- Sample use-case tutorials
- Validating historical features with Great Expectations
- Building streaming features
- Retrieval Augmented Generation (RAG) with Feast
- RAG Fine Tuning with Feast and Milvus
- MCP - AI Agent Example
- Running Feast with Snowflake/GCP/AWS
- Running Feast in production (e.g. on Kubernetes)
- Feast on Kubernetes
- Online Server Performance Tuning
- Customizing Feast
- Adding or reusing tests
- Starting Feast servers in TLS(SSL) Mode
- Importing Features from dbt
- Codebase Structure
- Type System
- Data sources
- Offline stores
- Online stores
- Registries
- Providers
- Compute Engines
- Feature repository
- Feature servers
- [Beta] Web UI
- [Beta] On demand feature view
- [Alpha] Static Artifacts Loading
- [Alpha] Vector Database
- [Alpha] Data quality monitoring
- [Alpha] Streaming feature computation with Denormalized
- [Alpha] Feature View Versioning
- OpenLineage Integration
- Feast CLI reference
- Python API reference
- Usage