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Alibaba Cloud Native
Alibaba Cloud Native
Mar 20, 2026 · Cloud Native

How a Gaming Platform Scaled to Millions with RocketMQ & Kafka: A Cloud‑Native Success Story

Facing explosive growth, the game‑service platform 悠悠有品 rebuilt its architecture on Alibaba Cloud, using RocketMQ for core transaction messaging and Kafka for data synchronization, achieving elastic scaling, high availability, cost reduction, and reliable high‑concurrency processing across its trading and analytics pipelines.

KafkaMessagingRocketMQ
0 likes · 8 min read
How a Gaming Platform Scaled to Millions with RocketMQ & Kafka: A Cloud‑Native Success Story
Bilibili Tech
Bilibili Tech
Jul 25, 2023 · Artificial Intelligence

Bilibili Game Center Recommendation System: Architecture, Core Technologies, and Experimental Results

The Bilibili Game Center recommendation system combines a unified feature platform, multi‑stage recall, ranking and re‑ranking models, online services, and AB experimentation to deliver personalized game suggestions, resulting in up to 78% higher click‑through, 76% higher conversion, and substantial increases in user engagement and revenue.

AB testingfeature engineeringgame-platform
0 likes · 26 min read
Bilibili Game Center Recommendation System: Architecture, Core Technologies, and Experimental Results
vivo Internet Technology
vivo Internet Technology
Jun 29, 2022 · Operations

Intelligent Gray Release Data Analysis System Practice for Game Center

The article details vivo Game Center’s end‑to‑end intelligent gray‑release data analysis system, which combines experimental design, statistical significance testing, multi‑dimensional anomaly root‑cause analysis (via the Adtributor algorithm), automated reporting, and sample‑size estimation to enable scientific version evaluation, rapid issue detection, and a fast closed‑loop verification process for game updates.

Vivoab-testingadtributor
0 likes · 14 min read
Intelligent Gray Release Data Analysis System Practice for Game Center
DataFunSummit
DataFunSummit
Dec 22, 2020 · Artificial Intelligence

Angel Recommendation Algorithms for Game Platforms

This article introduces Tencent's self‑developed Angel distributed machine‑learning platform and demonstrates how its recommendation algorithms, including classic linear models, collaborative filtering, and the non‑linear DeepFM model, are applied to game recommendation scenarios such as Steam, WeGame, and the Tesla platform.

collaborative filteringdeepfmgame-platform
0 likes · 10 min read
Angel Recommendation Algorithms for Game Platforms