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Amazon Web Service’s S3 stands for “Simple Storage Service.” It is a type of cloud storage provided to the developers as a scalable solution over the Internet.
Amazon S3 uses the concept of Buckets and Objects to store the data. It allows an easy, user-friendly, fast and on-demand approach for storing & retrieving the data online.
Amazon S3 or Amazon Simple Storage Service is a service offered by Amazon Web Services to store objects, download, and use the data kept in the S3, and help to build an application that requires internet storage.
Mulesoft provides the Amazon S3 connector to help you easily connect to your S3 and get on with your integration.
In this article, I am going to explain to you how we can use the power of MuleSoft to send PDF files from Experience API to Process/System API, using the multipart/form-data type, and to covert it back to PDF file in the second API.
We are going to read the PDF file from the local disk using Mule’s out-of-the-box (OOTB) File connector to read in Experience API. Then we will be sending this PDF as binary with some other fields to another API (this can be named as Process API) which accepts data as multipart/form-data. Next, we will extract this PDF binary from the received payload and convert it back to PDF and save the file to the local disk using Mule’s OOTB File connector to write.
When most of the integration data is lying inside an organization's data center and data is highly secured, then the On-Prem deployment model is the right solution.
It does offer the flexibility to set up your load balancing, domains, VPC, and anything you want to do to your environment as you will be building it in your own data center. You can cluster specific servers that you have in your infrastructure and set them accordingly.
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.
Object Store Connector is a Mule component that allows the storage of key-value. Although it can serve a wide variety of use cases, it is mainly designed for storing watermarks, access tokens, user information, etc. It stores data in the form of Key-Value pair.
Object store connector provides 7 types of operation:
VM Connector is used for intra-app (within the app) and inter-app communication through either Transient or Persistent asynchronous queues.
VM Connector is mainly used for the following:
Hey Guys
These are below 10 videos that help you to learn MuleSoft Development Hands-on!
This video materials will help you to understand the fundamentals of Mulesoft. Most of these videos are having demo-based tutorials. Please go through each video to understand the MuleSoft related topics.
This article shows you how to design, develop, deploy, and manage a simple RESTful Application using MuleSoft.
Let us take a simple real-time scenario of how ATM works internally.
In my previous article, we discussed what exactly is "Scalability" and how we can achieve it in Mule Apps. This article is in continuation of it.
As said previously, I use general terms to explain things so that you can relate those examples with real-time scenarios! Again this article will give you basic info on the concept. You can read more info in official Mule Docs.
In this tutorial, we will see how we can call multiple subflows dynamically with the help of single flow reference component.
As a first step, let's create a new Mule project using Anypoint Studio. After creating the project, we need to have all the subflow details listed under .properties/.yaml file.
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.