Scaling to 1 million users will require significant infrastructure changes at LivePerson. Currently LivePerson handles 13 TB of data per month from 20 million engagements and 1.8 billion visits. To scale, LivePerson considered using Couchbase for its always-on availability, linear scalability, search capabilities, and high throughput for the agent console data. LivePerson architected Couchbase into its data stack using Couchbase SDKs, Storm topologies, and XDCR to replicate data between clusters for redundancy.

1. Scalling to 1 million users
Ido Shilon | 4/6/2014

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. Data @ LP
13 TB
per month 20M
Engagements per month 1.8 B
Visits per month
VOLUME

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. Web agent console
Enables your agents to interact with
website visitors
Improve agent efficiency
Reduce chat time
The use case

6. The story - once upon a time
Visitor’s
Events
Agents console
(Java app)
Web Tier Visitors

7. And then the story continues
Data center 1 Data center 2
Kafka & Strom
(Event bus)
Web Agent
???

8. Possible solutions we considered

9. Why did we pick Couchbase
Always on
Linear scale
Searchable
Document store
Key Value
High throughput (R/W)
XDCR
Cassandra

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. 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. Thank You