WebSphere Message Broker In Shared Runtime Environments

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TMM20: WebSphere Message Broker in TMM20: WebSphere Message Broker in Shared Runtime EnvironmentsShared Runtime Environments

Mårten Gustafson, ZystemsMårten Gustafson, Zystemsmarten.gustafson@zystems.semarten.gustafson@zystems.se

Introducing DataPower

Point to PointSpaghetti

MiddlewareAdoption

EAIFocusing onApplicationIntegration

ESBFocusing on

ReusableServices

BPMBusinessProcess

Management

Introducing DataPowerParts of an ICC Parts of an ICC (according to Zystems)(according to Zystems)

Communication

Delivery

GovernanceOperations ICC

Introducing DataPowerAgendaAgenda

Delivery

Governance

Operations

Introducing DataPower

Development Organizationsand their requirements on a shared runtime

Introducing DataPowerICC Organizational ModelsICC Organizational Modelsas defined by Schmidt & Lyle in “Integration Competency Center, An Implementation Methodology”as defined by Schmidt & Lyle in “Integration Competency Center, An Implementation Methodology”© 2005, Informatica© 2005, Informatica

Project silos

Best practices

Standard services

Shared services

Central services

Self-service

Introducing DataPowerTypical shared services ICCTypical shared services ICC

BU

Project /dev

team

BU

Project /dev

team

BU

Project /dev

team

BU

Project /dev

team

ICCGovernance Operations

Introducing DataPowerShared services runtimeShared services runtime

• CharacteristicsCentral operationsUsed by project teams from disparate

business units• Key things

IsolationAuditing/Monitoring

Introducing DataPowerICC Example - Customer Case 1ICC Example - Customer Case 1

• Shared Services ICC~10 headcount

Architects and managersOperations as a separate entity

~4 headcount~4 projects on their way into the runtime

Introducing DataPowerTypical central services ICCTypical central services ICC

BU BU BU BU

ICCDelivery

(project / dev team)Operations

Governance

Introducing DataPowerCentral services runtimeCentral services runtime

• Used only by the ICCCentral control within a closed team

• CharacteristicsCentral operationsUsed only by the ICCCentral control within a closed team

• Key thingsMessage tracing/trackingDevelopment guidelines/re-use/patterns

Introducing DataPowerICC Example - Customer Case 2ICC Example - Customer Case 2

• Central Services ICC~50 headcount

Developers, architects, process modelers, operations staff

~330 flowsFile transfer 48,5%Transformation 35,9%

Introducing DataPower

Introducing DataPower

Shared Runtime Environments

Introducing DataPower

Broker B

Typical environment configurationsTypical environment configurations

Broker A

Cluster or virtualization technique

WMQ cluster / HTTP load balancer

Introducing DataPowerQoS – Performance and QoS – Performance and AvailabilityAvailability

Cluster or virtualization technique

WMQ cluster + HTTP load balancer

High performance “zone”- Active/Active- Workload balancing- Continuous availability

Broker A

Low performance “zone”- One node- Failover delay

Broker C

Broker B

Introducing DataPower

Broker

Isolation / PartitioningIsolation / Partitioning

Broker

EGEG

EG

EG

EG

Introducing DataPower

Examples of real world environments

Introducing DataPowerCustomer example 1Customer example 1

MQcluster

Solaris zones + Veritas cluster

Broker A Broker B

GW QM

HTTP Load Balancer

Broker CDedicated, per project

Shared between projects

(preferred)

Broker CBroker … Broker …

Introducing DataPowerCustomer example 2Customer example 2

MQ cluster A

MQ cluster B

Broker B2

Broker B1Broker A1

Broker A2

GW QM1

GW QM2

Extranet DMZ Intranet

HT

TP

load balancer

HT

TP

load balancer

Introducing DataPowerCustomer example 3Customer example 3

LPARLPAR

AIX HACMP

Broker A Broker A

Introducing DataPowerCustomer example 4Customer example 4

MQcluster

Microsoft Cluster Services

Broker A Broker B

GW QM

Introducing DataPower

Active/Active Runtime Environmentsand Implications on Development

Introducing DataPowerStateState

Introducing DataPowerConcurrencyConcurrency

Introducing DataPowerHTTPHTTP

Broker A

HTTP load balancer

Broker B

?!

biphttplistener biphttplistener

SupportPac IE01

Introducing DataPowerSOAPSOAP

Broker BBroker A

WMQ cluster / HTTP load balancer

EG-embeddedlistener

EG-embeddedlistener

Introducing DataPowerHeads upHeads up

Introducing DataPowerTimers / SchedulesTimers / Schedules

Introducing DataPowerTCP/IP inputTCP/IP input

Introducing DataPower

Wrap up

Introducing DataPowerGeneral lack of data and best pracicesGeneral lack of data and best pracices

• Why is there so little data, patterns and practices available out in the “wild”?

In our experience Because the products “just work”

Both good and bad Good: products proven as very stable for mission

critical operation Bad: if you break new ground or think “outside the

box” there’s not much experience, best practices available, assets or patterns

Introducing DataPowerExamples of mission critical deploymentsExamples of mission critical deployments

• Manufacturing industry• Banking/Trading• Pension funds management• Construction

If the integration platform stop,the business stop

Introducing DataPowerShared runtime - Key takeawaysShared runtime - Key takeaways

• Isolate Execution Groups as the unit of isolation Examine your OS ability to limit resources for processes and/or users

• Automate Broker and EG creation

Permissions File system structures

Deployment Consider self-service deployment (at least for test/QA environments)

• Govern Development guidelines / harvest patterns / document key concepts Implementation patterns adapted to the runtime environment

Req/Rep, Pub/Sub, Fan in/out, Collection, FTP, File transfer etc Make sure the people responsible for governance participate in projects

themselves