2. OEP BOF9272 SOA Event Delivery Network
empowered by Fast Data
Simone Geib
Director of Product Management
Service Integration
Lloyd Williams
Principal Product Manager
Business Integration
September 30, 2014
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4. Agenda Oracle Event Processing (OEP) Product Overview
Event Delivery Network (EDN) Overview
OEP & SOA EDN
Demo: Service Request SLA Monitoring
Demo: Wire Transfer Fraud Monitoring

5. Oracle Event Processing Applications

6. Connecting the Internet-of-Things to Your Enterprise
Oracle Event Processing: From Noise to Value
Internet of Things
SOA / Enterprise
High Volume
Continuous Streaming
Sub-Millisecond Latency
Disparate Sources
Time-Window Processing
Pattern Matching
High Availability / Scalability
Unique Coherence Integration
Geospatial, Geo-fencing
Big Data & IoT Integration
Action!
Devices / Gateways
SOA
OEP
OEP
OEP
embedded
Distributed Intelligence
Filtering
Correlation
Aggregation
Pattern matching
Macro-event
High-value
Actionable
In-context
“Sea of data”

7. Modern Computing Challenges
Conditions for Event Processing
Does the problem have any one or more of the following conditions:
Requires high-throughput and low latency processing
Continuously streaming data
Real-Time correlation between multiple incoming data sources
Time-sensitive alerts, aggregations and calculations
Patterns in the data stream
Problem is more easily solved by analyzing before storing in DB
Data does not need to be stored, if there is nothing of interest in it
Does the problem you want to solve have any one or more of the following conditions?
Requires high-throughput and low-latency processing
Continuously streaming data
Real-time correlation between multiple incoming data sources
Time-sensitive alerts, aggregations and calculations
Needs to look for patterns in the data stream
Data does not need to be stored, if there is nothing of interest in it
Problem is more easily solved by analyzing before storing in DB

8. Solution Product Overview
Oracle Event Processing
Streaming Event Data
Solution involves one or more of the following:
High Volume
Continuous Streaming
Sub-Millisecond Latency
Disparate Sources
Time-Window Processing
Pattern Matching
Business Event Visualization
OEP
Filtering,
Pattern Matching,
Missing Events,
Aggregations,
Correlations, Calculations,
Geo-Spatial
Alerts, Actions

9. Oracle Event Processing (OEP)
High-Volume, Low-Latency Event Processing Infrastructure
Time-Sensitive Processing & Pattern Matching
Light-weight Java Application Server
Deploy in Data Center or Distributed Locations

10. Solution Overview Time Management & Pattern Matching
Continuous Query Language (CQL)
Pattern Matching
Detect Absence of Events & Missing Events
Event “A” NOT followed by Event “B” within 10 minutes
Event “A”, Event “B” should occur next, but Event “C” occurs instead.

11. Oracle Event Processing ApplicationDB
Business Logic
(CQL)
Output Adapter
Channel
Input Adapter
Channel
Business Logic
(CQL)
Channel
Input Adapter
Channel
CQL processors contain filtering, correlation, aggregation and pattern matching business logic
Output Adapter
Business Logic
(CQL)
Channel
Channels help control the flow of data and can be tuned for optimal performance
Input adapters connect to data sources
Output adapters send data and alerts to downstream systems and business processes
Big Data
Coherence
Databases, Coherence caches, Hadoop (HDFS) and NoSQL database can be referenced directly in CQL processors 11

12. High-Performance In-Memory Data Processing
Input Adapter
Data
Data
Channel
Data
Business Logic
(CQL)
Business Logic
(CQL)
Output Adapter
Analytics
Data
Channel
Data
Enrich
Data
Data
Data
Input Adapter
Data
Data
Data
Channel
Analytics: Continuously Sliding Windows of Streaming Data, Filtering, Correlations, Calculations, Aggregations, Pattern Matching, Missing Event Detection, Spatial Analysis, etc.
Enrichment: Integrate with data from DB, Coherence, NoSQL, Hadoop etc.
Oracle Event Processing

13. Oracle Event Processing 12c
What’s new? 1 2
New development environment (JDev)
Big Data extensions
Coherence Integration enhancements
Library of patterns to choose from (ex: missing event rule)
Easily connects with SOA infrastructure through EDN 3 4 5

14. Event Delivery Network (EDN)
Easy integration for event driven patterns
Provides a declarative way to generate and consume business events
Business events are managed by the event engine
Publishers and subscribers only need to know event name, and data format
Configuration of queues and topics and any associated filters is hidden
Delivery details hidden under the covers
SOA composite
newSupplier event
OEP
Subscribe/Publish
EDN T T T T T T
Scalable
Store & Forward
Durable
Reliable
JMS

15. Event Delivery Network (EDN)
Wizard driven approach to create typed event definitions
Browse and choose events for subscription/publication
Easy mapping of event types to topics from EM FMWC
Support for JMS and AQ
Leverages durable, reliable and store/forward features of JMS

16. SOA Event Delivery Network & OEP
Integrate SOA Composite Architecture with OEP Event Processing Networks

17. SOA Composite vs. OEP Application
Request
SOA Composite Instances
Request
SUM, AVG, etc.
OEP
OEP Application
Event Data
Event Data
Pattern Match

18. Demo Service Request SLA Monitoring
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19. SOA Composite with Event Delivery Network (EDN)

20. OEP Application Receiving Events From EDN

21. Service Request Process Customer-specific SLA Times
Service Request Status = ‘OPEN’
Oracle SOA Infrastructure
Oracle Business Activity Monitoring
Oracle User Messaging Service
Action!
Service Request Status = ‘CLOSED’
SLA Alert!
EDN
Was the service request completed in time?
Oracle Event Processing
Oracle Coherence
CQL
Pattern Matching
Customer-specific SLA Times

22. SOA Composite vs. OEP Application
Service Request Status = ‘OPEN’
SOA Composite Instances
Service Request Status = ‘CLOSED’
Pattern Match
OEP
OEP Application
SLA Alert!
CLOSED
OPEN

24. Demo Wire Transfer Fraud Check
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25. SX: Empower Business Users for Real-Time Streaming Data Analytics
Fast exploration of Real Time Streams
Fast definition & re-use of Real Time Event Patterns
Fast Testing and Deployment of Projects
Simple but powerful visual façade tooling abstracting for a general audience (business users) an underlying comprehensive, Lightweight, Low Latency, Extreme High Throughput capable, scalable OSGi Java-based Run Anywhere, Application Development & Deployment Event Server Platform technology
Sparc T5 benchmark released in August 2014
Streaming Event-Driven Architecture (EDA) , Server Platform

26. Stream Explorer Features for Business Users
Explorer: The application User Interface

27. Stream Explorer Features for Business Users
Catalog: The repository for browsing resources

28. Stream Explorer Features for Business Users
Exploration: An application that correlates events from streams, data from data sources, even other Explorations. It uses filters, groupings, summaries, ranges, and more to Identify, Qualify and Expose a Real Time Business Solution.

29. Stream Explorer Features for Business Users
Pattern: A pre-built Exploration that addresses a particular business scenario in a focused and simplified User Interface

30. Stream Explorer: Empowers Business Users for Real-Time Streaming Data Analytics and IOT
Proactively identify and act on emerging threats and opportunities in the Streaming data related to your enterprise
Improve operational efficiencies with actionable insight from real-time information
Improve signal-to-noise ratio by only processing and storing data that is relevant
Build real-time applications in half the time and with no complexity
Business Applications, SOA Infrastructure, Social media outlets & M2M sensors/devices/gateways
Reusable general purpose & industry specific solution templates
Completely modifiable, flexible, extensible business definitions
, the Continuous Query Language (CQL) or the semantics of Event Stream Processing Application Models
Augment solution applications with comprehensive development tooling (if needed)

31. Wire Transfer Fraud Demo
Check to see if someone is receiving multiple wire transfers in small amounts within a few hours to try to avoid detection.
Crosses multiple SOA composite instances.
Simple example to demonstrate the EDN – OEP Stream Explorer integration.

32. SOA Composite vs. OEP Application
Wire Transfer 1 $8000
Wire Transfer 2 $9000
WT 1
WT 2
> $50,000 received in 3 hours

33. When to Use OEP? 1
Business Logic Layer for Event-Driven Coherence Applications 2
High-Volume Business Activity Monitoring Applications 3
Real-Time Spatial Applications 4
Fast Data: Real-Time Requirements with Big Data Infrastructure 5
High Volume Batch to Real-Time Conversion Projects 6
Internet of Things (IoT): Processing Data On and From Devices 7
Pattern Matching / Missing Events / Alerting / Fraud Detection

34. Oracle Event Processing (OEP)
High-Volume Low-Latency Event Processing Infrastructure
Event Processing Network (EPN)
Light-weight Java Application Server (embeddable)
Easily Customizable
Integrate with existing infrastructure and other Oracle Products (e.g. Coherence, BAM, RTD, Database, Big Data, Data Mining, Spatial, NoSQL Database etc.)
Time Management & Pattern Matching
Continuously Perform Calculations Over Time Windows or Number of Events
Partition Event Streams By Key Values
Perform Complex Pattern Matching
Adjust Core Business Logic in Real-time without Redeploying 34