In our upcoming MuleSoft webinar, “‘The Health Cloud’: Are we there yet?”, we’ll be talking all about healthcare and the cloud. There has been quite a bit of talk about a “Health Cloud” which promises to extend the point of care, improve patient outcomes, enable closer clinical collaboration and lower costs, but have healthcare organizations really embraced the cloud? Or is this another case of media hype? With such confidential information at risk, how are organizations dealing with data security and integration with third party applications and services?
Hot on the heels of the announcement of the RESTful API Modeling Language (RAML) by the RAML working group, I am very happy to announce the general availability of APIkit.
APIkit consists of a set of open source Maven and Mule Studio-based tools that enable developers to be massively productive in creating well-designed REST APIs. APIkit features include the ability to take a REST API designed in RAML, automatically generate backend implementation flows for it, and then run and test the API with a pre-packaged console.
CloudHub Release 34 is now live! With this release we’ve made a number of improvements to CloudHub to make managing your integrations easier. These include the ability to promote applications from sandboxes, monitor workers for problems, create secure environment variables, and scale applications vertically, as well as horizontally.
I’m pleased to announce the availability of the Oct 2013 release of Studio and CloudHub. It greatly expands our support for DataSense in our Anypoint™ Connectors, improves connector usability through auto-paging of result sets, and includes many other improvements.
In the past, as now, Mule ESB follows a release schedule that introduces a new version of our industry-leading ESB software every 9 – 12 months, supplemented with maintenance releases approximately every 6 months. Though this cadence fit very tightly with the demands of our customers who deploy Mule on premises, we came to realize that our customers deploying Mule to CloudHub were much more flexible in terms of updating versions of software, and were more eager to take advantage of new features and functionality.
We have a lot of cool things happening at MuleSoft, here is a quick round up of things you shouldn’t miss.
Discover how to take your integration strategy to the next level at MuleSoft Summit — coming to a city near you this Fall! Join the core MuleSoft team and integration experts to learn best practices and empower your development team to stay one step ahead of evolving business needs. The eight cities on this Fall Summit tour are:
In the past few months, you may have noticed that we have regularly announced the release of new Mule connectors for NoSQL data-stores. Two main forces are at play behind the need for these types of data-stores:
Big Data – The need to deal in realtime or near-realtime with the vast amounts of data “web-scale” applications can generate,
BASE vs ACID – The need to scale reliably in the unreliable environment that is the cloud leading to the relaxation of RDBM’s ACID properties (Atomicity, Consistency, Isolation and Durability) towards BASE ones (Basically Available, Soft state, Eventually consistent).
So where is Mule coming into play in this equation you might ask?
Mule can help integrating such NoSQL data-stores with the resources that produce and consume data. This integration goes way beyond than simply establishing protocol connectivity: thanks to Mule queuing, routing and transformation infrastructure, important tasks like data capture and curation can be achieved. Mule can also be used to expose APIs that make either raw data or processed data available for use in custom applications.
In your daily work as an integration developer you’re working with different kinds of patterns, even if you’re not aware of it.
Since Mule is based on EIP (Enterprise Integration Patterns) you’re most definitely using patterns when using Mule.
One of those patterns that seems to raise a lot of questions is the “fork and join pattern”. The purpose of the fork and join pattern is to send a request to different targets, in parallel, and wait for a aggregated response from all the targets.
The recently upgraded Redis connector for Mule allows you to interact with this NoSQL data-store in a convenient manner. This blog is a tutorial that you can follow in order to get your feet wet with Redis, if you don’t know it already, or Mule, if you have Redis experience and want to see how they both can work together.
In this tutorial, we will build a very simple back-end that captures page visit count for identified users via a web bug. This example illustrates the usage of Mule as a tool for capturing events and routing them to NoSQL storage for later analysis.