Integration has been an enterprise challenge for a long time. In order to create the new products, applications, and services that businesses need to confront the digital revolution, you have to connect systems, data, and devices. There’s no way around it. Enterprises struggled with point-to-point integrations, which created a spaghetti-like mess of code, and then, for many years, companies found a better integration solution with ESBs (Enterprise Service Bus) and an ESB integration approach.
This tutorial continues from Part 1.
Mock is a feature provided by MUnit to mock the behavior of the message processor. Basically, MUnit replaces the actual behavior of message processor with the behavior defined by the user.
There are various scenarios where we can use the Mock Message processor. Imagine we have completed the development of a Mule application and need to test it,
Mule ESB allows you to connect to anything and anywhere using a wide range of connectors and endpoints. File connector is one of the commonly used connectors that allows you to read/write files with file systems. There are two ways to use file connector –
- Inbound Endpoint – When file connector is used at the beginning of the flow, it acts as an inbound endpoint where you can receive files for processing.
This post is by one of our MuleSoft champions, Antonio Abad.
Let’s start with a simple definition of both concepts:
“An ESB is basically the integration of the new and the old, providing a central place for the services, applications, and IT resources in general that you want to connect.”
“A microservice architecture (vs. the legacy monolithic architecture) is an approach to developing a software application as a series of small services,
We all know how powerful Dataweave Transform Message component is. This is such a powerful template engine that allows us to transform data to and from any format (XML, CSV, JSON, Pojos, Maps, etc. basically ).
So if we need to transform we need a Dataweave component in our flow. But wait! Dataweave also provides us a function called Dataweave function that helps us to execute Dataweave language outside a Dataweave transform component.
The principles of SOA were sound, it was the implementation that failed. Service-oriented principles should be the underpinning philosophy behind integration; and an enterprise service bus pattern, when delivered with lightweight solutions, has been proven effective.
Service Oriented Architecture (SOA) has been both hailed as a modern and agile approach to enterprise architecture and software development as well as deemed as a colossal waste of time and money.
An Enterprise Service Bus (ESB) is a set of principles and rules for connecting applications together over a bus-like infrastructure. ESB products enable users to build this architecture, but they differ in their methodology and the capabilities they provide. Mule as an ESB is the runtime engine of Anypoint Platform.
The core concepts of Mule ESB
The core concept of the ESB architecture is that applications are integrated by putting a communication bus between them and then enabling each application to talk to the bus.
What is hMailServer?
hMailServer is a free, open source, e-mail server for Microsoft Windows. It supports the common e-mail protocols like IMAP, SMTP and POP3.
Let’s have a look at a simple example of sending emails using hMailServer Administrator. Here, hMail administrative server is used for configuring email server on local machine. We need to do following 3 steps for sending emails via MuleSoft:
- hMail server setup on local machine for setting up email server and creating domain and different usernames
- Mulesoft project setup
- Outlook configuration for viewing mails
Steps for configuration:
There is a lot of interest in how Mule supports emerging patterns like CQRS (Command Query Responsibility Segregation), so I wanted to create a series of blog posts discussing an insightful approach. Over the course of the series so far, we described the initial problem at hand and how to solve it using CQRS and API-led Connectivity. Next, we designed and implemented the synchronous Query API application followed by the implementation of the asynchronous Command API application with a composable API architecture.
Welcome to the final post in the three post series about batch improvements on Mule 3.8!
The last new feature we have is a simple one which comes quite handy when you need to read through logs. As you know, batch jobs are just programs processed in batch mode, and each time the job is triggered, a new job instance is created and tracked separately. Each of those instances is unique and therefore has a unique ID.