Co-authors: Michele Ursino and Joe Xue Introduction At LinkedIn, we believe that an opportunity can arise from just one conversation, so having reliable and powerful messaging capabilities to enable people to have those meaningful and professional conversations is crucial. Over the years, we have evolved our messaging platform to meet the needs of our 900...
Co-authors: Xiang Zhang and Jingyu Zhu Introduction The Lambda architecture has become a popular architectural style that promises both speed and accuracy in data processing by using a hybrid approach of both batch processing and stream processing methods. But it also has some drawbacks, such as complexity and additional development/operational overheads. One of...
- Stream Processing,
- batch processing
In the previous blog posts of our “Rebuilding messaging” series, we shared the process of how we designed the system from high-level product and engineering requirements, and how we bootstrapped the data. In this post, we’ll explore why we made extensibility a core aspect of our messaging platform, what that meant for our partner teams, and how we got it done....
Co-authors: Pradhan Cadabam and Jingxuan (Rex) Zhang Messaging has been a core part of Linkedin since the day we launched and our...
Co-authors: Tyler Grant, Armen Hamstra, Cliff Snyder Over the last five years, the number of messages sent on LinkedIn has quadrupled....
Co-authors: Xiang Zhang, Estella Pham, and Ke Wu Identity services are critical systems that serve data on profile and member settings...
- A/B Testing,