An Introduction to the Message Queuing Technology & IBM WebSphere MQ

1. An Introduction to the Message Queuing
Technology & IBM WebSphere MQ
Ravi Yogesh
Web Performance Engineer, Wells Fargo
(https://www.linkedin.com/in/raviyogesh)

2. Agenda:
 Basics of MQ Technology
(Persistence, Types, Styles)
 Message Queuing in Banking
 Different Message Queuing Implementations
 In Focus : IBM WebSphere MQ
 Message Queues in Action around Us

3. MQ Technology: Basics
• Message queuing is a middleware technology that greatly simplifies
communication between the nodes of a system and between the nodes that
connect systems together.
• This technology builds on two basic concepts:
Message : String of Bytes/Information that needs to be communicated from one
node to another.
Has two parts : Header (message ID, message type, priority, expiration time )
and Data (can be XML, binary data etc)

4. Queues : Data Structures used to store messages.
• They enable applications and services to communicate asynchronously,
without each having to be available at the same time.
• When both nodes are available, messages arrive at destination in near real
time.
• If either of the network or node is unavailable/busy, the queue holds the
messages until they can be received and processed, thus assuring
delivery.

5. Message Persistence:
• Persistent messages are logged (data synchronously written to disk at the
same time as sending) thus enabling recovery of message on failure.
• Semi Persistent Messaging : Tradeoff between robustness of delivery and
throughput- logging occurs asynchronously after message dispatch- faster but
riskier than persistent mode.
• Non persistent Messaging : No logging thus no recovery on failure !!
• Recovery , persistence and assured delivery of messages : handled by the
Queue Managers which are themselves backed up in high availability
environments.

6. Types of Queues:
Remote Queues: References/handles to queues residing on other machines.
Transmission Queues: Special Queues used internally to move messages across
a network.
Dynamic Queues: Local Queues created on demand.
Dead Letter Queues: Queues that store messages that can not be delivered
(destination queue full scenario).
Repository Queues: Queues holding clustering information.

7. Messaging Topology:
Point to Point : Useful for simple
scenarios and NOT for larger
deployments because of the large
number of connections required.
{n(n-1)/2}.
Hub and Spoke: Requires more
initial planning but much lesser
number of connections for the
same number of nodes. Single
point of failure exists !
Bus: Same number of connections
as Hub and Spoke with distributed
connectivity logic across the
backbone. Thus, no single point of
failure.

8. Messaging Styles:
• Fire & Forget: Sender does not need a confirmation from receiver.
• Request - Response: Replies need to be sent from receiver.
• Publish & Subscribe: Event driven style of messaging, backbone
dynamically determines where the messages have to be delivered, relives
applications and services of information burden.

9. Benefits of Message Queuing Technology in Banking:
• Letting the applications talk to the messaging backbone through a
simple common API saves a lot of complex and application specific
connectivity logic to be defined on each application.
• Assured delivery: Critical business information like a banking
transaction needs assured and only-once delivery.
• Time-independent (asynchronous) processing.
• Avoids redundancy and duplication of data.
• Can easily scale and adapt to business requirements change.

10. Message Queuing Implementations:
 Proprietary software:
• Microsoft Message Queuing (tied to specific operating system).
• IBM's WebSphere MQ.
 Message Queuing as a Service:
• StormMQ
• IronMQ
• Amazon SQS.
 Open Source Software:
• JBoss Messaging
• JORAM
• Apache ActiveMQ
• Sun Open Message Queue
• Apache Qpid
• RabbitMQ,
• Beanstalkd,
• Tarantool
• HTTPSQS

11. Queuing Solutions on the Cloud:
Amazon Simple Queue Service (Amazon SQS):
A distributed queue messaging service introduced by Amazon.com in April
2006.
Storm MQ: available as hosted, On-Premise or Cloud solution for
Machine-to-Machine Message Queuing using the standard Advanced
Message Queuing Protocol (AMQP).
Rabbit MQ : open source software that implements the AMQP & is written
in the Erlang programming language.

12. In Focus : IBM MQ WebSphere
WebSphere MQ moves more than 10 billion messages every day,
supporting more than US$1 quadrillion (US $1 000 000 000 000 000)
worth of business transactions !!
• launched by IBM in March 1992
• available on a large number of platforms (both IBM and non-IBM),
including z/OS (mainframe), OS/400 (IBM System i or
AS/400), Transaction Processing Facility, UNIX (AIX, HP-UX, Solaris),
HP NonStop, OpenVMS, Linux, OS 2200, and Microsoft Windows.

13. Message Handling in Websphere MQ:
• Each WebSphere MQ message can be up to 100 MB in size.
• Larger messages and files can be transported by segmenting them into
smaller chunks.
• Messaging traffic can be reduced when many very small
messages are being sent to the same destination by grouping these
together into larger WebSphere MQ messages.
• By default, WebSphere MQ uses persistent messaging.
• WebSphere MQ can preserve the order of messages, delivering them to
applications in the same order as they were dispatched. First-In-First-Out
(FIFO) is the default.

14. Clustering
• Enables to improve the performance of a messaging backbone, more
messaging engines to be added as needed.
Scalability
• WebSphere MQ takes advantage of multiprocessor and multicore
machines so that you can scale your messaging backbone by using
parallel processing to accelerate messaging.
Security
• Supports the industry standard Secure Sockets Layer (SSL) for strong
authentication of message channels before messages are exchanged to
help prevent malicious attacks to the backbone.

15. Message Queuing is Ubiquitous !
Twitter : Open Source Message Queue Service: Kestral
https://blog.twitter.com/2009/building-open-source
Whatsapp and Facebook : Messaging Cluster based on XMPP
(Extensible Messaging and Presence Protocol) and Erlang Programming
Language.
http://www.erlang-factory.com/upload/presentations/558/efsf2012-whatsapp-scaling.pdf

16. References:
• http://www.redbooks.ibm.com/redbooks/pdfs/sg247128.pdf
• ftp://ftp.software.ibm.com/software/integration/wmq/WS_MQ_Messaging_Backbone_for_SOA.pdf
• http://blog.codepath.com/2013/01/06/asynchronous-processing-in-web-applications-part-2-
developers-need-to-understand-message-queues/
• http://www.infoq.com/articles/AMQP-RabbitMQ