Mulesoft DataWeave is a simple powerful tool to transform data inside a flow. Numerous core operators and functions are already present to perform various operations such as capitalize, camelize, upper, and lower.
For string operations, there are no core functions present to resolve a wildcard. I hope the DataWeave(DWL 1.0) function below helps you to perform a requirement where you want to resolve a wildcard using a set of parameters.
Working with data, there are several scenarios to transform data from input files using the Mule 4 connector.
There are several scenarios for files with special characters or language-based characters.
This article will explain in detail, how to integrate with RabbitMQ in MuleSoft and read messages from a queue.
In this section, I will explain how to install RabbitMQ on Mac, create a new queue and publish messages to the queue using the RabbitMQ portal.
MuleSoft Custom Policies can be layered on top of the implementation of the APIs to provide the governance, security, and visibility required. While the out-of-the-box API management policies cover the majority of use cases, an organization may need to create a custom policy to meet specific business needs.
There is a lot of documentation that shows how to work with MuleSoft custom policies through API manager, however, developing the custom policy and debugging them locally has been always challenging. In this article, I will demonstrate how to develop and test Mule custom policy on your local standalone Mule runtime instances before uploading to the API manager or Exchange for live running APIs.
