How LinkedIn Uses MySQL

The article introduces Northguard and Xinfra, two innovative systems developed by LinkedIn to enhance log storage scalability and operability.

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...

The article discusses LinkedIn's transition to Azure Linux as its primary operating system, detailing the motivations, challenges, and strategies involved in the migration.

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

The article discusses the open sourcing of OpenHouse, a control plane designed for managing tables in a data lakehouse.

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 introduces OpenHouse, a control plane developed at LinkedIn for managing tables in open source data lakehouse deployments.

The article discusses the development of Hoptimator, a declarative data pipeline orchestrator designed to streamline the creation of end-to-end data pipelines at LinkedIn.

The article discusses Metal as a Service (MaaS), an internal tool developed by LinkedIn to manage server lifecycles at scale.

The article discusses how LinkedIn scaled its Salt infrastructure to support its growing needs for remote execution jobs, achieving a tenfold increase in job capacity and improved reliability.

The article discusses LinkedIn's approach to measuring developer productivity and happiness through the development of the Developer Insights Hub (iHub).

The article discusses the evolution of AutoBuild, LinkedIn's automated server lifecycle management system, highlighting the challenges faced with its initial architecture and the improvements made ...

The article discusses the open sourcing of Venice, LinkedIn's derived data platform, which supports over 1800 datasets and 300 applications.

The article discusses the importance of data governance in large organizations like LinkedIn, emphasizing the need for effective schema annotations and automation in managing vast datasets.

The article discusses how LinkedIn addresses the last mile problem in MySQL high availability by implementing Openark Orchestrator for seamless failover and improved service reliability.

The article discusses Opal, a system developed at LinkedIn to manage mutable datasets within a data lake.

The article discusses DARWIN, LinkedIn's unified Data Science and Artificial Intelligence Workbench, designed to streamline the workflows of data scientists and AI engineers by centralizing various...

The article discusses LinkedIn's transition from a proprietary analytics tech stack to an open-source big data technology stack, detailing the challenges faced and the improvements made during the ...

This article discusses the challenges and solutions LinkedIn faced while scaling its Hadoop YARN cluster beyond 10,000 nodes.

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

The article discusses the evolution of metadata architectures, focusing on three generations of data discovery tools.

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

This article provides an in-depth look at LinkedIn's data pipeline monitoring system, focusing on the challenges faced with traditional monitoring methods and how they have evolved to improve visib...

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 implementation of Smart Alerts in ThirdEye, LinkedIn's real-time monitoring platform, focusing on the challenges of setting up effective alerts for diverse metrics.

The article discusses the re-architecture of LinkedIn's contacts and calendar ecosystem, focusing on the migration to a single source of truth for contact data.

The article discusses the evolution of incremental data capture for Oracle databases at LinkedIn, highlighting the transition from a batch processing model to a near-real-time system.

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 Query Analyzer, a tool developed by LinkedIn for analyzing MySQL queries with minimal overhead.

The article discusses the importance of site speed monitoring during A/B testing and feature ramp-up at LinkedIn.

The article 'Building Venice: A Production Software Case Study' discusses the development of Venice, a distributed derived data-serving platform at LinkedIn.

The article discusses the implementation of Conversion Tracking at LinkedIn, focusing on how it enables advertisers to measure the effectiveness of their campaigns.

The article discusses the Kafka ecosystem at LinkedIn, detailing its critical role as a messaging system and the various solutions developed to enhance its functionality.

The article discusses the development of LinkedIn Placements, a system designed to streamline the campus recruitment process for Indian universities.

The article discusses the complex migration of SlideShare's technology stack to LinkedIn's data centers, highlighting the challenges faced and the strategies employed to ensure a seamless transitio...

The article discusses Gobblin, a unified data ingestion framework developed by LinkedIn, designed to bridge batch and streaming data ingestion.

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

The article discusses LinkedIn's efforts to simplify big data ingestion for Hadoop-based warehouses using a framework called Gobblin.

The article discusses the implementation of Hadoop and HBase for near real-time analytics at SlideShare, detailing the upgrade process, technology selection, and the resulting improvements in data ...

The article discusses the significance of the log as a fundamental abstraction in real-time data systems, emphasizing its role in distributed systems, data integration, and stream processing.

This article discusses the optimization of Linux memory management specifically for low-latency and high-throughput databases, focusing on LinkedIn's GraphDB.

The article discusses the open-source release of Databus, LinkedIn's low latency change data capture system, which has been in production since 2011.

The article discusses the evolution of engineering leaders, highlighting the stages they typically progress through: from being a technology-focused individual contributor to becoming a well-rounde...

This article discusses the development of a LinkedIn application within an OpenSocial container, detailing the architecture, technologies used, and the author's experiences during their internship.