This document provides an overview of designing a scalable and highly available IBM MQ infrastructure. Key points include: - Using a client/server architecture with MQ deployed separately from applications provides flexibility and allows MQ to be treated as critical infrastructure similar to a database. - Each sender should connect to two queue managers and each receiver should have two listeners concurrently attached to provide redundancy and no single point of failure. - Other topics covered include synchronous request/response, publish/subscribe messaging, limitations for ordered messages, and integrating with IBM Integration Bus. The document emphasizes an active/active design philosophy with minimum two queue managers and discusses workload management strategies for sending and receiving messages across multiple queue managers.

1. © 2014 IBM Corporation
Building a Scalable &
Continuously Available
IBM MQ Infrastructure
AMC-1882

2. Please Note
IBM’s statements regarding its plans, directions, and intent are subject to change
or withdrawal without notice at IBM’s sole discretion.
Information regarding potential future products is intended to outline our general
product direction and it should not be relied on in making a purchasing decision.
The information mentioned regarding potential future products is not a
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functionality. Information about potential future products may not be incorporated
into any contract. The development, release, and timing of any future features or
functionality described for our products remains at our sole discretion.
Performance is based on measurements and projections using standard IBM
benchmarks in a controlled environment. The actual throughput or performance
that any user will experience will vary depending upon many factors, including
considerations such as the amount of multiprogramming in the user’s job stream,
the I/O configuration, the storage configuration, and the workload processed.
Therefore, no assurance can be given that an individual user will achieve results
similar to those stated here.

3. Introduction
Article series describing one possible MQ topology as a pattern
• ibm.co/1cz0MrL
Why?
• Make it easier to include MQ in a project
• Help meet ‘five nines’ or ‘continuous’ availability via a standard approach
• Help MQ admin teams do more with less through consistency
• Provide config and code samples to get started quickly in a DevOps culture
The approach is client/server, why?
• Applications increasing have a large number of instances
• Application instances come and go
• MQ should be seen as critical infrastructure, similar to a Database
• Provisioning and scaling MQ separately from the app gives flexibility
How many ‘hubs’ of MQ could you have?
• In general continue to provision MQ on a per-project basis – just like a DB
• Some sharing/multi-tenancy is likely based on risk assessment – just like a DB

4. MQ Cluster
Workload Balancing
MQ Cluster
Workload Balancing
Overview – architecture view
Every sender/requester uses two connections
Every receiver/service has two listeners
Make each Queue Manager HA to recover persistent messages
Simple to interoperate with co-located Queue Managers
Simple to interoperate with z/OS Queue Sharing Groups
Pattern discussed in detail here: http://ow.ly/vrUUV
App1 QM1App1 QM1
App1
QM2
App1
QM2
App2 QM1App2 QM1
Shared QM1Shared QM1
Shared QM2Shared QM2
App1 Inst1App1 Inst1
App1 Inst2App1 Inst2
App1 Inst3App1 Inst3
App1 Inst4App1 Inst4
App2 Inst1App2 Inst1
App2 Inst2App2 Inst2
App2 Inst3App2 Inst3
App2 Inst4App2 Inst4
App2 QM2App2 QM2
App2 QM3App2 QM3
App2 QM4App2 QM4
App1 Inst1App1 Inst1
App1 Inst2App1 Inst2
App1 Inst3App1 Inst3
App1 Inst4App1 Inst4
App2 Inst1App2 Inst1
App2 Inst2App2 Inst2

5. Overview – infrastructure view
Principal design philosophy is active/active
• Continuous availability of the service
Minimum number of queue managers is 2
• Sending and receiving gateway roles can be fulfilled by the same qmgr
HA failover is optional
• If you have persistent messages that you need to recover quickly after a failure
MQ1
Standby
MQ2
Standby
Machine 1 Machine 2
HA failover
HA failover
MQ2
(Sending &
Receiving GW)
MQ1
(Sending &
Receiving GW)
Highly available
network-attached
file-system
MQ Hub
Senders Receivers

6. Overview – 2 is the magic number
Every sender sends to two queue managers
• No single point of failure for sending messages
• Not too many places to look for messages
Every receiver listens to two queue managers concurrently
• Every queue manager has two app instances listening for messages
• Every app instance listens to two queue managers
• Note: cannot have more receiving gateways than receiving app instances
No single point of failure
• Any single component can fail, and all other components continue processing
MQCluster
Receiver 1
Receiver 2
Receiver 3
Receiver 4
Sender 1
Sender 2
Sender 3
Sender 4
Sender 5
Sender 6
Sender 7
Sender 8
MQ
Gateway 1
MQ
Gateway 2
MQ
Gateway 3
MQ
Gateway 4
MQ
Gateway 5
MQ
Gateway 1
MQ
Gateway 2
MQ
Gateway 3
MQ
Gateway 4
MQ
Gateway 5

7. Sending messages
Each app instance sends to two different queue managers
Need a workload management strategy
• Prioritised
• Random
• Round robin – my personal preference
Biggest practical concern for customers:
How do I create/change my app code to connect
to two different remote queue managers
Sending
application
Connection
logic
(CCDT or
custom)
Sending
Gateway 1
Sending
Gateway 2
MQ connection 1
MQ connection 2
MQCluster

8. Sending messages – choices for multi-QM client attachment
CONNAME list CCDT (multi-QMGR) Load balancer Code stub
Scale of code change
required for existing
apps that connect to a
single QM
+ive
MQCONN("QMNAME") to MQCONN("*QMNAME")
QMName might be in JNDI config for Java EE apps.
Otherwise requires a one character code-change.
-ive
Replace existing JMS/MQI
connection logic with code
stub.
Support for different
WLM strategies
-ive
Prioritized only
=
Prioritized + Random
+ive
Any, including per-
connect round-robin
+ive
Any, including per-
message round-robin.
Performance
overhead while
primary QM is down
-ive
Always tries first in
list
+ive
Remembers last good
+ive
Port monitoring
avoids bad QMs
+ive
Can remember last good,
and retry intelligently
XA Transaction
Support
-ive
The transaction manager needs to store recovery information that
reconnects to the same QM resource. An MQCONN that resolves to
different QMs generally invalidates this. e.g. in Java EE, a single
Connection Factory should resolve to a single QM when using XA.
+ive
Code stub can meet the
XA transaction manager’s
requirements. e.g.
multiple Connection
Factories.
Connection
rebalancing on
failback.
e.g. when a QM
restarts after a failure
or planned outage,
how long till apps
use it again
-ive
Connection pooling in Java EE will hold onto connections indefinitely,
unless connections are configured with an aged timeout. Using an aged
timeout might drive exceptions in some cases. An aged timeout also
introduces a performance overhead during normal operation.
Conversation sharing might need to be disabled (SHARCNV=1) with an
aged timeout to ensure reconnects always establish a new socket.
The ‘remembers last good’ CCDT behaviour might also delay failback.
+ive
Code stub can handle
failback flexibly, with
little/no performance
overhead.
Admin flexibility to
hide infrastructure
changes from apps
-ive
DNS only
=
DNS and/or shared file-
system / CCDT file push
+ive
Dynamic Virtual IP
address (VIP)
=
DNS or single-QMGR
CCDT entries
More detail on MQDev here: http://ibm.co/MM8rMl

9. Receiving messages
The application needs two active listeners
• Random/prioritised attachment can lead to stranded messages
• AMQSCLM is an alternative - discussed in AMC-1883
For Java EE this means two MDB endpoints
• EJB 2.1 style deployment descriptors
– Add a second endpoint to the XML
• EJB 3.0 style annotations
– Create a code hierarchy
EJB 2.1 & 3.0 samples on github:
https://github.com/ibm-messaging/mq-wlm-client
Receiving
application
Active
Active
MQ Listener 1
MQ Listener 2
MQCluster
Receiving
Gateway 1
Receiving
Gateway 2

10. Synchronous request/response
Response 1
Requester
application
Connection
logic
(CCDT or
custom)
MQ 1
MQ 2
MQ connection 1
MQ connection 2
MQCluster
Request 1
Response 2
Request 2
Use same MQ connection to receive the response
• e.g. the same JMS Session
MQ fills in the MQMD.ReplyToQMgr on send
• Back-end app must honour this when sending the response

11. Synchronous request/response – advanced case
A clustered reply queue for synchronous request/response
• Lets replies take a different route back from requests
• Only adds resilience for highly parallel nonpersistent request/reply, where requests
build up on back-end threads in business logic rather than in MQ
Requires correlation logic to pass responses back to waiting threads
This is not the same as two-way asynchronous messaging
Code samples: https://github.com/ibm-messaging/mq-wlm-client

12. Asynchronous
Receiver
Two-way asynchronous messaging
The optimal use of messaging is fully asynchronous
Requests are sent “fire & forget”, as are responses
• Critical requests are sent as persistent within a transaction that updates a DB
• Transactional state update + persistent send = exactly once delivery
Responses are handled by any app instance at any time
• No thread is left ‘hung’ in the requesting application
• If responses need to be correlated with requests, then a state store is used
– A Database – DB2 etc.
– An elastic cache – WebSphere eXtreme Scale
Must be designed into the application
• Can revolutionize responsiveness
• Truly decouples applications
Receiving
application
Active
Active
MQ Listener 1
MQ Listener 2
MQCluster
Receiving
Gateway 1
Receiving
Gateway 2
Fire &
Forget
Requester
CCDT
or custom
Sending
Gateway 1
Sending
Gateway 2
MQ connection 1
MQ connection 2
MQ Listener 1
MQ Listener 2
50% requests
50% requests
50% responses
50% responses

13. Publish/subscribe messaging
MQ gives the same QoS for pub/sub as for P2P
• Fan out messages one-to-many
• WLM across multiple subscriber instances
Achieved by bridging durable subscriptions to cluster queues
• Define subscriptions on queue managers where publishers
connect
Sub1 Inst1
Sub1 Inst2Pub Inst1
Pub Inst2
QM1
QM2
QM3
QM4
Pub/SubFan-Out
+MQClusterWLM
Sub2 Inst1
Sub2 Inst2
QM3
QM4

14. Limitations for message ordering
No active/active solution is provided here for ordered messages
• MQ only assures order when there is one path from
producing thread to consuming thread
The simplest solution, and as far as this presentation goes
• Allocate individual queue managers with HA Failover for ordered messages
MQ
Gateway 1
MQ
Gateway 2
MQ
Gateway 1
MQ
Gateway 2
MQ
Gateway N1
MQ
Gateway N2
MQ
Gateway N1
MQ
Gateway N2
Receiver 1
Receiver 2
Receiver 3
Receiver 4
Receiver N1
Receiver N2
Receiver N3
Receiver N4
Sender 1
Sender 2
Sender 3
Sender 4
Sender N1
Sender N2
Sender N3
Sender N4
MQClusterWorkloadManagement
..
.
..
.
..
.
..
.
Sender
Sending
gateway
Receiving
gateway
Receiver
Can be the same queue manager.
Might be in different hubs.

15. Including IBM Integration Bus
The architecture fits IBM Integration Bus
• Option 1: Add it as a separate tier
• Option 2: Compress everything into a single active/active IIB tier
For more on IIB architectures, try the following link (plug):
ibm.co/1a2Y2os
MQ
GW1
MQ
GW2
Receiver 1
Receiver 2
Receiver 3
Receiver 4
Sender 1
Sender 2
Sender 3
Sender 4
Sender
Sending
gateway
Receiving
gateway
Receiver
MQ
GW1
MQ
GW2
Integration
Node 1
Integration
Node 2
Routing
& filtering
MQCluster
MQCluster
Can be same the queue manager

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