Co-authors: Alexander Ivaniuk and Weitao Duan Editor’s note: This blog post is the second in a series providing an overview and history of LinkedIn’s experimentation platform. The previous post on the history of LinkedIn’s experimentation infrastructure can be found here. Introducing variant assignment Previously on the blog, we’ve shared a look into how...
scale Articles
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- Topics:
- scale,
- A/B Testing,
- infrastructure,
- T-REX
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Co-authors: Walaa Eldin Moustafa, Wenye Zhang, Sushant Raikar, Raymond Lam, Ron Hu, Shardul Mahadik, Laura Chen, Khai Tran, Chris Chen, and Nagarathnam Muthusamy Introduction At LinkedIn, our big data compute infrastructure continually grows over time, not only to keep pace with the growth in the number of data applications, or their domains spanning data...
- Topics:
- scale,
- Apache Pig,
- Data,
- Dali,
- Open Source
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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...
- Topics:
- scale,
- A/B Testing,
- infrastructure,
- T-REX,
- experimentation
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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...
- 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...
- 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