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OEP BOF9272 SOA Event Delivery Networkempowered by Fast Data
Simone GeibDirector of Product Management Service Integration
Lloyd WilliamsPrincipal Product ManagerBusiness Integration
September 30, 2014
Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |
Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | 3
Safe Harbor StatementThe following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle.
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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
Copyright © 2014, Oracle and/or its affiliates. All rights reserved. | 5
Oracle Event Processing Applications
Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |
OEP
Oracle Event Processing: From Noise to ValueConnecting the Internet-of-Things to Your Enterprise
Distributed Intelligence
• Filtering• Correlation• Aggregation• Pattern matching
Devices / Gateways
SOA
Internet of Things SOA / Enterprise
“Sea of data”
Macro-eventHigh-valueActionableIn-context
OEPembeddedOEP
• 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!
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Modern Computing Challenges
Does the problem have any one or more of the following conditions:① Requires high-throughput and low latency processing② Continuously streaming data③ Real-Time correlation between multiple incoming data sources④ Time-sensitive alerts, aggregations and calculations⑤ Patterns in the data stream⑥ Problem is more easily solved by analyzing before storing in DB⑦ Data does not need to be stored, if there is nothing of interest in it
Conditions for Event Processing
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Oracle Event ProcessingSolution Product Overview
Solution involves one or more of the following:High VolumeContinuous StreamingSub-Millisecond LatencyDisparate SourcesTime-Window ProcessingPattern MatchingBusiness Event Visualization
OEP
Streaming Event Data
Alerts, Actions
Filtering,Pattern Matching,Missing Events,Aggregations,Correlations, Calculations,Geo-Spatial
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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
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Solution OverviewTime Management & Pattern Matching
Event “A” NOT followed by Event “B” within 10 minutes Event “A”, Event “B” should occur next, but Event “C” occurs instead.
Pattern Matching
Detect Absence of Events & Missing Events
Continuous Query Language (CQL)
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Input Adapter
Channel
Input Adapter
Channel
Business Logic
(CQL)
Channel
Channel
Channel
Output Adapter
Output Adapter
Oracle Event Processing Application
DB
Input adapters connect to data sourcesChannels help control the flow of data and can be tuned for optimal performanceDatabases, Coherence caches, Hadoop (HDFS) and NoSQL database can be referenced directly in CQL processorsCQL processors contain filtering, correlation, aggregation and pattern matching business logicOutput adapters send data and alerts to downstream systems and business processes
Business Logic
(CQL)
Business Logic
(CQL)
Big Data
Coherence
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High-Performance In-Memory Data Processing
Input Adapter
Data
Input Adapter
Data
ChannelBusiness
Logic (CQL)
Channel
Data
Data
Data
Data
Analytics ChannelBusiness
Logic (CQL)
EnrichOutput Adapter
Data Data
Data
Data Data
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
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What’s new?
Oracle Event Processing 12c
① New development environment (JDev)② Big Data extensions③ Coherence Integration enhancements④ Library of patterns to choose from
(ex: missing event rule)⑤ Easily connects with SOA infrastructure
through EDN
1
4
5
2
3
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Event Delivery Network (EDN)
SOA composite
newSupplier event
Store &
Forward
Durable
ReliableJMS
Subscribe/Publish
• 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
EDN
OEP
Scalable
T T T T T T
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• 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
Event Delivery Network (EDN)
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SOA Event Delivery Network & OEPIntegrate SOA Composite Architecture with OEP Event Processing Networks
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SOA Composite vs. OEP Application
Request
Request
Event Data Event Data
SUM, AVG, etc.
Pattern Match
SOA Composite Instances
OEP Application
SOA
OEP
18Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |
Service Request SLA Monitoring
Demo
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SOA Composite with Event Delivery Network (EDN)
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OEP Application Receiving Events From EDN
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Oracle SOA Infrastructure
Oracle Event Processing
Oracle Coherence
EDN
Pattern Matching
Customer-specific SLA Times
Service Request Process
Oracle Business Activity Monitoring
SLA Alert!
Action! Oracle User Messaging
Service
Service Request Status = ‘OPEN’
Service Request Status = ‘CLOSED’
Was the service request completed in time?
CQL
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SOA Composite vs. OEP Application
Service Request Status = ‘OPEN’
Service Request Status = ‘CLOSED’
CLOSED OPEN
Pattern Match
SOA Composite Instances
OEP Application
SOA
OEPSLA
Alert!
24Copyright © 2014, Oracle and/or its affiliates. All rights reserved. |
Wire Transfer Fraud Check
Demo
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• Fast exploration of Real Time Streams
• Fast definition & re-use of Real Time Event Patterns
• Fast Testing and Deployment of Projects
SX: Empower Business Users for Real-Time Streaming Data Analytics
Streaming Event-Driven Architecture (EDA) , Server Platform
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Stream Explorer Features for Business Users
• Explorer: The application User Interface
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• Catalog: The repository for browsing resources
Stream Explorer Features for Business Users
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• 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.
Stream Explorer Features for Business Users
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• Pattern: A pre-built Exploration that addresses a particular business scenario in a focused and simplified User Interface
Stream Explorer Features for Business Users
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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
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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.
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Wire Transfer 1 $8000
WT 1
> $50,000 received in 3 hours
SOA Composite vs. OEP Application
Wire Transfer 2 $9000
WT 2
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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
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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