Search results for "Espresso"

  • Espresso-online-data-flow-with-Netty4

    Improving performance and capacity for Espresso with new Netty framework

    June 27, 2019

    In this blog post, we’ll share how we migrated Espresso, LinkedIn’s distributed data store, to a new Netty4-based framework and achieved a large performance and capacity gain throughout the Espresso system as a result. In the larger scheme, this is particularly important since Espresso is a master data hub that serves many important applications across LinkedIn,...

  • espresso1

    Migrating to Espresso

    August 2, 2017

    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...

  • Jhubbub-on-Helix-making-stateless-and-elastic-easy

    Jhubbub on Helix: Stateless and elastic made easy

    August 27, 2020

    Co-authors: Hunter Lee and Dru Pollini LinkedIn was built to help professionals achieve more in their careers, and every day millions of people use our products to make connections, discover new opportunities and get better at what they do. An important part of our mission is helping people to find other professionals who are interested in the same things they...

  • chart-showing-the-state-transition-timing

    Improving Espresso availability with preemptive...

    August 11, 2020

    Co-authors: Gaurav Mishra, Song Lu, Antony Curtis, Shuangyang Yang Espresso is LinkedIn's horizontally scalable, highly-available, and...

  • diagram-of-espressos-architecture

    How we improved latency through projection in Espresso

    March 5, 2020

    Co-authors: Xiang Zhang and Chuck Jerian Espresso is LinkedIn’s document-oriented, highly available, and timeline-consistent...

  • activitygraph1

    Building the Activity Graph, Part I

    June 12, 2017

    Co-authors: Val Markovic and Vivek Nelamangala Serving a feed of relevant, personalized content to 500 million members is a massive...