This workshop aims to teach basic Feast concepts and walk you through how to achieve common architectures.
This workshop assumes you have the following installed:
- A local development environment that supports running Jupyter notebooks (e.g. VSCode with Jupyter plugin)
- Python 3.7+
- pip
- Docker & Docker Compose (e.g.
brew install docker docker-compose)
See also: Feast quickstart
| Description | Module |
|---|---|
| Setting up Feast projects & CI/CD + powering batch predictions | Module 0 |
| Online feature retrieval with Kafka, Spark, Redis | Module 1 |
| On demand feature views | Module 2 |
| Versioning features / models in Feast | TBD |
| Data quality monitoring in Feast | TBD |
| Feature server deployment (embed, separate service, or via AWS Lambda) | TBD |