Package: feast-azure-provider-temp
Feast on AzureThis project provides resources to enable aFeastfeature store on Azure. There are two options for operating Feast on Azure:Feast Azure Provideris a simple, light-weight architecture that acts as a plugin to allow feast users to connect to Azure hosted offline, online and registry stores.Feast on Azure Kubernetes Service (AKS)is a comprehensive solution, such as a Kubernetes based registry deployment, as well as a Spark based ingestion mechanism.Feast Azure ProviderTheFeast Azure provideracts like a plugin that allows Feast users to connect to:Azure SQL DB and/or Synapse SQL as theoffline storeAzure cache for Redis as theonline storeAzure blob storage for the feastregistry store📐 ArchitectureTheinteroperabledesign of feast means that many Azure services can be used toproduceand/orconsumefeatures (for example: Azure ML, Synapse, Azure Databricks, Azure functions, etc).🐱‍👤 Getting StartedIf you want to install locally:pipinstallfeast-azure-providerWe recommend thegetting started tutorialthat walks you through an end-to-end example.You can deploy the infrastructure for feast using:The only 2 required parameters during the set-up are:Admin Passwordfor the the Dedicated SQL Pool being deployed.Principal IDthis is to set the storage permissions for the feast registry store. You can find the value for this by openingCloud Shelland run the following command:azadsigned-in-usershow--queryobjectId-otsvFeast on Azure Kubernetes Service (AKS)TheFeast on AKSis a secure enterprise deployment on a customer provisioned AKS cluster in an Azure VNET. This deployment does not expose any public endpoints and leverages Azure Private Link over the Feast core and serving so that the traffic flows over the Microsoft Network. This deployment also supports secure connectivity from Azure Synapse Analytics and Azure Machine Learning via private endpoints.📐 Architecture🐱‍👤 Getting StartedPlease refer toFeast on AKSwhich will walkthrough the instructions to setup, install the required packages and then run the sample from Azure Synapse Analytics and Azure Machine Learning.ContributingThis project welcomes contributions and suggestions.  Most contributions require you to agree to a
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