Editor’s note: This blog post is the first in a series providing an overview and history of LinkedIn’s experimentation platform. At any given time, LinkedIn’s experimentation platform is serving up to 41,000 A/B tests simultaneously on a user population of over 700 million members. Operation at such a scale is enabled with the LinkedIn Targeting, Ramping, and...
scale Articles
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- Topics:
- scale,
- A/B Testing,
- infrastructure,
- T-REX
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Co-authors: Scott Meyer, Andrew Carter, and Andrew Rodriguez Editor’s note: This is the second part of a two-part blog series. Part 1 described how graph data relates to the in-memory graph of structures commonly used as models (as in “model-view-controller”) by applications, how graph data can be stored in a conventional relational database, and why...
- Topics:
- scale,
- infrastructure,
- knowledge graph,
- Data
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Co-authors: Scott Meyer, Andrew Carter, and Andrew Rodriguez Editor’s note: In this two-part blog series, we introduce LIquid, a new graph database built by LinkedIn to support human real-time querying of the economic graph. It is a complete implementation of the relational model that supports fast, constant-time traversal of graph edges with a relational graph...
- Topics:
- scale,
- infrastructure,
- knowledge graph,
- Data
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Co-authors: Viranch Mehta, Jon Sorenson, Samir Jafferali As LinkedIn has grown to more than 690 million members, we’ve expanded our...
- Topics:
- scale,
- infrastructure,
- SRE
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Co-authors: Jefferson Lai, Vinyas Maddi, and Vijay Ramamurthy One of our core engineering principles here at LinkedIn is to create...
- Topics:
- scale,
- infrastructure,
- Product Design
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Co-authors: Walaa Eldin Moustafa, Wenye Zhang, Adwait Tumbde, Ratandeep Ratti Introduction Over the years, the popularity of Apache...