Espresso is LinkedIn's strategic distributed, fault-tolerant NoSQL database that powers many LinkedIn services. Espresso has a large production footprint at LinkedIn, with close to a hundred clusters in use, storing about 420 terabytes of Source of Truth (SoT) data and handling more than two million queries per second at peak load. This post discusses our...
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Editor’s note: Members of the information security team at LinkedIn have an opportunity to work on research topics under a well-defined framework that allows them to evaluate new products and technologies, as well as explore the related threat surface. The team strives to find new and innovative ways to help simplify and strengthen security and contribute back...
- Topics:
- Open Source,
- Security
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Typical distributed data systems are clusters composed of a set of machines. If the dataset does not fit on a single machine, we usually shard the data into partitions, and each partition can have multiple replicas for fault tolerance. Partition management needs to ensure that replicas are distributed among machines as evenly as possible. More crucially, when a...
- Topics:
- Apache Helix,
- Big Data,
- Distributed Systems,
- Open Source
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Earlier this month, and for the first time in our company’s history, more than 50% of pages on LinkedIn were accessed over IPv6 from...
- Topics:
- IPv6
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In a previous post, I gave some advice for those who are interested in a career in data science. One of the suggestions I made was to...
- Topics:
- data science,
- engineering culture
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Co-authors: Vivek Nelamangala and Val Markovic Editor’s note: In Part 1 of this series, we talked about how we built the Activity...
- Topics:
- relevance,
- Feed Personalization