ACTIVE INSIGHT<br />Event Stream Processing in the Cloud<br />Mike Telem<br />Business Development<br />
Table of Contents<br /><ul><li>Background: The Digital Era
Processing, Correlating and Aggregating Events
Use Cases: From Behavioral Targeting to Electrical Smart Grids
ESP in the Cloud
Roadmap: Where is ActiveInsight headed</li></li></ul><li>The Digital Era<br /><ul><li>Our world is becoming digital…
Cell phones, web sites, GPS devices, cars, ads, Financial transactions,…
RFID, industrial eq., security sensors, border controls, medical eq.,…
Utilities, pipelines, meters, digital signage, home appliances, entertainment devices, cars, …
Applications, infrastructure, web-services, customer data,…
Markets, stocks, currencies, news, wiki’s, blogs, tweets,…
…
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Active Insight - Event Stream Processing In The Cloud

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The activeInsight open source event stream processing platforms enables cloud based event processing, correlation, aggregation and reaction to events and patterns

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  • Active Insight - Event Stream Processing In The Cloud

    1. 1. ACTIVE INSIGHT<br />Event Stream Processing in the Cloud<br />Mike Telem<br />Business Development<br />
    2. 2. Table of Contents<br /><ul><li>Background: The Digital Era
    3. 3. Processing, Correlating and Aggregating Events
    4. 4. Use Cases: From Behavioral Targeting to Electrical Smart Grids
    5. 5. ESP in the Cloud
    6. 6. Roadmap: Where is ActiveInsight headed</li></li></ul><li>The Digital Era<br /><ul><li>Our world is becoming digital…
    7. 7. Cell phones, web sites, GPS devices, cars, ads, Financial transactions,…
    8. 8. RFID, industrial eq., security sensors, border controls, medical eq.,…
    9. 9. Utilities, pipelines, meters, digital signage, home appliances, entertainment devices, cars, …
    10. 10. Applications, infrastructure, web-services, customer data,…
    11. 11. Markets, stocks, currencies, news, wiki’s, blogs, tweets,…
    12. 12.
    13. 13. Multiple events share various perspectives
    14. 14. Event stream quantity and frequency will fluctuate
    15. 15. Effective time window for reactions is minimal
    16. 16. Reaction channels may vary
    17. 17. Events should be correlated with historical data</li></li></ul><li>Event Stream Processing (ESP)<br /><ul><li>Event Stream Processing:
    18. 18. Processing application level events in a distributed environment
    19. 19. Event Correlation – Directing multiple event streams based on their context to the corresponding ESP containers
    20. 20. Complex Event Processing:
    21. 21. Processing multiple events to detect meaningful patterns using correlation, aggregation and time-frames
    22. 22. Pattern detection: Detecting specific event combinations and patterns in contexts
    23. 23. Cross-Context Correlation: Processing multiple streams into multiple contexts / perspectives (fraud / marketing)
    24. 24. Aggregation: Accumulating correlated events into time-based contexts, support for “event state machine” aggregation.
    25. 25. Data Integration: Caching data sources as “reference data” for processing
    26. 26. Reaction: Invoking an action after a successful event or pattern match</li></li></ul><li>Different Use-cases &gt; Similar Challenges<br /><ul><li>Online Gaming : Real-time BI, money laundering, local compliance, application offload
    27. 27. Online Advertisement: Behavioral targeting, multiple site click-stream correlation
    28. 28. Ecommerce : Identifying customer interests (up-sell/cross—sell) , Improving conversion rates, anonymous user hooking, campaign management
    29. 29. Online Self-Service : Identifying customer turnover or dissatisfaction, Monitor user experience and assist in transaction completion
    30. 30. Algo-Trading : performance and availability improvements and HW cost reduction
    31. 31. Auditing: Feeding “Who” did “What” and “When” to auditing and SIEM systems
    32. 32. Fraud detection: Fraudulent behavior pattern detection, Bot detection, alongside fraud detection systems
    33. 33. Electrical smart-grid: Detecting misuse, mal-functions, on-demand supply
    34. 34. Home Land Security: Enhance airport and border security, correlate multiple events, intelligence data and incoming alerts
    35. 35. Traffic management: Vehicle location management for Insurers, authorities and drivers
    36. 36. …Similar Challenges</li></li></ul><li>Different Use-cases &gt; Similar Challenges<br />Process<br />Correlate<br />Aggregate<br />Match<br />React<br />
    37. 37. ESP in the Cloud<br /><ul><li>Elastic ESP
    38. 38. On-demand usage
    39. 39. Scaling up and out to varying event frequencies
    40. 40. ESP as a service
    41. 41. Offloading event processing
    42. 42. Dynamic Stream Sources
    43. 43. Dynamic event sources
    44. 44. Handling remote event sources
    45. 45. SaaS Enabler
    46. 46. Porting event-oriented applications to the cloud
    47. 47. SaaScomponent
    48. 48. Enhance SaaS applications
    49. 49. Offload the core application
    50. 50. Comply to regional regulations
    51. 51. Provide SaaS Application integration
    52. 52. IaaS/Hosting
    53. 53. Value Added Services (Security, Auditing, BI)
    54. 54. Customer Experience Management</li></li></ul><li>ActiveInsight.org<br />Distributed Event Stream Processing Framework<br /><ul><li>Real-time event processing
    55. 55. Multi-source event stream processing
    56. 56. Event correlation and aggregation
    57. 57. Pattern matching
    58. 58. Integrated data caching
    59. 59. Embeddable framework
    60. 60. Scalable, elastic cloud run-time</li></li></ul><li>Typical Architecture<br />Mobile Device<br />Web App<br />Distributed Cache<br />Distributed Cache<br />Distributed Cache<br />Reference Data<br />Reference Data<br />Reference Data<br />Context<br />Context<br />Context<br />Context<br />Context<br />Context<br />Car GPS<br />AI Server Node<br />AI Server Node<br />AI Server Node<br />Process<br />Process<br />Process<br />Match<br />React<br />Match<br />React<br />Match<br />React<br />Contexts<br />Marketing<br />Security<br />
    61. 61. Roadmap<br /><ul><li>Cloud ESP
    62. 62. Amazon Public Image, Devpay
    63. 63. SaaSconnectivity (Sales Force, etc.)
    64. 64. First SaaS OEM’s
    65. 65. AI in additional IaaS
    66. 66. Enhanced ESP
    67. 67. Integrating mathematical/statistical engines (R-server)
    68. 68. In-memory data-grid integration
    69. 69. Clustered ESP container
    70. 70. Pattern Recognition</li></li></ul><li>Q&A<br />Thank you!<br />http://www.activeinsight.org<br />mike.telem@activeinsight.net<br />

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