Co-Authors: Estella Pham and Guanlin Lu At peak, LinkedIn serves over 1.4 million member profiles per second. The number of requests to our storage infrastructure doubles every year. In the past, we addressed latency, throughput and cost issues by migrating off Oracle onto Espresso, an open-source document platform, and adding more nodes. We are now at the point...
ESPRESSO Articles
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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...
- Topics:
- Apache Helix,
- Distributed Systems,
- ESPRESSO,
- Data
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Co-authors: Gaurav Mishra, Song Lu, Antony Curtis, Shuangyang Yang Espresso is LinkedIn's horizontally scalable, highly-available, and elastic data-as-a-service platform that serves nearly 95% of our online storage traffic. Given its position in our tech stack, an optimization in Espresso availability can have a major impact on our members’ experience. In this...
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Espresso is LinkedIn's defacto NoSQL database solution. It is an online, distributed, fault-tolerant database that powers most of...
- 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...
- Topics:
- A/B Testing,
- Architecture,
- experimentation,
- Performance,
- ESPRESSO,
- T-REX,
- Data
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Co-authors: Christian Mathiesen and Jie Zhang Your LinkedIn profile is intended to be a representative picture of your professional...
- Topics:
- Hadoop,
- Product Design,
- ESPRESSO