Scaling to 1 million users v1

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Scaling to 1 million users v1

  1. 1. Scalling to 1 million users Ido Shilon | 4/6/2014
  2. 2. @idoshilon { name: "Ido Shilon", age: 37, kids: [ "illy" ], wife: "Oshrat", Title: "Group Manager @ LivePerson (Heading the platform group)", Lived_Worked_At: [ "Silicon Wadi (Israel)", "Silicon Alley (NYC)", "Silicon Valley (Bay Area)" ] }
  3. 3. Data @ LP 13 TB per month 20M Engagements per month 1.8 B Visits per month VOLUME
  4. 4. Data stack LiveEngage DASHBOARD MONITORING CHAT/VOICE system Batch track Real-Time track APACHE KAFKA STORM COMPLEX EVENT PROCESSING PERPETUAL STORE RT REPOSITORY Cassandra BUSINESS INTELLIGENCE ANALYTICAL DB
  5. 5. Web agent console Enables your agents to interact with website visitors Improve agent efficiency Reduce chat time The use case
  6. 6. The story - once upon a time Visitor’s Events Agents console (Java app) Web Tier Visitors
  7. 7. And then the story continues Data center 1 Data center 2 Kafka & Strom (Event bus) Web Agent ???
  8. 8. Possible solutions we considered
  9. 9. Why did we pick Couchbase Always on Linear scale Searchable Document store Key Value High throughput (R/W) XDCR Cassandra
  10. 10. Architecture Couchbase Java SDK Application server Tomcat M/R views cluster M/R views cluster XDCR REST API Couchbase Java SDK Storm Topology Couchbase Java SDK Storm Topology
  11. 11. Data stack now with Couchbase LiveEngage DASHBOARD MONITORING CHAT/VOICE system Batch track Real-Time track APACHE KAFKA STORM COMPLEX EVENT PROCESSING PERPETUAL STORE RT REPOSITORY Cassandra BUSINESS INTELLIGENCE ANALYTICAL DB
  12. 12. Thank You

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