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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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  • Overview
  • 1. Requirements
  • 2. Configure Terraform
  • 3. Apply

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  1. Feast on Kubernetes
  2. Getting started
  3. Install Feast

Google Cloud GKE (with Terraform)

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Last updated 3 years ago

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Overview

This guide installs Feast on GKE using our .

The Terraform configuration used here is a greenfield installation that neither assumes anything about, nor integrates with, existing resources in your GCP account. The Terraform configuration presents an easy way to get started, but you may want to customize this set up before using Feast in production.

This Terraform configuration creates the following resources:

  • GKE cluster

  • Feast services running on GKE

  • Google Memorystore (Redis) as online store

  • Dataproc cluster

  • Kafka running on GKE, exposed to the dataproc cluster via internal load balancer

1. Requirements

  • Install > = 0.12 (tested with 0.13.3)

  • Install (tested with v3.3.4)

  • GCP and sufficient to create the resources listed above.

2. Configure Terraform

Create a .tfvars file underfeast/infra/terraform/gcp. Name the file. In our example, we use my_feast.tfvars. You can see the full list of configuration variables in variables.tf. Sample configurations are provided below:

my_feast.tfvars
gcp_project_name        = "kf-feast"
name_prefix             = "feast-0-8"
region                  = "asia-east1"
gke_machine_type        = "n1-standard-2"
network                 = "default"
subnetwork              = "default"
dataproc_staging_bucket = "feast-dataproc"

3. Apply

After completing the configuration, initialize Terraform and apply:

$ cd feast/infra/terraform/gcp
$ terraform init
$ terraform apply -var-file=my_feast.tfvars
reference Terraform configuration
Terraform
Helm
authentication
privilege