Vector Search

Related topics

• autoscaling is part of Vector Search From the official documentation: “Vector Search supports autoscaling, which can automatically resize the number of nodes based on the demands of your workloads.”
• Private Service Connect works with Vector Search From the official documentation: “Enabling Private Service Connect on a Vector Search endpoint is suited for use cases that:”
• Vector Search works with Vertex AI From the official documentation: “Reference architecture for a RAG-capable generative AI application using Vertex AI and Vector Search.”
• Agent Platform Pipelines works with Vector Search From the official documentation: “Pipelines allows for building automated pipelines to generate embeddings, create and update Vector Search indexes, and form an MLOps setup for production search and recommendation systems.”
• Cloud Storage works with Vector Search From the official documentation: “Cloud Storage: You can use the embeddings from a Cloud Storage bucket for building vector indexes and performing Vector Search.”
• Google Cloud Storage works with Vector Search From the official documentation: “Cloud Storage: You can use the embeddings from a Cloud Storage bucket for building vector indexes and performing Vector Search.”
• Shared VPC works with Vector Search From the official documentation: “The following diagram shows a Vector Search architecture in which the Vector Search API is enabled and managed in a service project (`serviceproject`) as part of a [Shared VPC](/vpc/docs/shared-vpc) deployment.”
• Vector Search is part of BigQuery From the official documentation: “This document provides an overview of embeddings and vector search in BigQuery.”
• Vector Search depends on embeddings From the official documentation: “Vector search is built on embeddings.”
• Vector Search is part of Vertex AI From the official documentation: “Vertex AI features for AutoML Forecasting, AutoML Tabular, Batch Prediction, Online Prediction, Pipelines, Training, Vector Search, and Vizier are available in [10 additional Google Cloud regions](/vertex-ai/docs/general/locations#feature-availability).”
• Vector Search works with Virtual Private Cloud From the official documentation: “If you already have a VPC with private services access configured, you can use that VPC to peer with Vector Search.”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• Cloud Run works with Cloud Storage From the official documentation: “Route Cloud Storage events to Cloud Run”
• BigQuery is an alternative to Google Cloud Storage From the official documentation: “The training data can be either a CSV file in Cloud Storage or a table in BigQuery.”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• Dataflow works with Managed Service for Apache Airflow From the official documentation: “Launch Dataflow pipelines with Cloud Composer”
• 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.”
• Cloud Run is an alternative to GKE From the official documentation: “The app uses Cloud SQL, Vertex AI, and either Google Kubernetes Engine (GKE) or Cloud Run.”
• Cloud Storage works with Managed Service for Apache Airflow From the official documentation: “Managed Airflow associates a Cloud Storage bucket with your environment.”
• Managed Service for Apache Airflow works with Shared VPC From the official documentation: “Make sure that you configured Shared VPC networking for Managed Airflow.”
• Shared VPC works with VPC Service Controls From the official documentation: “If you use both Shared VPC and VPC Service Controls, the host project that contains the network and the service project that contains the Managed Lustre instance must both be inside the same perimeter.”
• BigQuery works with Managed Service for Apache Airflow From the official documentation: “You can use Managed Airflow to orchestrate services in your data pipelines, such as triggering a job in BigQuery or starting a Dataflow pipeline.”
• Vertex AI is part of Gemini Enterprise Agent Platform From the official documentation: “Vertex AI's services are now part of Gemini Enterprise Agent Platform.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• VPC Service Controls secures Managed Service for Apache Airflow From the official documentation: “Managed Airflow can be selected as a secured service inside a VPC Service Controls perimeter.”
• Cloud Run works with Google Cloud Storage From the official documentation: “The Cloud Run function will receive syslog messages from FortiEDR via HTTP and write them to GCS.”
• Cloud Run works with Vertex AI From the official documentation: “The Cloud Run service can interact with Vertex AI services.”
• Managed Service for Apache Airflow depends on GKE From the official documentation: “Managed Airflow runs your workloads on GKE.”
• Managed Service for Apache Airflow works with VPC Service Controls From the official documentation: “When used with Managed Airflow, VPC Service Controls have several [known limitations](/vpc-service-controls/docs/supported-products#composer).”
• Private Service Connect works with VPC Service Controls From the official documentation: “VPC Service Controls that use Private Service Connect”
• VPC Service Controls secures Gemini Enterprise Agent Platform From the official documentation: “The API for Agent Platform can be protected by VPC Service Controls and the product can be used normally inside service perimeters.”
• BigQuery works with Cloud Run From the official documentation: “You can then use Cloud Run to transcode data present in the bucket and move it to BigQuery.”
• BigQuery works with Vertex AI From the official documentation: “The page provides guidance for getting predictions from Vertex AI, based on retail [data exported into BigQuery](/retail/docs/export-data-into-bq).”
• Cloud Run works with GKE From the official documentation: “Leverage Google Kubernetes Engine (GKE) and Cloud Run to deploy applications to the Google Cloud, optimizing costs, performance, and management overhead.”
• Cloud Run works with Shared VPC From the official documentation: “To see which Cloud Run resources are using the Shared VPC network, run the following command:”
• Cloud Storage works with Gemini Enterprise Agent Platform From the official documentation: “This page describes how to use Gemini Enterprise Agent Platform to export your image AutoML Edge models to Cloud Storage.”
• Dataflow depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
• Dataflow depends on Google Cloud Storage From the official documentation: “- A gcs bucket for staging DataFlow files. Replace `<BUCKET_NAME>`: the name of a valid Google Cloud Storage bucket.”
• Dataflow works with Google Cloud Storage From the official documentation: “Data is transferred between Spanner and Cloud Storage using Dataflow.”
• Dataflow works with Shared VPC From the official documentation: “The following error occurs when you run a Dataflow job on a Shared VPC network:”
• Gemini Enterprise Agent Platform works with Private Service Connect From the official documentation: “Use Private Service Connect to access Agent Platform from on-premises”
• Managed Service for Apache Airflow depends on Google Cloud Storage From the official documentation: “Managed Airflow uses a [Cloud Storage](/storage) bucket to store DAGs of your Managed Airflow environment.”
• Shared VPC is an alternative to Virtual Private Cloud From the official documentation: “From the **Network** drop-down, select a VPC or a Shared VPC network.”
• VPC Service Controls secures Google Cloud Storage From the official documentation: “Storage Transfer Service supports on-premises transfers to Cloud Storage buckets protected by VPC Service Controls, under the following conditions:”
• Agent Platform Pipelines depends on Cloud Storage From the official documentation: “Agent Platform Pipelines stores the artifacts of your pipeline runs using Cloud Storage.”
• Agent Platform Pipelines is part of Gemini Enterprise Agent Platform From the official documentation: “With Agent Platform Pipelines, you can use BigQuery operators to plug any BigQuery jobs (including BigQuery ML) into an ML pipeline.”
• autoscaling is part of Cloud Run From the official documentation: “When using autoscaling, each Cloud Run revision is automatically scaled to the number of instances needed to handle all incoming requests, events, or CPU utilization.”
• autoscaling is part of GKE From the official documentation: “Verify that GKE node pools have autoscaling enabled to handle variable workloads.”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• BigQuery is an alternative to Dataflow From the official documentation: “To automate the EDA process, use BigQuery or a managed data processing service like Dataflow.”
• BigQuery works with GKE From the official documentation: “Subsequently, by integrating BigQuery with GKE, you can use BigQuery to efficiently handle massive datasets (like Google Analytics) and the model's natural language understanding capabilities to generate meaningful insights.”
• 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.”
• BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Cloud Run works with Dataflow From the official documentation: “Route Dataflow events to Cloud Run”
• Cloud Run is an alternative to Gemini Enterprise Agent Platform From the official documentation: “The application that's deployed on Cloud Run or on Gemini Enterprise routes the request to the SOC manager.”
• Cloud Run works with Virtual Private Cloud From the official documentation: “Send outbound traffic from Cloud Run to a VPC network.”