recommendation-system - Production Recommendation System Architecture
Deploy scalable recommendation APIs with feature stores, tiered caching, model serving, A/B testing, and quality monitoring.
Tags
Updated: 2026-09-28Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Deploy recommendation APIs
- Manage user features
- Serve multiple models
- Implement tiered caching
- Run A/B tests
- Monitor recommendation quality
- Track recommendation metrics
- Handle cache invalidation
Inputs
- User IDs
- Item data
- User events
- User and item features
- Recommendation requests
- Recommendation models
Outputs
- Personalized recommendations
- Recommendation API responses
- Health status responses
- Cached recommendations
- Cached feature values
- Prometheus metrics
Requirements
- Python environment
- FastAPI 0.109.0
- Redis 5.0.0
- Prometheus client 0.19.0
- Redis service
- Uvicorn runtime