Co-authors: Yixing Zhang, Bingfeng Xia, Ke Wu, and Xinyu Liu Since Beam Samza runner was developed in 2018 at LinkedIn, we now have 100+ Samza Beam jobs running in production. As our usage grew, we wanted to better understand how the Samza runner performs compared to other runners and identify areas of improvement. In general, for stream processing platforms,...
Performance Articles
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- Topics:
- Stream Processing,
- Apache Samza,
- Performance,
- Benchmark
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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...
- 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...
- 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