Bigtable online serving

Related topics

• Bigtable online serving is an alternative to Optimized online serving From the official documentation: “Depending on the type of online serving you've configured for your online store, you can serve feature values in one of the following ways: - Fetch feature values by using Bigtable online serving. - Fetch feature values by using Optimized online serving with a public endpoint.”
• BigQuery works with Bigtable online serving From the official documentation: “If you want to use continuous data sync to sync data from the BigQuery data source to your feature views in near real-time, use Bigtable online serving.”
• Bigtable online serving is part of Agent Platform Feature Store From the official documentation: “In this tutorial, you learn how to use Bigtable online serving in Vertex AI Feature Store for online serving and fetching of feature values in BigQuery.”
• Bigtable online serving is part of Vertex AI Feature Store From the official documentation: “In this tutorial, you learn how to use Bigtable online serving in Vertex AI Feature Store for online serving and fetching of feature values in BigQuery.”
• BigQuery works with Knowledge Catalog From the official documentation: “Some Knowledge Catalog functionalities trigger job execution using BigQuery.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• Agent Platform Feature Store works with BigQuery From the official documentation: “In this tutorial, you learn how to use Bigtable online serving in Vertex AI Feature Store for online serving and fetching of feature values in BigQuery.”
• BigQuery works with Vertex AI Feature Store From the official documentation: “In the new Vertex AI Feature Store, BigQuery serves as the offline store.”
• BigQuery works with Gemini Enterprise Agent Platform From the official documentation: “The BigQuery dataset stores all versions for the associated Gemini Enterprise Agent Platform dataset.”
• Data Catalog is an alternative to Knowledge Catalog From the official documentation: “Use Knowledge Catalog for all new projects to take advantage of AI-powered features and enhanced governance.”
• Agent Platform Feature Store is part of Gemini Enterprise Agent Platform From the official documentation: “In the Agent Platform section of the Google Cloud console, go to the **Feature Store** page.”
• BigQuery works with feature view From the official documentation: “A BigQuery table or view directly associated with the feature view.”
• Data Catalog is part of Knowledge Catalog From the official documentation: “Knowledge Catalog features”
• BigQuery works with Data Catalog From the official documentation: “The instructions in this page use both BigQuery and Data Catalog.”
• Gemini Enterprise Agent Platform works with Private Service Connect From the official documentation: “Use Private Service Connect to access Agent Platform from on-premises”
• Optimized online serving works with Private Service Connect From the official documentation: “Fetch feature values by using Optimized online serving with a Private Service Connect endpoint.”
• Optimized online serving is part of Vertex AI Feature Store From the official documentation: “Vertex AI Feature Store offers the following types of online serving that you can use to serve features for online predictions: - [Bigtable online serving](#bigtable_serving) - [Optimized online serving](#optimized_serving)”
• Agent Platform Feature Store works with Knowledge Catalog From the official documentation: “Vertex AI Feature Store is integrated with Knowledge Catalog to track feature metadata.”
• BigQuery works with Private Service Connect From the official documentation: “Click the private zone that contains the DNS records for the Private Service Connect endpoints, which you created to allow BigQuery Toolkit for SAP to privately connect to the BigQuery and IAM APIs.”
• Cloud Monitoring works with Gemini Enterprise Agent Platform From the official documentation: “Gemini Enterprise Agent Platform exports metrics to [Cloud Monitoring](/monitoring/docs).”
• Cloud Monitoring works with Knowledge Catalog From the official documentation: “Knowledge Catalog is integrated with Cloud Monitoring, which collects metrics, events, and metadata from Knowledge Catalog services.”
• Cloud Monitoring works with Private Service Connect From the official documentation: “Private Service Connect exposes key metrics to Cloud Monitoring that give you insights into your Private Service Connect connections.”
• Cloud Monitoring works with Vertex AI Feature Store From the official documentation: “In Cloud Monitoring, the monitored resource type for an online store instance is [`aiplatform.googleapis.com/FeatureOnlineStore`](/monitoring/api/resources#tag_aiplatform.googleapis.com/FeatureOnlineStore).”
• Data Catalog works with Vertex AI Feature Store From the official documentation: “Data Catalog catalogs metadata from Vertex AI Feature Store resources.”
• feature view is part of Agent Platform Feature Store From the official documentation: “Learn how to use a dedicated service agent for a feature view in Agent Platform Feature Store.”
• feature view depends on BigQuery From the official documentation: “A feature view is a logical collection of features materialized from a BigQuery data source to an online store instance.”
• Gemini Enterprise Agent Platform works with Knowledge Catalog From the official documentation: “Knowledge Catalog provides a way to search for your Agent Platform models across projects and regions.”
• Knowledge Catalog works with Vertex AI Feature Store From the official documentation: “Knowledge Catalog is also integrated with Vertex AI Feature Store, offering similar capabilities.”
• Optimized online serving is part of Agent Platform Feature Store From the official documentation: “Optimized online serving in Agent Platform Feature Store supports embedding management.”