Introduction LinkedIn is committed to providing economic opportunities for every member of the global workforce, and we’re growing at a rapid pace. Our platform is built on a collection of large-scale multi-cluster services functioning in harmony to offer a unified product experience to members. The aim of several backend engineering teams is to allow other...
scale Articles
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- Topics:
- scale,
- infrastructure,
- Data
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Co-authors: Yu Li, Szymon Gizecki, and Chinmaya Dattathri To ensure we have significant flexibility in how our teams collaborate, our trunk-based engineering development workflow manages dependencies on a binary level, instead of source level. This requires very efficient and sophisticated management of the resulting dependency graph, and we discussed our...
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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...
- Topics:
- scale,
- infrastructure
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Brooklin - a distributed service for streaming data in near real-time and at scale - has been running in production at LinkedIn since...
- Topics:
- scale,
- Stream Processing,
- infrastructure,
- Kafka,
- Data,
- Open Source
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Pinot, a scalable distributed columnar OLAP data store developed at LinkedIn, delivers real-time analytics for site-facing use cases...
- Topics:
- scale,
- Developer Productivity,
- Pinot,
- infrastructure,
- Data
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With over 630 million members, the LinkedIn platform delivers thousands of features that individually serve and store large amounts of...
- Topics:
- scale,
- Developer Productivity,
- infrastructure,
- Data