Unifying Messaging Experiences across LinkedIn
LinkedIn Engineering Blog
by Michele Ursino
2d ago
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 million members and customers.  From our legacy asynchronous email-based system to our current system, which features threaded conversations delivered in real-time, LinkedIn’s messaging platform serves as the backbone to all of i ..read more
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Improving the customer’s experience via ML-driven payment routing
LinkedIn Engineering Blog
by Xianyun Mao
3d ago
Co-Authors: Xianyun Mao, Stan Xu, Rachit Kumar, Vikas R, Xia Hong, and Divyakumar Menghani   As a LinkedIn member, you can subscribe to LinkedIn Premium on a monthly or annual basis. For our customers, we offer the same option for our Talent Solutions and/or Sales Navigator products. For each, LinkedIn offers subscription renewal payments. These subscription renewal payments used to go through a rule-based routing engine to selected payment gateways, which often resulted in a less-than-optimal experience. In this blog, we will discuss how we replaced the existing rule-based approa ..read more
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Career stories: Next-gen systems, servers, and SREs
LinkedIn Engineering Blog
by
1M ago
Saira joined our Bangalore site reliability engineering (SRE) team to tackle large-scale, site engineering challenges and grow. She highlights for us the impactful work she found here — from ushering in LinkedIn’s next-generation, server query system that runs over a fleet of 350,000 servers, to mentoring the next generation of female engineers: In my engineering career, I’ve always followed the path less taken. As a student, I became interested in cloud computing and systems engineering after working on an OpenStack project. My passion for this engineering area led to me pu ..read more
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Accelerating Code Delivery By 97% With Yarn Workspaces
LinkedIn Engineering Blog
by Jordan Hawker
1M ago
As teams and applications experience growth, it’s critical to adopt architectures that optimize for clear code ownership, build isolation, and provide efficient delivery of code. While many projects start small with just one or two repositories (for example, frontend and backend), this approach often becomes difficult to maintain as the codebases expand. At LinkedIn, we develop many applications that receive regular contributions from a multitude of teams, with each team owning distinct products or features. Our infrastructure teams enable developers to work effectively within these large a ..read more
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Ocelot: Scaling observational causal inference at LinkedIn
LinkedIn Engineering Blog
by
1M ago
Co-authors: Kenneth Tay and Xiaofeng Wang At Linkedin, we constantly evaluate the value our products and services deliver, so that we can provide the best possible experiences for our members and customers. This includes understanding how product changes impact key metrics related to those experiences. However, simply looking at connections between product changes and key metrics can be misleading. As we know, correlation does not always imply causation. When making decisions about the path forward for a product or feature, we need to know the causal impact of that change on our key me ..read more
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Hosted Search: LinkedIn Search as a cloud service
LinkedIn Engineering Blog
by Vibhaakar Sharma
1M ago
Search functionality is a core part of most data-driven products, and is used widely at LinkedIn. We have long provided a central platform for search functionalities; however, it was not fully managed in the sense that the application teams needed to own and operate the corresponding resources. As data needs grow and an increasingly high number of products want to integrate search, we discovered a need for a fully managed self-service platform to completely democratize search for all of our product teams. In this post, we will talk about Hosted Search, our new search solution that allows pr ..read more
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Our Approach to Research and A/B Testing
LinkedIn Engineering Blog
by Ya Xu
1M ago
We are constantly striving to improve the experience on LinkedIn for our members and customers, with research and experimentation, such as A/B Testing, playing a key role in that work.  Nearly a decade ago, I discussed the importance of these techniques in our journey to create economic opportunity for every member of the global workforce. Today we have a strong principled approach to how we design and run A/B tests on everything from UI designs to AI algorithms, and feature launches to bug fixes. As our platform continues to grow and evolve, these techniques have become even mor ..read more
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Operating System Snapshot Automation
LinkedIn Engineering Blog
by Rohit Jamuar
1M ago
Co-authors: Rohit Jamuar, Tianxin Zhou Introduction LinkedIn has a large set of physical servers geographically spread across several locations. Every application is hosted on a physical server and is distributed and managed across one of these hosts. With a reasonably sizable footprint of servers in data centers, LinkedIn is responsible for ensuring that these hosts are always on an operating system (OS) version deemed the “latest and greatest” for all intents and purposes. The Production Systems Software Engineering (PSSE)  organization within LinkedIn has taken the responsibility of ..read more
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Building LinkedIn's Skills Graph to Power a Skills-First World
LinkedIn Engineering Blog
by Sofus Macskássy
2M ago
Co-authors: Sofus Macskássy, Yi Pan, Ji Yan, Yanen Li, Di Zhou, Shiyong Lin As industries rapidly evolve, so do the skills necessary for success. Skill sets for jobs globally have changed by 25% since 2015 and this number is expected to double by 2027. Yet, we’ve long relied on insufficient and unequal signals when evaluating talent and predicting success - who you know, where you went to school, or who your last employer was. If we look at the labor market instead through the lens of skills - the skills you have and the skills a role or industry demands - we can create a transparent ..read more
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TopicGC: How LinkedIn cleans up unused metadata for its Kafka clusters
LinkedIn Engineering Blog
by
2M ago
Introduction Apache Kafka is an open-sourced event streaming platform where users can create Kafka topics as data transmission units, and then publish or subscribe to the topic with producers and consumers. While most of the Kafka topics are actively used, some  are not needed anymore because business needs changed or the topics themselves are ephemeral. Kafka itself doesn’t have a mechanism to automatically detect unused topics and delete them. It is usually not a big concern, since a Kafka cluster can hold a considerable amount of topics, hundreds to thousands. However, if the topic n ..read more
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