Mule Clustering is the easiest way to transparently synchronize state across Mule applications in a single data center. Mule Clustering, however, assumes that the Mule nodes are “close” to each other , typically on the same network, in terms of network topology.   This allows Mule applications to be developed independently from the underlying cluster technology and not to explicitly account for scenarios like network latency or cluster partitioning.

These assumptions aren’t as sound when dealing with multi data center deployments.  

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Working with JPA managed entities in Mule applications can be difficult.  Since the JPA session is not propagated between message processors, transformers are typically needed to produce an entity from a message’s payload, pass it to a component for processing, then serialize it back to an un-proxied representation for further processing.

Transactions have been complicated too.  Its difficult to coordinate a transaction between multiple components that are operating with JPA entity payloads.  Finally the lack of support for JPA queries makes it difficult to  load objects without working with raw SQL and the JDBC transport.

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Apache Cassandra is a column-based, distributed NoSQL database.  Until recently the only way to interact with Cassandra databases from Mule was to reuse one of the existing Java clients, like Hector or Astyanax, in a component.  Mule’s Cassandra DB Module now provides message processors to insert, update, query and delete data in Cassandra.

To show off some of the features of the Cassandra module I’ll show how to implement a simple account management API.

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You want to get more done in 2013 so you’re going to need to switch from synchronous to asynchronous processing to do more with the same resources.  Mule started life as an asynchronous message engine and has a lot of capabilities and optimisations built in for processing data concurrently. To help you understand asynchronous processing in Mule we have created this cheat sheet that will help you understand the basics.  

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One of our New Year resolutions is to create more content around specific subject areas. The aim of MuleSoft Blueprints is to provide a complete guide on a specific topic in a way that can be easily read and kept for reference.

To get you started we have a preview of the Load Balancing Mule for Availability and Scalability. This blueprint will introduce the necessary concepts and show how to achieve availability and scale with JMS,

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Just a quick one today since you’re probably busy getting ready for the New Year (or clearing out your bunker after the world didn’t end on Christmas Eve as they Mayans predicated).  Either way we recommend that you go download and print the Mule 3 Refcard from DZone.  If you haven’t seen these reference cards before they are a great companion for working with many open source and commercial platforms. Th Mule 3.3 Refcard will guide you through the basics as well as provide examples for working with components ,

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You’re going to read more in 2013, right? Well lets get you started with this sample chapter, Implementation Patterns in Mule from the forthcoming Mule in Action book from Manning Publishing.  This book is the ultimate companion for anyone using Mule and Manning run an early access program so you get get you hands on 8 chapters currently and even pre-order the book. Enjoy!

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A frequent issue I come across writing integration applications with Mule is deciding how to communicate back and forth between my front end application, typically a web or mobile application, and a flow hosted on Mule.

I could use web services and do something like annotate a component with JAX-RS and expose this out over HTTP.  This is potentially overkill,  particularly if I only want to host a few methods, the methods are asynchronous or I don’t want to deal with the overhead of HTTP.  

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Mule is typically used on the receiving end of service requests.  Mule flows, for instance, are generally initiated by external events like a JMS message being sent to a queue, a POSTed HTTP request, or the firing of a Quartz trigger.   Since Mule is usually deployed as a server this behavior should be expected.  What isn’t so obvious, however, is using Mule as a client of these services.  We’ll see in this blog post how MuleClient can be embedded in a non-Mule application to send and consume messages as a client.

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As evident by some prominent web applications PHP remains a popular choice when implementing the front-end of a web application.   PHP’s lacks a bit, however, when it comes to implementing the backend of such applications.   While some very nice frameworks are beginning to fill this gap, the Java ecosystem is often a better choice for implementing the backend of a PHP application.

Despite this, however,

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