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MuleSoft Platform Architect's Guide

MuleSoft Platform Architect's Guide

By : Jitendra Bafna, Jim Andrews
5 (8)
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MuleSoft Platform Architect's Guide

MuleSoft Platform Architect's Guide

5 (8)
By: Jitendra Bafna, Jim Andrews

Overview of this book

We’re living in the era of digital transformation, where organizations rely on APIs to enable innovation within the business and IT teams are asked to continue doing more with less. Written by Jim Andrews, a Mulesoft Evangelist, and Jitendra Bafna, a Senior Solution Architect with expertise in setting up Mulesoft, this book will help you deliver a robust, secure, and flexible enterprise API platform, supporting any required business outcome. You’ll start by exploring Anypoint Platform’s architecture and its capabilities for modern integration before learning how to align business outcomes with functional requirements and how non-functional requirements shape the architecture. You'll also find out how to leverage Catalyst and Accelerators for efficient development. You'll get to grips with hassle-free API deployment and hosting in CloudHub 1.0/2.0, Runtime Fabric Manager, and hybrid environments and familiarize yourself with advanced operating and monitoring techniques with API Manager and Anypoint Monitoring. The final chapters will equip you with best practices for tackling complex topics and preparing for the MuleSoft Certified Platform Architect exam. By the end of this book, you’ll understand Anypoint Platform’s capabilities and be able to architect solutions that deliver the desired business outcomes.
Table of Contents (21 chapters)
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The Competing Consumers pattern

Multiple consumers from the same channel can process messages in parallel thanks to the Competing Consumers pattern. When multiple consumers of the same pool instance need to process several small tasks in parallel and asynchronously, this pattern comes in handy.

In a normal scenario, the traffic coming to the message broker from the publisher is low, and the consumer can process messages at the rate at which they come from the publisher, as shown in Figure 7.7.

Figure 7.7 - Competing Consumers pattern for low traffic

Figure 7.7 - Competing Consumers pattern for low traffic

There might be a scenario where the ingress traffic increases, such as when publishers start sending more messages to the queue or the number of publishers increases. In this case, the rate at which messages are published to the queue is faster than that at which they are consumed.

If this happens, we can increase the number of consumers listening to a message stream and allow more than one consumer per...

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