In this blog post, we’ll share how we migrated Espresso, LinkedIn’s distributed data store, to a new Netty4-based framework and achieved a large performance and capacity gain throughout the Espresso system as a result. In the larger scheme, this is particularly important since Espresso is a master data hub that serves many important applications across LinkedIn,...
infrastructure Articles
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- Topics:
- infrastructure,
- Distributed Systems,
- ESPRESSO
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At LinkedIn, we are entrusted with protecting the privacy and data of our members. Storing members’ choices on how they intend their data to be used is vital to building and maintaining member trust, as well as ensuring compliance with legal and regulatory requirements. It is also essential that we respect members’ preferences for how they wish to interact with...
- Topics:
- infrastructure,
- scale
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LinkedIn’s infrastructure has grown remarkably over the years, and that has kept the Production Infrastructure Engineering teams on their toes. Growing quickly means we’ve had to learn to adapt quickly. While most of our systems are solid and ready to scale, from time to time we find ourselves supporting systems that struggle to meet increasing demands. It’s...
- Topics:
- infrastructure,
- scale
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Co-authors: Szymon Gizecki, Yu Li, Chinmaya Dattathri, Ethan Hall, Irina Issayeva, and Deep Majumder Introduction At LinkedIn, we...
- Topics:
- infrastructure,
- scale,
- ESPRESSO
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Co-authors: Ethan Dow, George Pearman, and Bradley Walker In November 2017, Microsoft and LinkedIn introduced an exciting integration...
- Topics:
- infrastructure,
- Product Design
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With more than a half billion members on LinkedIn, we have had to create new ways to scale our infrastructure and support the...
- Topics:
- infrastructure,
- Data