Category Archives: Mulesoft Tutorial

Mule 4 Mulesoft Tutorial

Retry Mechanism – Until Success Vs Flow Reference

Published by:

Retry Mechanism – Until Success Vs Flow Reference

In mule 3 we have roll back exception strategy which enable’s the ability to retry the execution in case of error and define a separate flow to be executed once the retry count has exceeded.

In mule 4 you do have re-connection strategy which we can define on the connectors but that only retries in case of failure in connection. In Mule 4 we do not have roll back exception strategy, so in this tutorial we will be looking on how we can implement the same functionality in Mule 4.

Scenario: We want to implement retry mechanism on Web service call, in case of error if HTTP status code is 502 then only API should retry the Web Service call 3 times.

To achieve this retry mechanism, we can use Until Successful, but the issue we will face are:

  1. We would not be able to specify any specific error condition on which we want retry to happen . For Example: We will not be able to define retry only when HTTP status code is 502.
  2. We also cannot implement error flow, once an error has occurred. For Example: Every time an error is generated we need to send the error message on to a queue before retrying.

To complete the above scenario, we will be using Flow Reference.

Flow Reference in Mule 3 was not able to call its own flow in which it was defined. But in Mule 4 you can call any flow even its own flow.

Flow Diagram:

All we need is to use is flow reference to call its own flow when an error is generated. We have moved HTTP Request to another flow “HTTPFlow” and is referred by flow reference in main flow “get:\users:test-config”.

Inside HTTPFlow we have HTTP Request call on which we have implement retry mechanism. In Error handling part, “On Error Continue” is checking for the retry count if it has reached to its max or not. Inside error flow of “On Error Continue” retry count value is getting incremented and after some seconds of sleep; flow reference will again call HTTPFlow. Once the retry count has reached to its max “On Error Continue” will no longer catch the error and the final error is throw back to its parent flow.

    <flow name="get:\users:test-config">
    <ee:transform xmlns:ee="http://www.mulesoft.org/schema/mule/ee/core" xsi:schemaLocation="http://www.mulesoft.org/schema/mule/ee/core http://www.mulesoft.org/schema/mule/ee/core/current/mule-ee.xsd" doc:id="86de922d-7d4d-4d0a-b010-e1cf9e23a79d">
            <ee:message>
                <ee:set-payload><![CDATA[%dw 2.0
output application/json
---
{
  userID: [
    "1", 
    "2"
  ],
  userName: "Varun",
  subject: [
    "Maths", 
    "Mule", 
    "TIbco"
  ],
  class: {
    name: "Class 10"
  }
}]]></ee:set-payload>
            </ee:message>
        </ee:transform>
    <logger level="INFO" doc:name="Logger" doc:id="897eb15a-c379-4051-ae78-21ebbbf33cd1" />	
      <set-variable value="1" doc:name="SetRetryCount" doc:id="ae08693c-0c8e-4397-b5e2-235b8b288821" variableName="retryCount" />
    <flow-ref doc:name="HTTPFlow" doc:id="84ab16f4-0fa5-4ac4-a73e-80dd7ab20ea0" name="HTTPFlow"/>
    <logger level="INFO" doc:name="Logger" doc:id="92727a36-d8ed-4ea1-8616-3c0537598400" />
    </flow>
  <flow name="HTTPFlow" doc:id="610bee6d-59f2-4f77-a29e-d60b88aaea01" >
    <logger level="INFO" doc:name="Logger" doc:id="38537854-3f21-48a7-a6a6-31907d8bca90" message="Calling HTTP request count - #[(vars.retryCount default 0)]" />
    <http:request method="GET" doc:name="HTTPCall" doc:id="c766093c-c7ac-444f-914d-cd4d1b70676d" config-ref="HTTP_Request_configuration" path="/abc">
      <reconnect />
    </http:request>
    <error-handler >
      <on-error-continue enableNotifications="true" logException="true" doc:name="On Error Continue" doc:id="8d23329f-b006-4a56-b6a7-6e33eb748957" when="#[(vars.retryCount as Number default 0) &lt; 3 and error.muleMessage.attributes.StatusCode == 503]">
        <logger level="INFO" doc:name="Logger" doc:id="1be75ffe-a4bf-4fe1-9802-ae1309d76341" message="#[error.description]"/>
        <set-variable value="#[(vars.retryCount default 0) +1]" doc:name="Increment retryCount" doc:id="a9877e1d-d1f5-4786-93e9-58126d08f3f4" variableName="retryCount"/>
        <scripting:execute doc:name="Sleep" doc:id="531bc61a-937d-4a0c-81ce-1ea0685ce64f" engine="groovy">
          <scripting:code >def duration = Long.valueOf('3000');
sleep(duration);
return message.payload;</scripting:code>
        </scripting:execute>
        <flow-ref doc:name="HTTPFlow" doc:id="3f37c302-ec9a-4751-ab4e-dcdefb2607f5" name="HTTPFlow"/>
      </on-error-continue>
    </error-handler>
  </flow>

 

 

 

 

 

Mule 4 Mulesoft Tutorial

Error Handling In Mule 4

Published by:

In this tutorial we will be understand about various types of error handling in mule 4 and how we can implement it in our project with an example.

There are 3 types of error handling mechanism in Mule 4.

  1. On Error Continue
  2. On Error Propagate
  3. Try Catch Scope


On Error Continue


On-Error Continue catches the error, and do not report it as an error; thus the processing of the flow continues even after the error has occurred. This error handler can be used in flows where you don’t want to stop the flow processing even if an error has occurred.

For example in the below flow, the parent flow will execute till the end even if web consumer has returned an error.

SchedulerFlow is calling flow callWebService flow, in case of any error at point 9 (at web service consumer) the flow will process as follows: 1->2->3->7->8->9->12->13->4.
Here at point 13 the error is send to its parent flow (SchedulerFlow) as flow message, and parent flow executes its processing further.

On Error Propagate


On Error Propagate works exactly as Mule 3 Catch exception strategy. In case on any error, On Error Propagate processes the error message and re-throws the error to its parent flow. No further processing is done on that particular flow.

For example in the below Flow, when flow execution starts, point 1, 2, 3 will execute first, on error at point 3 the error is catch by on-error propagate and error processing begins with point 6, 7; once the error handling flow is completed the flow processing ends and an error is re-thrown to its parent flow.

In can of no error or happy scenario point 1,2,3,4,5 are executed, in case of error at point 3; point 1,2,3,6,7 are executed.

In the second example below, SchedulerFlow is calling flow callWebService flow, in case of any error at point 9 (at web service consumer) the flow will process as follows: 1->2->3->7->8->9->12->13->5->6.
Here at point 13 the error is thrown to its parent flow (SchedulerFlow), and parent flow error handler is invoked.

Try Catch Scope


Try catch scope can be used within a flow to do error handling of just inner components. Try catch scope can be very useful in cases where we want to add separate error processing strategy for various components in the flow.

For example: In case of error at point 3 (at web service consumer) the flow will process as follows: 1->2->3->7->8->10->11.
In case of error at point 5 (at saleforces connector) the flow will process as follows: 1->2->3->4->5->9->6.

 

Configuring On-Error Continue and On-Error Propagate


As in Mule 3 we had to specify which error is to be catch inside the catch exception strategy, same we can do in Mule 4 with even more control.

In Mule 4 we can specify Error Type and/or When Condition which when is evaluated true that particular error handler is executed. In case none error handler catches the error the error is re-thrown to its parent flow. 

Error Type: This matches with the type of error that is thrown. Error Type are auto populated based on connectors used in the flow. It contains the list of errors that the connectors can throw in the flow.

 

When Condition: The expression that will be evaluated to determine if the exception strategy could be executed. This should always be boolean expression. 

In below example when variable errorCount is greater than 3 then only that particular error handler is invoked.

Mule 3 Mulesoft Basics Mulesoft Tutorial

Externalizing Common Mule Flows

Published by:

Externalizing Common Mule Flows


In this tutorial we will be externalizing some common mule flows so they can be used by multiple Mule Applications
For Example – If I have a common exception handling which is same for all my other applications and I want to externalize this common exception handling code so that –
1. No one in the team can modify the common flows leading to code discrepancy.
2. Teams don’t have to copy same code again and again in my next API which they are going to build.
3. Also, This will also help my API code look more neat and clean.

Externalizing common mule flows can be achieved by exporting the flows to be externalized into a JAR file and then importing the JAR in other applications. Tells look on the details of how we can do this with just few steps.

1. Understanding the Flow


In the flow below we want to externalize sub flow – “externalizeMuleAPISub_Flow” which is been called by Flow reference in Get and Post  Flows  and exception handling – “externalizeMuleAPI-apiKitGlobalExceptionMapping”.


2. Creating new Mule project


We need to create a new mule project and dump the mule common flows that we want to externalize into it. And remove copied code from our previous project.

Here we have deleted and added the 2 flows from our old project into our new project.

 

3. Exporting the new project as JAR file.


Here are the steps to be followed to export the project as JAR.

Right Click on the Project in Package Explorer >> Click Export

In the Popup Window Select Java>Jar File and Click Next.

Select The project to be exported “externalflows” and add the path where the JAR is to be saved and Click Finish.

 

Now, we have create the project with common flows as Jar and export it to the specified location.

4. Importing the JAR file


Now after exporting JAR, we need to import it to our main project.

To Import the Jar -> go to Project Properties and Click “Add External Jars” and select the JAR File.

5. Adding the Common Flows


Now we need to add the mule XML file name that we have imported as JAR into our main project.

6. Running the Code


You might see few error been reported by Mule even after adding the mule XML filename. But do not worry on building the application all the error will go off.

Mule 4 Mulesoft Basics Mulesoft Tutorial

Variables in Mule 4

Published by:

Variable in Mule 4


In this Variable in Mule 4 tutorial we will look how we can create and use mule variable in Mule 4, and how it is different from Mule 3 and Mule 4.

In Mule 3 we had Flow variables, Session variables and record variable to store the data inside mule flow. But now in Mule 4 this has been changed; session variable and record variable has been removed and there is only Flow Variable.

As in Mule 3, Flow Variable in Mule 4 value is lost even when the flow crosses the transport barrier.
Session variable has been completely removed in Mule 4.

In Mule 4, flow variables have been enhanced to work efficiently during batch processing, just like the record variables. Flow variables created in batch steps are now automatically tied to the processing record and stays with it throughout the processing phase. No longer record variables are needed.
Continue reading

Mule 4 Mulesoft Basics Mulesoft Tutorial

Mule 4: JSON Schema Validation

Published by:

JSON Schema is a specification for JSON based format for defining the structure of JSON data. It validates input data at runtime and verifies that they match a referenced schema or not. We can match against defined schemas that exist in local file or in an external URI.

If the payload is incorrect with given JSON schema, then compiler throws below Exception:

org.mule.module.json.validation.JsonSchemaValidationException: Json content is not compliant with schema

Use Case:

Validating the input JSON payload against with JSON Schema.

JSON Payload:

{
  "firstName": "Murali",
  "lastName": "Krishna",
  "age" : 26
}	

JSON – Schema :

{
  "$schema": "http://json-schema.org/draft-04/schema#",
  "type": "object",
  "properties": {
    "firstName": {
      "type": "string"
    },
    "lastName": {
      "type": "string"
    },
    "age": {
      "type": "integer"
    }
  },
  "required": [
    "firstName",
    "lastName",
    "age"
  ]
}

Mule Flow:

Step -1 :

Configure the HTTP Listener with by giving hostname, port number and path along with this specify allowed methods (Optional) at an Advanced tab of HTTP connector.

Step-2:

Drag and Drop the JSON Validate Schema from Mule Palette to validate the input payload. And provide the schema path. In my case it is like below:

schemas/Sample-Schema.json

From above line,

schemas –> It is directory

Sample-Schema.json —> It is JSON-Schema structure for validation.

Syntax of JSON Validator as below:

<json:validate-schema doc:name="Validate schema" doc:id="5a8b10e1-59e8-4f68-9aaa-303c9cb5c9d6" schema="schemas/Sample-Schema.json">

Step-3:

Drag & Drop the Logger component to log the resultant payload after validation.

Final Config.xml:

<?xml version="1.0" encoding="UTF-8"?>

<mule xmlns:json="http://www.mulesoft.org/schema/mule/json" xmlns:validation="http://www.mulesoft.org/schema/mule/validation"
  xmlns:ee="http://www.mulesoft.org/schema/mule/ee/core"
  xmlns:http="http://www.mulesoft.org/schema/mule/http" xmlns="http://www.mulesoft.org/schema/mule/core" xmlns:doc="http://www.mulesoft.org/schema/mule/documentation" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.mulesoft.org/schema/mule/core http://www.mulesoft.org/schema/mule/core/current/mule.xsd
http://www.mulesoft.org/schema/mule/http http://www.mulesoft.org/schema/mule/http/current/mule-http.xsd
http://www.mulesoft.org/schema/mule/ee/core http://www.mulesoft.org/schema/mule/ee/core/current/mule-ee.xsd
http://www.mulesoft.org/schema/mule/validation http://www.mulesoft.org/schema/mule/validation/current/mule-validation.xsd
http://www.mulesoft.org/schema/mule/json http://www.mulesoft.org/schema/mule/json/current/mule-json.xsd">
  <http:listener-config name="HTTP_Listener_config" doc:name="HTTP Listener config" doc:id="8a601d72-5913-4ed7-99d3-707601301ec9" >
    <http:listener-connection host="0.0.0.0" port="8080" />
  </http:listener-config>
  <flow name="abcFlow" doc:id="30917fd1-0429-4ec7-9d7d-aa8d4d19413e" >
    <http:listener doc:name="Listener" doc:id="2b89fed0-69ce-47eb-93bf-3bd0628fe188" config-ref="HTTP_Listener_config" path="abc" allowedMethods="POST">
      <ee:repeatable-file-store-stream />
    </http:listener>
    <json:validate-schema doc:name="Validate schema" doc:id="5a8b10e1-59e8-4f68-9aaa-303c9cb5c9d6" schema="schemas/Sample-Schema.json">
    </json:validate-schema>
    <logger level="INFO" doc:name="Logger" doc:id="26b62866-2f25-4374-9d95-9fe14c052366" message="Payload is Validated ----&gt; #[message.payload]" />
  </flow>
</mule>

Success Scenario:

Failed Scenario:

Thank you!

Please feel free to share your thoughts in the comments section.

Mule 4 Mulesoft Basics Mulesoft Tutorial

Mule – 4 DataWeave Functions – Part – 1

Published by:

In DataWeave 2.0 functions are categorized into different modules.

  1. Core (dw::Core)
  2. Arrays (dw::core::Arrays)
  3. Binaries (dw::core::Binaries)
  4. Encryption (dw::Crypto)
  5. Diff (dw::util::Diff)
  6. Objects (dw::core::Objects)
  7. Runtime (dw::Runtime)
  8. Strings (dw::core::Strings)
  9. System (dw::System)
  10. URL (dw::core::URL)

Functions defined in Core (dw::Core) module are imported automatically into your DataWeave scripts. To use other modules, we need to import them by adding the import directive to the head of DataWeave script, for example:

import dw::core::Strings

import dasherize, underscore from dw::core::Strings

import * from dw::core::Strings

Sample Payload:
{
"firstName" : "Murali",
"lastName" : "Krishna",
"age" : "26",
“age” : ”26”
}

1. Core (dw::Core)

Below are the DataWeave 2 core functions:

++ , –, abs, avg, ceil, contains, daysBetween, distinctBy, endsWith, filter, IsBlank, joinBy, min, max etc….

result : [0, 1, 2] ++ [“a”, “b”, “c”] will gives us “result” : “[0, 1, 2, “a”, “b”, “c”]”

result : [0, 1, 1, 2] — [1,2] will gives us “result” : “[0]”

result : abs(-20) will gives us “result” : 20

average : avg([1, 1000]) will gives us “average” : 500.5

value : ceil(1.5) will gives us “value” : 2

result : payload contains “Krish” will gives us “result” : true

days: daysBetween(“2016-10-01T23:57:59-03:00”, “2017-10-01T23:57:59-03:00”) will gives us “days”: 365

age : payload distinctBy $ will gives us  :

 {

“firstName” : “Murali”,

“lastName” : “Krishna”,

“age” : ”26”

}

a: “Murali” endsWith “li” will gives us “a” : true

a: [1, 2, 3, 4, 5] filter($ > 2) will gives us “a” : [3,4,5]

empty: isBlank(“”) will gives us “empty” : true

aa: [“a”,”b”,”c”] joinBy “-” will gives us “a” : “a-b-c”

a: min([1, 1000]) will gives us “a” : 1

a: max([1, 1000]) will gives us “a” : 1000

2.Arrays (dw::core::Arrays)

Arrays related functions in DataWeave are :

countBy, divideBy, every, some, sumBy

[1, 2, 3] countBy (($ mod 2) == 0) will gives us 1

[1,2,3,4,5] dw::core::Arrays::divideBy 2 will gives us :

[

[

1,

2

],

[

3,

4

],

[

5

]

]

 

[1,2,3,4] dw::core::Arrays::every ($ == 1) will gives us “false”

[1,2,3,4] dw::core::Arrays::some ($ == 1) will gives us “true”

[ { a: 1 }, { a: 2 }, { a: 3 } ] sumBy $.a will gives us “6”

3.Binaries (dw::core::Binaries)

Binary functions in DataWeave-2 are:

fromBase64, fromHex, toBase64, toHex

toBase64(fromBase64(12463730)) will gives us “12463730”

{ “binary”: fromHex(‘4D756C65’)} will gives us “binary” : “Mule”

{ “hex” : toHex(‘Mule’) } will gives us “hex” : “4D756C65”

4.Encryption (dw::Crypto)

Encryption functions in Dataweave – 2 are:

HMACBinary, HMACWith, MD5, SHA1, hashWith

{ “HMAC”: Crypto::HMACBinary((“aa” as Binary), (“aa” as Binary)) } will gives us :

“HMAC”: “\u0007£š±]\u00adÛ\u0006‰\u0006Ôsv:ý\u000b\u0016çÜð”

Crypto::MD5(“asd” as Binary) will gives us “7815696ecbf1c96e6894b779456d330e”

Crypto::SHA1(“dsasd” as Binary) will gives us “2fa183839c954e6366c206367c9be5864e4f4a65”

5.Diff (dw::util::Diff)

It calculates difference between two values and returns list of differences.

DataWeave Script:

%dw 2.0

import * from dw::util::Diff

output application/json

var a = { age: “Test” }

var b = { age: “Test2” }

a diff b

Output:

{

“matches”: false,

“diffs”: [

{

“expected”: “\”Test\””,

“actual”: “\”Test2\””,

“path”: “(root).age”

}

]

}

Note:

Rest of the things will proceed in Mule – 4 DataWeave Functions Part – 2 article

Mule 4 Mulesoft Basics Mulesoft Tutorial

DataWeave 1.0 to DataWeave 2.0 Migration – Part -1

Published by:

DataWeave is a new feature of Mule-3 that allows us to convert data to any kind of format, such as XML, CSV, JSON and POJO’s etc. In Mule 3, we use both MEL and Dataweave for writing the mule messages. Among these, MEL is default expression language in Mule 3 But this approach had some data inconsistencies and scattered approaches. To avoid the stress of converting data objects to Java objects in Mule 3 every time by the usage of expressions Mule 4 was launched. In Mule 4 DataWeave is the default expression language over Mule 3’s default MEL.

In Mule-4 DataWeave version has changed from 1.0 to 2.0.

Apart from syntax changes, there are many new features in DataWeave 2.0

Continue reading

Mule 3 Mule Interview Question Mulesoft Tutorial

Interview Questions Mulesoft / Mule ESB Tutorial

Published by:

MuleSoft or Mule ESB interview Questions


Here are the 18 most important and common mulesoft or mule esb interview questions and answers which are bound to be asked in any Mule ESB interview. Whether it’s Mulesoft or Mule ESB interview with Accenture, Cognizant, Infosys, Deloitte or any company below Mule ESB interview questions are always always been asked. You can easily clear any Mulesoft or Mule ESB interview questions if you learn answers to these Mule ESB questions.

1. What are Web Services?


Web service is a function or program in any language that can be accessed over HTTP. Message format can be XML or JSON or any other program as long as the other programs can understand and communicate. Web services can be synchronous or asynchronous. Any web service has server-client relationship. Any web service can have multiple clients. Eg: When a travel portal is selling tickets of an airliner, Portal is client and the Airline is the server as it is selling its service. Continue reading

Mule 3 Mule Interview Question Mulesoft Tutorial

Interview Questions 2 – Mulesoft / Mule ESB Tutorial

Published by:

MuleSoft or Mule ESB interview Questions


Here are the most important and common mulesoft or mule esb interview questions and answers which are bound to be asked in any Mule ESB interview. Also see Mule Interview Questions I.

1. What are inbound and Outbound properties ?


Inbound properties are immutable, are automatically generated by the message source and cannot be set or manipulated by the user.  They contain metadata specific to the message source. A message retains its inbound properties only for the duration of the flow; when a message passes out of a flow, its inbound properties do not follow it.
Continue reading

Mule 3 Mule Interview Question Mulesoft Tutorial

RAML Interview Questions – Mule Tutorial

Published by:

RAML Interview Questions.


In this mule tutorial, here are the most important and common RAML interview questions and answers which are bound to be asked in any Mule ESB interview.

1. What is RAML and why we use it?


RAML – RESTful API Modeling Language
RAML is similar to WSDL, it contains endpoint URL, request/response schema, HTTP methods and query and URI parameter.
RAML helps client (a consumer of the service) know, what the service is and what/how all operations can be invoked.
RAML helps the developer in creating the initial structure of this API. RAML can also be used for documentation purpose.

2. Who can you import RAML in your poject?


Read here: Mule Tutorial – Creating Mule Project with RAML
Continue reading

Mule 3 Mulesoft Basics Mulesoft Tutorial

Validation Framework – Handling Business Errors MuleSoft

Published by:

MuleSoft Validation Framework – Handling Business Errors


In this tutorial of mulesoft validation we will create an exception handling framework that will generate business/logical error and do custom validations to request/response message while mapping mulesoft code and learn how to handle those error.
For example: The message that mulesoft application received should have some validations while mapping to the backend application request, in case of validation failure the application should throw an error with error message.

The validations are:
1. if a is (a < b or a < 10) then generate error with error message “A should not be less than 10 or b”.
2. all the values a or b or c or d sum should be less than 500 else generate error with message “a+b+c+d should be less than 500.”

The above example, can be resolved in couple of ways and we will see one of the most simplest and easy way by creating validation framework.
We will resolve by using dataweave and a custom exception class.
Continue reading

Mule 3 Mulesoft Basics Mulesoft Tutorial

Scatter-Gather In Depth – MuleSoft Tutorial

Published by:

MuleSoft Scatter-Gather Scope


In this tutorial we will look at various configuration properties of Scatter-Gather with examples in detail and also see how to handle exception in Scatter-Gather.

Why use Scatter-Gather in Mulesoft:
To achieve parallel processing of multiple flows in mule we can use Scatter-Gather. The routing message processor Scatter-Gather sends a request message to multiple routes concurrently which are configured inside Scatter-Gather and collects the responses from all routes, and aggregates them into a single message. There will be multiple threads created for executing multiple routes simultaneously.
Scatter-Gather can also execute multiple routes sequentially.

Please read Validation Framework to understand how error is generated in the example.
Continue reading

Mule 3 Mulesoft Basics Mulesoft Tutorial

Caching or Cache Scope – Mulesoft / Mule ESB Tutorial

Published by:

Caching In Mule ESB or Cache Scope


In this Mule ESB tutorial we will look into what is caching and why to use it, how can we implement caching in mulesoft project and  configuration properties in Mule Cache Scope/Activity. Also a step by step configuration of mule cache scope/activity and how to cache information retrieved from database. Please refer to Mule Tutorial: Connecting with Database mule tutorial to know how to connect to database in Mule ESB.

What is caching and why to use it?


Caching is a concept with is used to store frequently used data in the memory, file system or database which saves processing time and load if it would have to be access from original source location every time.

For example: We have to create an API to retrieve user information, that has connect to an external database which is on different server and fetch the records. (Assumption: external DB is not changing frequently)
Continue reading

Mule 3 Mulesoft Basics Mulesoft Tutorial

Understanding Various Mule Flows – Mulesoft Tutorial

Published by:

Mulesoft / Mule EBS – Mule Flows Tutorial
Mule Flows


In this mule ESB tutorial we will understand various mule flows in detail with downloadable examples.

Various types of flows in mule


There are 4 types of flows in mule. While creating these flows the flow name should be unique in whole mule project despite beaning in different mule application XML file.

SubFlow


  1. Subflow always processes messages synchronously (relative to the flow that triggered its execution).
  2. Subflow executes in the same thread of the calling process. Calling process triggers the sub-flow and waits for it to complete and resumes once the sub-flow has completed.
  3. Subflow inherits processing strategy and exception handling strategy from the parent/calling flow.

Use – It can be used to split common logic and be reused by other flows.
Continue reading

Mule 3 Mulesoft Basics Mulesoft Tutorial

Creating Mule Project with RAML – Mulesoft / Mule ESB Tutorial

Published by:

Creating Mule Project with RAML


In this Mule tutorial we will learn how to create Mule project with RAML and a detailed walk-through on how the Mule flow works in case of a success or error scenario:

Mule ESB – What is RAML and why it’s used


RAML stands for RESTful API Modeling Language and is similar to WSDL. A RAML provides a structure to an API and also help the client who is invoking the API to know before hand what the API does.

A RAML contains:

  1. Endpoint URL with its Query parameters and URI parameters,
  2. HTTP methods to which API is listening to (GET, POST, PUT, DELETE),
  3. Request and response schema and sample message,
  4. HTTP response code that an API will return (eg: 200, 400, 404, 500). Continue reading
Mule 3 Mulesoft Basics Mulesoft Tutorial

Connecting with Database MySql – Mulesoft / Mule ESB Tutorial

Published by:

Connecting with Database MySQL


In this Mulesoft / Mule ESB tutorial of Connecting with Database Using MySql, we will use mulesoft Database Connector and connect it with MySQL DB:

MuleSoft Database Connector using MySQL


The Database connector allows you to connect with database with almost any Java Database Connectivity (JDBC) relational database using a single interface for every case. The Database connector allows you to run SQL operations on database including Select, Insert, Update, Delete, and even Stored Procedures. As of Anypoint Studio May 2014 with 3.5.0 Runtime, the JDBC connector is deprecated, and the Database connector takes on JDBC connection capabilities.
Continue reading