Keynote at Depsa07 - architectural view of event processing

IBM Software Group – Event Processing technologies

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© 2007 IBM Corporation

IBM Software Group – Event Processing Technologies and Architecture

Event Processing in a nutshell

Event Processing Network – as main
abstraction

Architectural Principles

Producing and consuming the events

Processing the events

Some Non-Functional Issues

Concluding Remarks
Event-Driven Processing in IBM © 2007 IBM Corporation

Event Processing

Event Event
Producer Consumer

Generate and Consume and
may publish perform operations react to either
events on events raw or complex
events

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EDA Reference Architecture Overview

Event Event Business State
Services
Producer Sensors Processes Machines

Event Monitoring and Analytic Infrastructure
Event Consolidator

Event Security Services

Event Flow
Event
Event Bus
Processing
Network
Event Operator (Facilitator)

Event Event Business State
Services
Consumer Actuators Processes Machines

© 2003 IBM Corporation 5


Consumers

Producers Agents

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Consumers
Producers Agents

Transform validate

g

Retrospective pattern

if the customer has breached his credit limit the second time within the last 48
hours then divert the workflow based on policies that relate to the history of
credit violations in the last year.


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Consumers
Producers Agents

Detect Pattern

Enrich

g

If a customer sends three requests over the last hour on the same topic and
the requests have been handled, notify immediately to the “unhappy
customers officer” and include count of “unhappy” detections for this customer
in the last year


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Consumers
Producers Agents

Detect Pattern

Dynamic
Subscribe
g

I am interested to know whenever my investment portfolio is down 2 percent
within the last couple of hours

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Concluding Remarks
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Processor examples:
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Validate, transform, detect
pattern, derive, enrich

Selector Processor Router

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Event Processing Reference Architecture

EVENT
SOURCES
EVENT PRE- Event Processing (EP/CEP)
EXTERNAL PROCESSING

DISTRIBUTED
LEVEL ONE LEVEL TWO LEVEL THREE
LOCAL
EVENT SITUATION IMPACT
EVENT REFINEMENT REFINEMENT ASSESSMENT
SERVICES
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EVENT
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PROFILES
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DB MANAGEMENT
DATA
BASES
. Historical Profiles &
LEVEL FOUR Data Patterns
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OTHER
PROCESS
DATA
REFINEMENT

Adapted from JDL:
Steinberg, A., & Bowman, C., Handbook of Multisensor Data Fusion, CRC Press, 2001
21 © 2006 TIBCO Software Inc. All Rights Reserved. Confidential and Proprietary. 24

Summary of Event Processing (Event-Decision)
User Interface
Human visualization, interaction and situation management
Level 4 - Process Refinement
Decide on control feedback, for example resource allocation, event source and state
management, parametric and algorithmic adjustments
Level of Level 3 - Impact Assessment
Inference Impact assessment, i.e. assess impact on the basis of situation development, recognition
and prediction
Level 2 – Situation Refinement
High Identify situations based on events relations, relational state estimation, etc.
Level 1 – Event Refinement
Identify and track events based on association, filtering, joins, correlation etc.
Med Level 0 – Event Preprocessing
Cleansing of event-stream to produce semantically understandable data
Event Sources

Low

Reference: Bass, T., Processing Patterns for PredictiveBusiness™, March 2006.
22 © 2006 TIBCO Software Inc. All Rights Reserved. Confidential and Proprietary.

Overview

Event Data
publish Processing consume
Publication Consumption
(Publishers) Selection (Consumers*)
Correlation
Distribution

Applications Files/DBs Sensor Data Feeds Propagations

* Consumers can act as publishers

23

Event Data Processing

Event Data
Processing

Stream
Stream Select
Process
Compose Stream
Retain
Deliver/propagate
Stream Stream

Single or multiple steps
Local or distributed

24



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Concluding Remarks
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Keynote at Depsa07 - architectural view of event processing

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