How LinkedIn Uses JSON

This article discusses the engineering of LinkedIn's job ingestion system, which processes millions of job postings daily from various sources.

The article discusses how LinkedIn developed the Contextual Agent Playbooks & Tools (CAPT) to enhance AI coding agents with organizational context, enabling them to better assist engineers in their...

The article discusses LinkedIn's transformation of its job search functionality through AI and large language models (LLMs).

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...

LakeChime is a data trigger service designed to enhance the efficiency of data processing in modern data lakes.

The article discusses the development of a new AI-powered experience at LinkedIn, focusing on the challenges and successes encountered while building a generative AI product.

The article discusses ValiData, a scalable automated config-driven data validation tool used at LinkedIn to ensure the accuracy and consistency of large datasets.

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 the implementation of Operating System Snapshot Automation (OSSA) at LinkedIn, detailing the challenges faced with manual processes and the transition to an automated system.

The article discusses LinkedIn's Distributed Firewall (DFW), a host-level firewalling system designed to manage extensive firewall rules across a vast network of hosts.

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 Smart Argument Suite, a Python library designed to streamline the process of passing command-line arguments for AI workflows.

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.

The article discusses the implementation of dark canary clusters at LinkedIn, a technique for safely testing new code in production environments without impacting end users.

The article discusses Spark-TFRecord, a new data source for Apache Spark that aims to provide full support for the TFRecord data format used in TensorFlow.

The article discusses LinkedIn's open sourcing of DataHub, a metadata search and discovery platform, detailing its development journey from WhereHows to DataHub.

The article discusses the open-sourcing of Brooklin, a distributed service for near real-time data streaming at scale, which has been in production at LinkedIn since 2016.

The article discusses the release of Unstructured Data Reactive in Rest. li, an open-source REST framework developed at LinkedIn.

The article discusses the collaboration between Microsoft and LinkedIn to create the Resume Assistant, a feature integrated into Microsoft Word that helps users enhance their resumes using LinkedIn...

The article discusses LinkedOut, a request-level failure injection framework developed by LinkedIn to enhance resilience engineering.

The article discusses LinkedIn Lite, a lightweight mobile web experience designed for India's mobile-first market.

The article discusses Brooklin, a data ingestion service developed by LinkedIn to facilitate streaming data from various sources to multiple destinations.

The article discusses the challenges and solutions associated with managing external libraries in software development, particularly at LinkedIn.

This article continues the exploration of the Glimmer Virtual Machine (VM) used in Ember. js for rendering, focusing on runtime compilation and execution.

The article introduces Flashback, an open-source internet mocking tool developed at LinkedIn to facilitate reliable testing of web applications that interact with third-party websites.

The article discusses Glimmer, a new rendering engine for Ember. js, designed to improve performance by reducing payload size, CPU time, and memory pressure.

The article discusses Pemberly, LinkedIn's re-imagined technology stack for their flagship app, focusing on modernizing the user experience and improving developer productivity.

The article discusses the engineering infrastructure at LinkedIn that supports test tracking across various platforms, including iOS, Android, and web.

The article discusses new analytics features on LinkedIn that allow users to see who has viewed their posts, enhancing their ability to understand audience engagement.

The article discusses the development of a native video player library for Android at LinkedIn, addressing technical challenges and solutions for optimizing video delivery and performance on mobile...

The article discusses the implementation of immutable models in the LinkedIn flagship app, highlighting their benefits such as thread safety and performance.

The article discusses the design and implementation of the LinkedIn Android Data Pipeline, which optimizes data flow between the app and server.

The article discusses a unique UI redressing attack that exploits CSS selectors to trick users into navigating to malicious sites.

The article discusses performance improvements made to the Slideshare Android application, focusing on optimizations in image loading, JSON parsing, and data model storage.

The article outlines the evolution of LinkedIn's architecture and scaling strategies from its inception in 2003 to its modern service-oriented architecture.

Espresso is LinkedIn's distributed, fault-tolerant NoSQL database that supports various applications, including Member Profile and InMail.

The article discusses the complete redesign of LinkedIn's mobile profile experience, emphasizing how it enhances user relationships and professional identity.

The article discusses the open-source release of Isaac, an Objective-C library designed to parse JSON into models, significantly improving code quality and reducing crash rates in iOS applications.

The article discusses LinkedIn's significant milestone with Rest. li, a framework for developing RESTful services, highlighting that 50% of all remote calls between services now utilize Rest. li.

The article discusses LinkedIn's approach to mobile A/B testing, highlighting how member feedback shapes app development.

The article discusses the Play Framework, an open-source web application framework that promotes functional programming principles to address modern web development challenges.

The article discusses the engineering behind LinkedIn's University Pages, detailing the architecture, data processing, and technologies used to create a platform that enhances interactions between ...

The article discusses Fluentd, an open-source log management tool utilized by Slideshare for efficient log handling.

The article discusses the creation of product tours using Hopscotch, a framework designed to help users understand complex software features through guided tours.

The article discusses the engineering behind the redesigned LinkedIn profile, highlighting the adoption of new technologies such as JSON mappers, Fizzy, and Dust.

The article discusses the development of the EatIn Suite, an internal food-rating platform at LinkedIn, built by a team of interns within three weeks.

The article discusses the implementation of the Play Framework at LinkedIn, highlighting its benefits, developer experience, and future plans.

Rest. li is a REST+JSON framework developed by LinkedIn for building scalable service architectures.

The article discusses the implementation of a messaging layer between the native and web portions of the LinkedIn iPad app using WebSockets.

The article discusses how LinkedIn optimized its iPad app by leveraging HTML5 Local Storage to enhance performance and responsiveness.