Scaling LinkedIn - A Brief History
LinkedIn started in 2003 with 2700 members in the first week and has since grown to over 400 million members globally. It initially had a monolithic Java application called Leo serving all pages and using a single SQL database. To scale, LinkedIn developed its first dedicated service for the member connection graph and another for search. It later introduced replica databases, extracted services f
LinkedIn: Creating A Low Latency Change Data Capture System With Databus
This is a guest post by Siddharth Anand, a senior member of LinkedIn's Distributed Data Systems team. Over the past 3 years, I've had the good fortune to work with many emerging NoSQL products in the context of supporting the needs of a high-traffic, customer facing web site. In 2010, I helped Netflix to successfully transition its web scale use-cases from Oracle to SimpleDB, AWS' hosted database
SNA Projects Blog : Tech Talk: Michael Deerkoski (Flickr) — “Continuous Deployment at Flickr”
LinkedIn operates the world’s largest professional network with more than 645 million members in over 200 countries and territories. This team builds distributed systems that collect, manage and analyze this digital representation of the world's economy, while our AI experts, data scientists and researchers conduct applied research that fuel LinkedIn’s data-driven products and provide insights tha
LinkedIn and Slideshare
LinkedInSocial Media Marketing Manager, Global Brand at LinkedIn
SNA Projects Blog : Tech Talk: Michael Deerkoski (Flickr) — “Continuous Deployment at Flickr”
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Photo Tourism: Microsoft Research, Interactive Visual Media Group
Espresso: LinkedIn's Distributed Data Serving Platform (Paper)
GitHub - linkedin/databus: Source-agnostic distributed change data capture system
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