This document provides an overview of Apache ActiveMQ, an open source messaging system. It discusses what ActiveMQ is, its basics like topics and queues, techniques for scaling such as vertical, horizontal and hybrid approaches, ensuring high availability, and its future direction with ActiveMQ Apollo. The presentation aims to explain how ActiveMQ works and how to configure it for different deployment needs.

1. Advanced Messaging with
Apache ActiveMQ
Bosanac Dejan
May 2011
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2. About me
 Bosanac Dejan
 Senior Software Engineer at FUSESource - http://
fusesource.com
 Apache ActiveMQ committer and PMC member
 Co-author of ActiveMQ in Action
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3. What we are going to cover?
 What is ActiveMQ
 The Basics
 Flow control
 Scaling
 High Availability
 Future
 Conclusion
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4. What is ActiveMQ?
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5. Apache ActiveMQ
 Apache ActiveMQ
• Leading Open Source messaging platform
• Supported Java Standards:
o JMS 1.1, J2EE 1.4, JCA 1.5 and XA
 Reliable, high performance messaging
• Out-performs many legacy proprietary message queues
• Configurable for many different deployments
 Multi-Protocol/Multi-Language Support
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6. Background
 ActiveMQ started in 2005 at CodeHaus
 Moved to Apache Software Foundation in 2006
 1,117,537 lines of code
 24 committers
 Now the most widely used open source messaging
system on the planet
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7. The Basics
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8. Messaging is
 Loosely coupled exchange of messages between
applications
 Location transparency
 Can be persistent or non-persistent
 Can be transactional
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9. Topics
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10. Topics
 One message goes to 0-to-many consumers
based on the current subscribers
 Think like mailing lists or discussion forums
 Ideal for publishing business events
 Distributed observer pattern
 Allows one part of your system to notify anyone
else who may be interested in an event
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11. Queues
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12. Queues
 Messages are load balanced across many consumers
 Each message goes to exactly one consumer
 Consumers compete for messages
 Its easy to browse and monitor queues
 Ideal for grid style applications
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13. Challanges
 Create a general messaging platform
 Support variety of use-cases
• Large number of clients
• Large number of destinations
• Slow consumers
 Provide enterprise feaures
• Security
• High availability
• Management
• etc
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14. Flow Control
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15. Flow Control - Why?
 Dealing with deep queues
 Dealing with slow consumers
 We want to prevent broker from being flooded with
messages
 We want to prevent broker running out of memory and
other resources
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16. Flow Control - How?
 Message Cursors
 Producer Flow Control
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17. Flow Control - Cursors
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18. Flow Control - Store-based Cursor
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19. Flow Control - Non-persistent cursor
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20. Flow Control - Limits
Per destination
<destinationPolicy>
<policyMap>
<policyEntries>
<policyEntry queue=">" memoryLimit="10mb"/>
</policyEntries>
</policyMap>
</destinationPolicy>
System settings
<systemUsage>
<systemUsage>
<memoryUsage>
<memoryUsage limit="256 mb" />
</memoryUsage>
<storeUsage>
<storeUsage limit="100 gb" />
</storeUsage>
<tempUsage>
<tempUsage limit="10 gb" />
</tempUsage>
</systemUsage>
</systemUsage>
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21. Flow Control - Producer Flow Control
 Throttling producer speed to the speed of consumers
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22. Flow Control - VM Cursor
<policyEntry queue=">" producerFlowControl="true" memoryLimit="1mb">
<pendingQueuePolicy>
<vmQueueCursor/>
</pendingQueuePolicy>
</policyEntry>
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23. Scaling
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24. Scaling - Types
 Vertical scaling
 Horizontal scaling
 Traffic partitioning
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25. Vertical Scaling
Increase load capacity using a single broker can handle.
Problems:
• Thread count
• Memory usage
• CPU usage
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26. Vertical Scaling - Threads
What are threads used for
• For Connections - Thread per Connection (blocking transport)
• For Dispatching - Thread per Destination
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27. Vertical Scaling - Number of Connections
Use non-blocking transport
<transportConnectors>
<transportConnector name="nio" uri="nio://0.0.0.0:61616"/>
</<transportConnectors>
Enables handling large number of clients
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28. Vertical Scaling - Number of Destinations
Don’t use dedicated task runner
ACTIVEMQ_OPTS="-Dorg.apache.activemq.UseDedicatedTaskRunner=false"
Use optimized dispatch for queues
<destinationPolicy>
<policyMap>
<policyEntries>
<policyEntry topic=">" optimizedDispatch="true">
...
</policyEntry>
</policyEntries>
</policyMap>
</destinationPolicy>
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29. Vertical Scaling - Memory
 Give broker enough memory
ACTIVEMQ_OPTS="-Xmx2048M -Dorg.apache.activemq.UseDedicatedTaskRunner=false"
 Configure big enough memory usage
<systemUsage>
<systemUsage>
<memoryUsage>
<memoryUsage limit="1024 mb" />
</memoryUsage>
...
</systemUsage>
</systemUsage>
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30. Vertical Scaling - CPU
 Disable tight encoding
It uses more CPU to create smaller packets
uri = "failover://(tcp://localhost:61616wireFormat.tightEncodingEnabled=false)";
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31. Vertical Scaling - Conclusion
There is a limit to the scalability a single machine can
give
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32. Horizontal Scaling
Increase load capacity using networked brokers
Concepts:
 Network of Broker
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33. Horizontal Scaling - Network of Brokers
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34. Horizontal Scaling - NOB Usage
Configuration
<networkConnector name="broker1-broker2"
uri="static:(tcp://broker2:61617)"
dynamicOnly="true"
prefetchSize="1000"
conduitSubscriptions="true"
decreaseNetworkConsumerPriority="true"
suppressDuplicateTopicSubscriptions="true"
networkTTL="3">
</networkConnector>
Connecting
failover://(tcp://broker1:61616,tcp://broker2:61616)?randomize=true
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35. Horizontal Scaling - Conclusion
 More latency in processing messages
 Beware of complex topologies
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36. Hybrid Scaling
Partition traffic to more non-connected brokers
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37. Hybrid Scaling - Conclusion
 Pros
• You can use all the tuning techniques used in Vertical scaling
• Have better Horizontal scaleability than using Network Of
Brokers (Less broker cross talk)
 Cons
• Added complexity required on the end user Application
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38. High Availability
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39. High Availability
 Pure Master/Slave
 JDBC Master/Slave
 Shared File System Master/Slave
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40. Pure Master-Slave
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41. Pure Master-Slave
 Shared nothing
 Fully replicated
• All messages
• All acknowledgements
• All transactions
 Slave does not start any transports or network
connections
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42. JDBC Master-Slave
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43. JDBC Master-Slave
 Extreme reliability – but not as fast
 Recommended if already using an enterprise database
 No restriction on number of slaves
 Simple configuration
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44. Shared Storage Master-Slave
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45. Shared Storage Master-Slave
 Recommended if you have a SAN
 No restriction on number of slaves
 Simple configuration
 N.B. – ensure file locking works – and times out – NFSv4
good!
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46. Future
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47. Future - ActiveMQ Apollo
 http://activemq.apache.org/apollo
 ActiveMQ 5.x reached scalability and performance
limits with the current architecture
 New broker core
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48. Future - ActiveMQ Apollo
 Reactor Based Thread Model
 Scala 2.8 Implementation
 Protocol Agnostic
 REST Based Management
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49. Future - ActiveMQ Apollo Performance
http://hiramchirino.net/blog
10 producers/10 consumers
single topic
using Stomp
20 byte payload
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50. Conclusions
 Dynamic community
 Leading in terms of messaging innovation
 Built for Enterprise
 Scalable, Good Performance, Reliable
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51. Questions?
 ActiveMQ Web sites:
• http://activemq.apache.org/
• http://fusesource.com/products/enterprise-activemq/
 Blog:
• http://www.nighttale.net/
 Twitter:
• http://twitter.com/dejanb
• http://twitter.com/fusenews
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