How LinkedIn Uses Java

FishDB is a generic retrieval engine developed by LinkedIn to replace the legacy FollowFeed system, enhancing scalability and performance for their feed infrastructure.

The article discusses the evolution of LinkedIn's Nuage control plane, highlighting its transition from a self-service platform to a comprehensive control plane solution for managing data infrastru...

This article discusses the challenges and solutions related to Java heap memory and garbage collection, specifically in the context of LinkedIn's FollowFeed service.

The article emphasizes the importance of representation and diversity in engineering, particularly in the context of developing AI technologies.

The article discusses LinkedIn's journey in evolving its professional community policies enforcement at scale, focusing on the development of its anti-abuse platform and account restriction systems.

The article discusses the imperative for engineering leaders to adapt their strategies in 2024, focusing on leveraging AI technologies while addressing associated challenges.

The article discusses LinkedIn's innovative use of Apache Beam for real-time streaming processing, handling over 4 trillion events daily across more than 3,000 pipelines.

The article explores Javier's transition from a music career to data science, highlighting the intersection of math and music in his journey.

The article discusses Rishika's journey from an intern to a software engineer at LinkedIn, highlighting her growth in engineering skills and her commitment to mentoring others in the tech community.

The article discusses the scalability and performance challenges faced by Espresso, LinkedIn's distributed document store, and outlines the solutions implemented to enhance its performance.

The article discusses LinkedIn's transition to a GraphQL architecture for product development, highlighting the challenges faced with their existing microservices and the reasons for adopting Graph...

The article discusses LinkedIn's approach to detecting viral spam content on its platform, emphasizing the importance of creating a safe and trusted environment for its users.

LinkedIn has integrated Google Protocol Buffers (Protobuf) with Rest. li to enhance microservices performance, achieving significant reductions in latency and improvements in resource utilization.

The article discusses Vasundhara's journey as an AI engineer at LinkedIn, highlighting her transition from Seoul to Dublin during the pandemic and her work on machine learning algorithms for Linked...

The article discusses the Hodor framework developed by LinkedIn for detecting and handling overload scenarios in microservices.

The article discusses LinkedIn's Ocelot platform, which enables scalable observational causal inference to estimate the impact of product changes when A/B testing is not feasible.

The article celebrates International Women in Engineering Day (INWED) and emphasizes the importance of skills in shaping the future of engineering careers, particularly for women.

The article details LinkedIn's migration journey from Java 8 to Java 11, emphasizing the performance improvements and challenges faced during the transition.

The article discusses the evolution of the Venice platform to support large fanout use cases at scale, particularly focusing on optimizing performance and scalability for handling high-throughput r...

The article discusses Hodor, a framework developed by LinkedIn to detect and address service overload in their microservices architecture.

The article discusses LinkedIn's Remote Development initiative, which leverages cloud computing to enhance developer productivity by drastically reducing setup and build times.

The article discusses the refactoring of the Ambry network stack at LinkedIn to adopt HTTP/2, addressing network bottlenecks between frontend and storage nodes.

This article discusses the evolution of LinkedIn's Daily Executive Dashboard (DED) from a simple dashboard to a robust enterprise-grade data pipeline.

The article discusses the implementation of keyword search functionality in LinkedIn Talent Insights (LTI) using Apache Pinot.

The article discusses the implementation of multi-task learning for homepage feed ranking at LinkedIn using TensorFlow.

The article discusses LinkedIn's significant advancements in scaling the Hadoop Distributed File System (HDFS), achieving the milestone of storing 1 exabyte of data and optimizing performance throu...

This article discusses the challenges and solutions for estimating the cardinality of set intersections at scale using Apache Pinot and Theta Sketches.

The article discusses the innovative approach taken by LinkedIn to enhance site capacity projections using the Capacity Analyzer.

The article discusses the challenges of data integration at scale within LinkedIn's big data ecosystem and presents Gobblin's Data Integration Library (DIL) as a solution to streamline and standard...

The article discusses the challenges of memory fragmentation encountered by the Venice team at LinkedIn and how they addressed these issues using Jemalloc, a memory allocator.

The article discusses the introduction of Pegasus Data Language (PDL), a new schema definition language designed to replace the existing Pegasus Data Schema (PDSC) for data modeling in Rest.

Dagli is an open-source machine learning library designed for Java and other JVM languages, aimed at simplifying the creation of model pipelines while minimizing technical debt.

This article discusses how LinkedIn scales its compatibility testing process to accommodate its rapidly growing ecosystem of 12,000 Multirepo codebases.

The article discusses the enhancements made to the Beam Samza runner, focusing on performance improvements achieved through benchmarking and optimization techniques.

The article discusses LIquid, a new graph database, focusing on its design and implementation.

This article discusses the integration of batch and stream processing to create a near real-time dashboard for Recruiter usage statistics at LinkedIn.

The article discusses the engineering principles behind building a platform at LinkedIn, particularly focusing on creating leverage through reusable software.

The article discusses advanced schema management techniques for Apache Spark applications at LinkedIn, focusing on the integration of Avro schemas with the Hive Metastore to enhance type safety and...

The article discusses LinkedIn's transition from Python 2 to Python 3, emphasizing the importance of this migration for improving developer happiness and productivity.

This article discusses the significant improvements made to LinkedIn's experimentation engine, known as the Lix Engine, which has been optimized to be 20 times faster.

This article discusses the importance of app performance in Android development, detailing how LinkedIn's performance engineering team monitors and optimizes their app.

The article discusses the introduction of the Nuage SDK at LinkedIn, which empowers developers to integrate various platforms with minimal effort.

The article discusses LinkedIn's 4th annual SRE[in]con conference, which brought together over 700 site engineers and partners for a series of workshops and talks.

The article discusses how LinkedIn customizes Apache Kafka to handle an impressive scale of 7 trillion messages per day.

The article discusses how LinkedIn improved developer productivity and build times using Gradle build cache.

The article discusses the evaluation of language adoption at scale, particularly focusing on Kotlin for Android development at LinkedIn.

The article discusses the importance of data management at LinkedIn, focusing on expediting data fixes and migrations through a centralized, scalable self-service platform.

This article discusses the migration of Espresso, LinkedIn's distributed data store, to a new Netty4-based framework, highlighting significant performance and capacity improvements.

The article discusses the rebuilding of LinkedIn's Profile Highlights System, focusing on the transition from a monolithic architecture to a microservices-based plug-in architecture.

The article discusses a community meetup held at LinkedIn focused on Apache Hadoop, highlighting contributions from various organizations and key presentations on topics like TensorFlow on YARN, Ha...