12. Chapter 12: Deploying to Your Own Data Center 13. Chapter 13: Government Cloud and the EU Control Plane – Special Considerations 14. Chapter 14: Functional Monitoring, Alerts, and Operation Monitors 15. Chapter 15: Controlling API Sprawl with Universal API Management 16. Chapter 16: Addressing Non-Functional Requirements – from a Thought to an Operation 17. Chapter 17: Prepare for Success 18. Chapter 18: Tackling Tricky Topics 19. Index 20. Other Books You May Enjoy

API concurrency

The ability of an API to handle multiple requests at the same time is referred to as API concurrency. It is particularly important in a decentralized system, where lots of independent services communicate with one another through APIs. If the system is overloaded without proper concurrent control, it can lead to race conditions where several processes access and manipulate the same data, leading to inconsistent results.

The following are the ways supported to handle concurrency:

  • Multi-threading: This is perhaps the most common way to handle concurrency. Each request is handled by a specific thread so that multiple requests can be processed in parallel. The downside is that it may be resource-intensive to manage many threads.
  • Rate limiting: This is used to control the number of API requests that a client may make during a specified time. This ensures that your API is not overwhelmed with too many requests at once.
  • Queuing: If the number of concurrent...
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