Routers in Mule, implement the Message Router pattern described in the seminal work on integration patterns: Enterprise Integration Patterns, Gregor Hohpe and Bobby Woolf. Addison-Wesley Professional; October 20, 2003. They allow you to route a Mule event from one Event Processor to one or many Event Processors.
The Content Enricher is a useful content transformation pattern that elaborates a basic message with information from another system. A typical use case is described in the seminal work on integration patterns: Enterprise Integration Patterns, Gregor Hohpe and Bobby Woolf. Addison-Wesley Professional; October 20, 2003. It describes a scenario where one system may provide a customer ID, but the target system requires the customer name and address. This additional information must be retrieved from another system and combined with the customer ID to form the information required by the target system.
Often times when you are processing data through a flow, you may want to treat certain errors differently than others. For instance, if you are trying to select records from Salesforce, you would want to handle a record not found error differently than an out of memory error. For this reason, MuleSoft allows us to handle errors based on use cases as well as the types of errors that are being thrown.
It is no secret that migrating to Mule 4 from Mule 3 is a challenge. Mule 4 saw the biggest change in the Mule runtime since its inception. However, with this series of “Mule 4 migration made easy” blogs, I will attempt to soothe any pain you might feel while migrating and provide tips and tricks on how to make the best from Mule 4.
In my previous blog post, I discussed the basics of error handling with Mule 4, helped understand what a Mule error is, what the two major error handling scopes in Mule 4 are, as well as how they work. In this post, I will discuss how to take these basic concepts and build them up so that you can implement error handling strategies in your application (and not be completely lost when doing so).
Like many developers and architects who build APIs and integrations, I was on top of the world when I completed the training on Anypoint Platform Development fundamentals (Mule 4); I was now able to take an idea for an API and build, design, deploy, and implement my API in a matter of hours. I now held the shiny key to become a MuleSoft Certified Developer — I just had to pass the MuleSoft Certified Developer –
This is part four of my five-part series documenting high scalability in Mule 4. If you haven’t read part one, Scale your APIs with Mule 4, part two, Reactive programming in Mule 4, and part three, Thread management and auto-tuning in Mule 4, check them out! This post will cover streaming in Mule 4.
My first two posts in this Mule 4 blog series were on scaling your APIs and reactive programming in our newest version of Mule runtime engine. This blog dives into thread management and auto-tuning.
Mule 4 uses reactive programming to enhance scalability so our developers can deliver smooth experiences for their users.
Mule 4 addresses vertical scalability with a radically different design using reactive programming at its core.
