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  • Introduction
  • Quickstart
  • Getting started
    • Install Feast
    • Create a feature repository
    • Deploy a feature store
    • Build a training dataset
    • Load data into the online store
    • Read features from the online store
  • Community
  • Roadmap
  • Changelog
  • Concepts
    • Overview
    • Feature view
    • Data model
    • Online store
    • Offline store
    • Provider
    • Architecture
  • Reference
    • Data sources
      • BigQuery
      • File
    • Offline stores
      • File
      • BigQuery
    • Online stores
      • SQLite
      • Redis
      • Datastore
    • Providers
      • Local
      • Google Cloud Platform
    • Feature repository
      • feature_store.yaml
      • .feastignore
    • Feast CLI reference
    • Python API reference
    • Usage
  • Feast on Kubernetes
    • Getting started
      • Install Feast
        • Docker Compose
        • Kubernetes (with Helm)
        • Amazon EKS (with Terraform)
        • Azure AKS (with Helm)
        • Azure AKS (with Terraform)
        • Google Cloud GKE (with Terraform)
        • IBM Cloud Kubernetes Service (IKS) and Red Hat OpenShift (with Kustomize)
      • Connect to Feast
        • Python SDK
        • Feast CLI
      • Learn Feast
    • Concepts
      • Overview
      • Architecture
      • Entities
      • Sources
      • Feature Tables
      • Stores
    • Tutorials
      • Minimal Ride Hailing Example
    • User guide
      • Overview
      • Getting online features
      • Getting training features
      • Define and ingest features
      • Extending Feast
    • Reference
      • Configuration Reference
      • Feast and Spark
      • Metrics Reference
      • Limitations
      • API Reference
        • Go SDK
        • Java SDK
        • Core gRPC API
        • Python SDK
        • Serving gRPC API
        • gRPC Types
    • Advanced
      • Troubleshooting
      • Metrics
      • Audit Logging
      • Security
      • Upgrading Feast
  • Contributing
    • Contribution process
    • Development guide
    • Versioning policy
    • Release process
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  1. Feast on Kubernetes
  2. Reference

API Reference

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Last updated 3 years ago

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Please see the following API specific reference documentation:

  • : This is the gRPC API used by Feast Core. This API contains RPCs for creating and managing feature sets, stores, projects, and jobs.

  • : This is the gRPC API used by Feast Serving. It contains RPCs used for the retrieval of online feature data or historical feature data.

  • : These are the gRPC types used by both Feast Core, Feast Serving, and the Go, Java, and Python clients.

  • : The Go library used for the retrieval of online features from Feast.

  • : The Java library used for the retrieval of online features from Feast.

  • : This is the complete reference to the Feast Python SDK. The SDK is used to manage feature sets, features, jobs, projects, and entities. It can also be used to retrieve training datasets or online features from Feast Serving.

Community Contributions

The following community provided SDKs are available:

  • : A Node.js SDK written in TypeScript. The SDK can be used to manage feature sets, features, jobs, projects, and entities.

Feast Core gRPC API
Feast Serving gRPC API
Feast gRPC Types
Go Client SDK
Java Client SDK
Python SDK
Node.js SDK