DataWeave is a powerful language, and the possibilities of what you can do with it are infinite.
In this blog post, I am going to show you how to select specific data inside a series of specified XML tags.
For example, in this case we want to encrypt data inside sensitive XML tags such as an SSN, a credit card number, etc.
We define an array with the XML tags to be encrypted named keyToEncrypt (we are encrypting just the contents, not the whole line including the tag)
Mule ESB offers an amazing out-of-the-box integration which easily integrates with ActiveMQ. There is a plethora of examples on the internet that will show how to use ActiveMQ with Mule. But here we will explore how to use a filter with ActiveMQ and Mule that will help us picking up the right JMS messages we need.
When you’re designing an API, you don’t just want to build an API. You want to design and build an API with a long life that your users will love. An API that is carefully created to be extendable and flexible, and will save your users time, money and energy in the long run. To design and build the perfect API, you’ll need to follow some best practices. While some of these may seem a little painful or like they just create more work, you’ll find that by adhering to these guidelines you will not only create a better API, but save a lot of time and money.
If you’re a Mule user, there’s a good chance that you’re using Maven to automate building and testing of your applications. We’re happy to announce Mule Maven Plugin 2.0, to help you automate your deployment and integration tests. This plugin will help you no matter where do you want it to run: CloudHub, a local Standalone server, Anypoint Runtime Manager, a local cluster or using the Mule Agent.
We are happy to announce the September ’15 release of the Salesforce Analytics Cloud Connector v2.0.0. In this blog post, I will be covering some of the important features of the connector as well as walking you through the technicalities of ingesting data into Salesforce Wave Analytics Cloud by leveraging features within Anypoint Platform.
Benefits of using the Salesforce Analytics Cloud Connector
In order to connect assets to audiences with speed and scale, you need a powerful data transformation tool. That tool should be able to integrate in real time using APIs, do batch tasks such as data ingestion or synchronization and handle a variety of data sources – from JSON to EDI to XML.
Have you ever wanted to learn best practices from MuleSoft’s technical experts? Are you an architect, developer, or manager looking to implement your first MuleSoft use case? Want to experience a one-of-a-kind integration workshop AND have tasty cocktails?
Now is your chance.
In the Getting Started with DataWeave: Part 1, we introduced you to DataWeave and its canonical format, the result of every expression you execute in the language. We now continue to explore our new transformation engine, aiming to give you enough grounding to tackle real-world use-cases.
As we did in Part 1, we will continue to show the results of each expression in the DataWeave canonical format.
This series is now complete here:
Ever wanted to get certified on our Anypoint Platform, but discovered that you didn’t have the training?
We’d like to introduce MuleSoft.U: self-study, public, FREE certification courses that will enable developers to learn core MuleSoft skills. At a significant cost per seat for a public class, instructor-led training is unattainable for most independent developers. With MuleSoft.U, independent developers can get up and running in no time. In our first course, Mulesoft.U Developer Essentials, students will learn:
- How to use Anypoint Studio to build integration applications to connect to SaaS and on-premise applications and data.
- How to use the Anypoint Platform for APIs to define APIs with RAML and then implementing them as web services using Anypoint Studio and APIkit.
- Deploying and running applications on CloudHub and/or Mule ESB Enterprise.
This is a great resource for independent developers, and any partner and customer developers who prefer the multi-week schedule are welcome to enroll as well. The first course begins on May 20, so register today!
Handling endpoints with disparate speed when the platform is in the cloud
A fairly common integration requirement is to accumulate data coming in real-time or near real-time, hold and consolidate the records, then send the transformed messages to another system on a fixed schedule (e.g. daily etc.) for business reasons, especially if the endpoints are legacy systems. For on-premises integration platforms, this use case is rather straightforward to implement. For cloud-based integration platforms though, which are generally geared toward real-time processing and lack access to local file storage, this requirement does seem to pose some technical challenges. Fortunately for CloudHub, with the built-in persistent queue feature and the Mule Requester Module, the implementation is as easy as doing it with legacy on-premises platforms.
Fast and Slow can play nice together