Co-authors: Sandhya Ramu and Vasanth Rajamani For companies and organizations, failure tends to be far more illuminating than success and the lingering effects of a failure can be harmful if the team moves too quickly and does not resolve the issue in a thorough and transparent manner. We recently ran into a large incident that involved data loss in our big data...
Performance Articles
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- Topics:
- Performance,
- Hadoop,
- data center,
- Data
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Espresso is LinkedIn's defacto NoSQL database solution. It is an online, distributed, fault-tolerant database that powers most of LinkedIn’s applications including member profiles, InMail (LinkedIn's member-to-member messaging system), sections of the main LinkedIn homepage, our mobile applications, and more. Since Espresso caters to many critical features, its...
- Topics:
- Performance,
- ESPRESSO,
- site speed,
- SRE
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Co-authors: Xiang Zhang, Estella Pham, and Ke Wu Identity services are critical systems that serve data on profile and member settings to help power many other applications at LinkedIn. In this blog post, we’ll share how we merged two layers of the identity services that handle more than half a million queries per second (QPS) that drove a 10% reduction in...
- Topics:
- A/B Testing,
- Architecture,
- experimentation,
- Performance,
- ESPRESSO,
- T-REX,
- Data
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Co-authors: Suruchi Shah and Hari Shankar The rise of instant messaging has changed how we communicate. Compared to the back-and-forth...
- Topics:
- Performance,
- infrastructure,
- Architecture,
- Search
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Co-authors: Xiang Zhang and Chuck Jerian Espresso is LinkedIn’s document-oriented, highly available, and timeline-consistent...
- Topics:
- Performance,
- Data,
- ESPRESSO
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Pinot, an open source scalable distributed columnar OLAP data store, is used extensively across almost all areas of LinkedIn. It...
- Topics:
- Performance,
- Pinot,
- linux,
- Data