Mule Kernel 4 – Anypoint Studio

Mule Kernel 4 – Anypoint Studio

In the last article I have described my attempts with writing Mule apps in IntelliJ for Kernel edition. With no luck. Here I will focus on writing a simple application in environment that we should know pretty well … Anypoint Studio. After that I will deploy this application on Kernel application server to test how it works. If you are interested with basic information’s about Mule Kernel 4 look at this article where I have revealed some basic news.

Reuse driven by DataType

Raml 1.0 introduces new concept called DataType.  This fragment is used to declare type in a separate yaml file. This is not just a simplification of JSON schema to conform raml/yaml. It also brings simple improvements and syntax sugar that allows to write types in more concise form. And therefore more readable. In this article we will look at how to define own data types and reuse them in API and its implementation

Error Handling simplified – Try Scope

Errors occurs all the time. All you can do is to implement error handling. In this article I will describe how to use introduced layer of abstraction in exceptions area. Prior to Mule 4, developer only could access raw Java exception as Mule is a Java based ESB. This lead to situation where you, as a developer, needed analyse documentation to find exact exception that you would like to handle. Now an Error concept was introduced.

DataWeave – Tip #3

DataWeave – Tip #3

I have already presented how to call Java code using messages processors with the newest Java Module for Mule 4.x. For earlier mule’s version Entry Point Resolvers were used to invoke custom Java code. However for scenarios when we would like to use custom code in DataWeave, for transformations, another approach is needed. Approach presented in this article will be more concise comparing to using message processors. It was highly extended comparing to possibilities of Mule 3.x version. Mule 3 allowed to invoke static methods. In contract Mule 4 not only permits to call static methods but also instantiate classes and access its instance attributes.

DataWeave – Tip #2

DataWeave – Tip #2

Tip number 2 is about converting decimal number into integer one. This may seem tricky at first. You may say that we do not need to do anything special and DataWeave engine will handle it underneath. However there is a nuance that you should be aware of. In transformation to XML this may not actually works. This tip is primary dedicated to DataWeave 1.0 as in DataWeave 2.0 this does not occur.