Overview of Home Intelligent Recommendation System: Architecture, Design, and Observability

In recent years, rapid growth of network and mobile internet has led to massive user and content scale for Home, creating knowledge anxiety for users and information overload for content, prompting the development of an intelligent recommendation system that connects users and content.

The system provides value in four aspects: personalized content for users, feedback and ecosystem growth for content providers, commercial monetization for advertisers and partners, and traffic efficiency and revenue improvement for the platform.

Business challenges of the previous siloed recommendation system include low feature reuse, high deployment and maintenance cost, and steep learning curve. To address these, Home adopts a platform‑based architecture with three pillars: business capability standardization, technical capability framework, and observability.

The technical framework consists of an operation platform (Beidou) for visual configuration, data and interface standardization to enable reuse, and a service architecture built from a base package and micro‑services (API, engine, recall, ranking, profile, index, rendering, packaging, etc.).

Service scheduling and observability are realized through log (ELK), metric (Tianyan) and tracing (Time Machine) components, forming the three pillars of observability that allow proactive monitoring and debugging.

Today the system serves tens of millions of users across more than 200 recommendation scenarios, and future work aims to further improve user experience, retention, activity, and ARPU while reducing commercial loss.