• LinkedIn_Tech_Update

    Building the next version of our infrastructure

    July 23, 2019

    The pursuit of our mission to connect the world’s professionals to make them more productive and successful is deeply dependent on the technology and infrastructure we build and maintain. Ten years ago, we had 50 million members. Fast forward five years and that number jumped to 300 million. Today, we have more than 645 million members, 20 million jobs and...

  • change-data-capture

    Open Sourcing Brooklin: Near Real-Time Data Streaming at Scale

    July 16, 2019

    Brooklin - a distributed service for streaming data in near real-time and at scale - has been running in production at LinkedIn since 2016, powering thousands of data streams and over 2 trillion messages per day. Today, we are pleased to announce the open-sourcing of Brooklin and that the source code is available in our Github repo!  Why Brooklin? At LinkedIn,...

  • PartitionConsumer-objects-distribution

    Auto-Tuning Pinot Real-Time Consumption

    July 11, 2019

    Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases such as LinkedIn's Who viewed my profile, Talent insights, and more. Pinot uses Apache Helix for managing cluster resources and Apache Zookeeper to store metadata. Pinot has wide adoption at LinkedIn, ranging from internal...

  • High-level-architecture

    Expediting Data Fixes and Data Migrations

    July 9, 2019

    With over 630 million members, the LinkedIn platform delivers thousands of features that individually serve and store large amounts of...

  • WomenConnect_table_discussion

    Driving Change with Authenticity and Allyship at...

    July 2, 2019

    WomenConnect is a series of events focused on bringing together women in tech to build meaningful relationships. Over the past four...

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

    Improving Performance and Capacity for Espresso with New...

    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...