This document discusses how to scale Mule applications globally through techniques like parallel processing, asynchronous tasks, orchestration, messaging backbones, clustering, and load balancing. It describes common problems with performance, integration, security, and transactions in large enterprises and how Mule addresses these through features such as transactions, computation optimization, identifying bottlenecks, and using external services like databases and messaging infrastructure.

1. Global Scale ESB with Mule
Andrew D Kennedy
grkvlt@apache.org
March 2011

2. Who Am I
• Enterprise Java Developer
• Apache Qpid Committer
• Previously Security Engineer
• Over 15 Years Java Experience
• Worked with various Investment Banks
• Interested in Data Mining and
Visualisation

3. This Presentation
• What is an ESB
• What is Mule
• Mule Applications
• Mule Scalability

4. What is an ESB
• Enterprise Service Bus
• SOA
– Service Oriented Architecture
• SEDA
– Staged Event-Driven Architecture
• EIP
– Enterprise Integration Patterns

5. Service Oriented Architecture
• Services
– Shared Business Functions
• Decoupling
– Local and Remote Services
• Distributed Applications
• Directory and Discovery

6. EIP
• Similar to Design Patterns
– Gang of Four Book
• Shared Terminology
• Names for Common Concepts
• Allows Discussion
• Simplifies Design

7. (Some) Common Patterns
• Aggregator (268)
• Channel Adapter (127)
• Content Based Router (230)
• Dead Letter Channel (119)
• Selective Consumer (515)
• Message Translator (85)
• Guaranteed Delivery (122)

8. What is Mule
• Open Source Project
• MuleSoft
– Mule Forge
– Mule Enterprise
– Mule MQ
– Tcat Server
• 2.x - Legacy Applications
• 3.1.1 - Current Community Release
• 3.2.0 - Latest Developer Build

9. Transports
• Carry Messages between Services
• Connector
– Configuration
– Threading
– Retry
• Endpoint
– Connects Services
– Transform Messages
– Transaction Boundary

10. Endpoint Examples
<file:inbound-endpoint path="/esb/in"
comparator="org.mule.transport.file.comparator.Older
FirstComparator" reverseOrder="true” />
<jetty:endpoint name="server" host="localhost"
port="60203" path="services/Lookup" />
<imaps:endpoint name=”mail" host="localhost"
password=”hunter2" port="123" user=”adk"/>
<quartz:endpoint name=”batch" repeatCount="10"
repeatInterval=”60000" jobName="job"/>
<jms:inbound-endpoint queue="test.queue"/>

11. VM
• Communication within VM
• Synchronous or Asynchronous
• Transactional
<vm:connector name="async"
queueEvents="true” />
<vm:inbound-endpoint path="in"
connector-ref="async"/>

12. JMS
• Queues
• Topics
• Request-Response
<jms:connector name=”jms" specification="1.1"
connectionFactory-ref=”qpid"
username=”adk" password=”hunter2” />
<jms:outbound-endpoint queue=”audit” />
<jms:inbound-endpoint topic=”uk.*.gbp” />

13. Web Services
• HTTP and HTTPS
– Custom Data Formats
• CXF
– JAX-WS
– SOAP
– WSDL
• REST

14. CXF JAX-WS
<inbound-endpoint
address="http://localhost:63081/hello" />
<cxf:jaxws-service
serviceClass="org.example.ServiceImpl” />
<cxf:jaxws-client clientClass=”com.example.Client”
wsdlPort="SoapPort”
wsdlLocation="classpath:/save.wsdl”
operation=”output” />
<outbound-endpoint
address="http://www.example.com/services/save” />

15. File System
• Poll Directory for Input
<file:connector name="input" fileAge="500"
autoDelete="true" pollingFrequency="100"
moveToDirectory="/backup"
moveToPattern="#[header:originalFilename].backup”
/>
• Write Output File
<file:connector name="output" outputAppend="true"
outputPattern="#[function:datestamp]-
#[header:originalFilename]" />

16. Other Transports
• AJAX • TCP
• jBPM • UDP
• JDBC • FTP
• Quartz • POP3
• STDIO • IMAP
• RMI • SMTP
• Servlet • XMPP

17. Transformers
• Change message content
• XML to POJO via JAXB
• Applied to endpoints
• Efficient mechanism for processing
• Similar to AOP

18. Transformer Types
• Encryption and Decryption
• ByteArray to Object
• Expression Evaluator
• XML and JSON
• Compression
• Encoding and Decoding

19. Filtering
• Apply to endpoints
• Payload Type
• Expression
– XPath, OGNL, JXPath
• RegEx
• Wildcard
• Message Property
• Logical Operators
– And, Or, Not

20. Filtering Examples
<and-filter>
<message-property-filter
pattern="JMSCorrelationID=1234567890"/>
<message-property-filter pattern="JMSReplyTo=null"/>
</and-filter>
<or-filter>
<payload-type-filter expectedType="java.lang.String"/>
<payload-type-filter expectedType="java.lang.StringBuffer"/>
</or-filter>
<not-filter>
<wildcard-filter pattern=”com.example.*"/>
</not-filter>

21. Routers
• Control message flow at endpoints
• Used to link services
• Both inbound and outbound
• Specify Filtering and Transformations

22. Selective Consumer
<inbound>
<selective-consumer-router>
<mulexml:jxpath-filter
expression="msg/header/resultcode =
'success'"/>
</selective-consumer-router>
<forwarding-catch-all-strategy>
<jms:endpoint topic="error.topic"/>
</forwarding-catch-all-strategy>
</inbound>

23. Idempotent Filter
<inbound>
<idempotent-receiver-router
idExpression="#[message:id]-#[header:foo]">
<simple-text-file-store directory="./idempotent” />
</idempotent-receiver-router>
</inbound>

24. Filtering Router
<outbound>
<forwarding-catch-all-strategy>
<jms:outbound-endpoint queue="error.queue"/>
</forwarding-catch-all-strategy>
<filtering-router>
<smtp:outbound-endpoint to=”adk@example.com"/>
<payload-type-filter expectedType="java.lang.Exception"/>
</filtering-router>
<filtering-router>
<jms:outbound-endpoint queue="string.queue"/>
<and-filter>
<payload-type-filter expectedType="java.lang.String"/>
<regex-filter pattern="the quick brown (.*)"/>
</and-filter>
</filtering-router>
</outbound>

25. Services
• Combine Endpoints, Routers and
Components
• Mule 2.0 idiom
• Replaced with Flows and Patterns
– Simpler to use and configure
– Some features still not available

26. Flows
• Mule 3 idiom
• Inbound endpoint
• Message processors
– Chained execution
– Components
• Outbound endpoint for one-way
• Response for request-response

27. Components
• Carry out actions
• Business logic in a flow
• Simple components
– Logging
– Passthrough
– Testing
• Spring or POJO
• Web services

28. Message Processors
• Aggregator and Splitter
• Message Filters
• Recipient List
• Resequencer
• Round Robin
• Wire Tap

29. Example Flow
<flow name=”OrderFlow">
<file:inbound-endpoint path="/incoming">
<file:filename-filter name=”order-*.xml"/>
</file:inbound-endpoint>
<xml:xslt-transformer xsl-file=”order-transform.xsl"/>
<splitter expression="xpath://order"/>
<!-- The following message processors will be invoked for each order in the xml file -->
<expression-filter expression="xpath://order[@type='book']"/>
<component class=”com.example.BookOrderProcessor"/>
<smtp:outbound-endpoint subject="Order Confirmation" address="#[variable:email]"/>
<jdbc:outbound-endpoint ref=“saveOrder"/ >
<default-exception-strategy>
<jms:outbound-endpoint queue="failedOrders"/>
</default-exception-strategy>
</flow>

30. JMS Flow
<flow name=”JmsFlow">
<jms:inbound-endpoint queue="in">
<jms:transaction action="ALWAYS_BEGIN" />
</jms:inbound-endpoint>
<component class="com.example.ProcessMessage" />
<jms:outbound-endpoint queue="out">
<jms:transaction action="ALWAYS_JOIN" />
</jms:outbound-endpoint>
<default-exception-strategy>
<commit-transaction exception-pattern="com.example.ExampleException” />
<jms:outbound-endpoint queue="dead.letter">
<jms:transaction action="JOIN_IF_POSSIBLE" />
</jms:outbound-endpoint>
</default-exception-strategy>
</flow>

31. Complex Flow
<flow name=”TwitterFlow”>
<poll frequency="5000">
<twitter:search query=”example" />
</poll>
<splitter evaluator="json" expression="results" />
<idempotent-message-filter idExpression="#[json:id]" />
<enricher target="#[variable:userDescription]" source="#[json:description]">
<twitter:user userId="#[json:from_user]" />
</enricher>
<salesforce:create type="Opportunity">
<salesforce:sObject>
<salesforce:field key="Name" value="#[json:from_user]" />
<salesforce:field key="Description" value="#[variable:userDescription]" />
</salesforce:sObject>
</salesforce:create>
</flow>

32. Patterns
• Specific integration Features
• Simple Service
– Exposes Components as Web Services
• Web Service Proxy
• Bridge
– Message Adapter and Transformer
• Validator
– Validates inbound messages synchronously
– Processes asynchronously

33. Questions?

34. Mule Application
Mule 2 Application Design

35. Mule Scalability
• Global Enterprises
• Performance
• Multiple Data Locations, Sources,
Destinations and Owners
• Services
– Software as a Service
– Infrastructure as a Service
– Platform as a Service

36. Problems
• Performance
– Computation
– Latency
– Throughput
– Infrastructure
• Integration
– Adding Functionality
– Collecting Data
• Security and Identity
• Transactions

37. Transactions
• ACID
– Atomicity, Consistency, Isolation, Durability
• Easy on one system
• Hard with distributed systems
– Pick your boundaries
• Robust failure handling

38. Computation
• Parallel Processing
• Asynchronous Tasks
• Orchestration
– Workflow
• Pooling and Threading
• More and faster is better

39. Bottlenecks
• Bandwidth
– Networking
– Latency and Throughput
• External service providers
• Data sources
– Database
• Messaging

40. Messaging Backbone
• Sets scalability limits
• Message flow through system
• Infrastructure choices
– JMS
– Web based
– AMQP
– XMPP
– TIBCO
• Hardware solutions available

41. Clustering
• Various external components
– Database
– Messaging
– Web Services
• Business logic components
– Terracotta
– GigaSpaces XAP

42. Load Balancing
• Web Services
• Software
• Hardware
– XML Transformation
– SSL
• Round Robin

43. Questions?
Thanks for Listening
Andrew D Kennedy
grkvlt@apache.org