LINEヤフーTech (LY Corporation Tech)

Introduction to "Spark Connect" and Implementation of Managed Spark as a Service

Replacing Data Analysts with AI - Building Data Pipelines and Automating Analysis with Generative AI

Advanced A/B Testing Systems with Dynamic User Segmentation

推薦システムと、RayやDeepSpeedを用いたユーザー・アイテムの次世代の埋め込み表現 / Recommender System and Next-Gen. Embedding Representations of Users and Items Using Ray and DeepSpeed

Metadata Management with Semantic

Yamla: Rustでつくるリアルタイム性を追求した機械学習基盤 / Yamla: A Rust-Based Machine Learning Platform Pursuing Real-Time Capabilities

Realtime Data Platform: from Lakehouse to Streamhouse

Flava Kubernetes Engine: 直感的に使えるプラットフォームを目指して / Flava Kubernetes Engine: Towards Intuitive Platform

Flava DBS for MySQL: Architecture and Features

Flava SecureG: Highest Security Cloud Environment After LY Corporation Merger

Flava IAM: Bridging Security and Usability with Athenz

Connecting Thousands of Services at LY Corporation with Central Dogma Control Plane

Migrating Microservices to Modular monolith and Monorepo to reduce operating costs

「Yahoo!オークション」や「Yahoo!路線情報」などを支える、イベント内容に合致する通知設定の抽出プラットフォームをレガシーシステムから移行した際のあれこれ / Various Aspects When Migrating the Notification Setting Extraction Platform Supporting "Yahoo! JAPAN Auction" and "Yahoo! JAPAN Transit Information" from Legacy Systems

「LINE MUSIC」におけるハイブリッド検索や略称抽出を用いた曖昧検索への挑戦 / Challenges in Ambiguous Search Using Hybrid Search and Abbreviation Extraction in "LINE MUSIC"

Pushsphere: LINE's Secret Recipe for Reliable, Prompt and High-Volume Push Notifications

Nginx + Luaを活用したDDoS攻撃対策: 「LINE STORE」における動的IP Blacklist運用とアプローチ / Utilizing Nginx + Lua for DDoS Attack Mitigation: Dynamic IP Blacklist Operation and Approach at "LINE STORE"

AIが生成した画像の品質を測定する方法 / How to measure the quality of AI-Generated Images