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Building a Scalable and Modern Infrastructure at CARFAX

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The CARFAX vehicle history database contains over twelve billion documents in a twelve shard cluster that replicates to multiple data centers. This will be a step by step walk through of how we deploy …

The CARFAX vehicle history database contains over twelve billion documents in a twelve shard cluster that replicates to multiple data centers. This will be a step by step walk through of how we deploy our servers, manage high volume reads and writes, and our configuration for high availability. By automating everything from the operating system install up we are able deploy complete replica clusters quickly and efficiently. Using distributed processing and message queuing we load millions of new documents each day with a projected growth over a billion records per year. Through the use of tagging, server configuration, and read settings we deliver content with high consistency and availability.

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  • 1. A Scalable and Modern Infrastructure at CARFAX
  • 2. About Me • Jai Hirsch – Senior Systems Architect, Data Technologies at CARFAX • Long-time Java and Database Developer • Data and Distributed Processing Enthusiast • Github: https://github.com/JaiHirsch Twitter: @JaiHirsch https://twitter.com/JaiHirsch LinkedIn: http://www.linkedin.com/pub/jai-hirsch/8/a89/335
  • 3. “CARFAX helps millions of people buy and sell used cars with more confidence”
  • 4. CARFAX Vehicle History Report
  • 5. Documents on the Report
  • 6. NoSQL Before it Was Cool Proprietary Key Value Store on OpenVMS Developed by CARFAX in 1984
  • 7. Never mind that sh*t! Here comes Mongo!
  • 8. Why MongoDB? Legacy structures mapped to documents High availability using replica sets Platform Independence Support
  • 9. MongoDB at CARFAX Our Production Environment The Legacy Database and High Volume Loads High Availability Reads
  • 10. Our Production Environment
  • 11. Server Deployment AUTOMATE AUTOMATE AUTOMATE AUTOMATE
  • 12. Server Configuration 12 Shards with two spare servers racked for failover • OS: Linux • MongoDB 2.4.9 • 128 GIGs of RAM • 1.8 TB of Drive Space • 10K RPM SAS Drives
  • 13. The Future
  • 14. Extract, Transform, Load
  • 15. Loading Millions to Billions of Records per Day AUTOMATE AUTOMATE AUTOMATE AUTOMATE
  • 16. First Attempt To Load Was Completely CPU Bound
  • 17. Not Acceptable! 45 Days to Backload the Legacy Database
  • 18. Distributed Processing
  • 19. Acceptable! Billion+ inserts per Day! 9 Days to Backload
  • 20. The MongoDB Implementation 13 billion+ documents 1.5 billion+ new documents per year  Document size: ~ 795 Bytes  VHR uses 200+ documents
  • 21. High Availability Reads
  • 22. Millions of Reports per Day AUTOMATE AUTOMATE AUTOMATE
  • 23. Read Scalability With Tagging
  • 24. Each Data center is Tagged Each Replica Set is Tagged
  • 25. 5X More Reports per Second
  • 26. But we can do More!
  • 27. Lets Wrap It Up Don’t buy a used car without a CARFAX report ➢Grok your data and working set ➢Architect for your load volume ➢Scale your reads to meet demand 29
  • 28. Keys To Success ➢AUTOMATE EVERYTHING ➢Test Many Configurations ➢Grid Computing is Awesome ➢Shard Early, Shard Often
  • 29. And Remember
  • 30. Friends Don’t Let Friends Use Default Ulimits!
  • 31. Thank You! The migration was a success due to the incredible teams at CARFAX and MongoDB We are always looking for great people to join us. www.carfax.com/careers