Lessons Learned: Scaling a Social Network

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Founded by two high school students in 2005, myYearbook.com has grown to become one of the top 5 social networks and one of the top 25 most trafficked web sites in the United States. In the face of such growth and large traffic volumes, we continually face technical challenges in achieving operational stability. In this session, we’ll review the growing pains, unique architectural decisions, and methodologies employed to support the consistent growth and demand of a social network while also affording for rapid development cycles required by a product development team.

Session Outline:
- Intro
- What is Social Networking?
- What is myYearbook.com?
- Challenges
– Monitoring
– Volume
– Response Times
– Stability
- Requirements for Scaling
– Money
– Bandwidth
– Hardware
- Computer Science Knowledge
– Algorithms (Data Management, Analysis, Time vs. Space)
– Mathematics (Probability, Discrete Math, Queueing Theory)
– Research
– Google
- Looking at Problems Differently
– Data at Rest vs. Data in Motion
– Synchronous vs. Asynchronous
– Exact vs. Approximate
– Multi-Process vs. Multi-Thread vs. Event Driven
– Best tool for the job…
- Technologies Employed @ myYearbook.com
– Design (SOA-ish)
– Languages (Java, Objective C, PHP, C, C++, Python, etc.)
HTTP (Apache, Cherokee, Tornado, etc.)
– Database (PostgreSQL, MySQL, TimesTen, eXtremeDB, BerkeleyDB, Tokyo, etc.)
– Transient Cache (memcached, APC, custom, etc.)
– Persistent Cache (eXtremeDB, TimesTen, custom, etc.)
– Queueing (ApacheMQ, RabbitMQ, ZeroMQ)
- Case Study #1: Matchmaking
- Case Study #2: Feed
- Case Study #3: Real-time Matchmaking

Photo of Michael Glaesemann

Michael Glaesemann


Michael Glaesemann is a senior data architect at myYearbook.com, developing infrastructure to support a variety of social-networking applications and riding herd over an ever-increasing number of PostgreSQL servers. He’s been using PostgreSQL since 2003 and has spoken on PostgreSQL at conferences in North America and Japan, and released software to aid in managing large PostgreSQL installations. Relational theory is dear to his heart, and he’s been increasingly enamoured with functional programming and how the two are related. In his spare time he might be found puzzling together ZeroMQ, Ruby, PostgreSQL, Javascript, and his cottage electrical usage.

  • EnterpriseDB
  • Amazon Web Services
  • Clustrix
  • Continuent
  • Facebook
  • HTI Consultoria e Tecnologia
  • Monty Program
  • Percona
  • Rackspace Hosting
  • Schooner Information Technology
  • SkySQL
  • Xeround

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