discovery service

Related topics

• discovery service works with Knowledge Catalog From the official documentation: “Additionally, discovery can connect to other Google Cloud services like Security Command Center, Google Security Operations, and Knowledge Catalog to enrich security operations and data management.”
• discovery service is part of Sensitive Data Protection From the official documentation: “This page shows you how to resolve issues with the discovery service of Sensitive Data Protection.”
• discovery service works with Vertex AI From the official documentation: “This page describes Sensitive Data Protection discovery for use with Vertex AI.”
• 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: “Sample to load Avro data from Cloud Storage into a new BigQuery table”
• BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• Model Armor works with Vertex AI From the official documentation: “The following example enables Model Armor on a Vertex AI endpoint.”
• Pub/Sub works with Sensitive Data Protection From the official documentation: “Inspect Datastore, using Pub/Sub for job status notifications.”
• BigQuery works with Knowledge Catalog From the official documentation: “Some Knowledge Catalog functionalities trigger job execution using BigQuery.”
• Cloud Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
• Model Armor works with Sensitive Data Protection From the official documentation: “Sensitive Data Protection and Model Armor work together in Gemini Enterprise to provide a layered security defense for your data.”
• BigQuery works with Pub/Sub From the official documentation: “createBigQuerySubscription creates a Pub/Sub subscription that exports messages to BigQuery.”
• Cloud Storage is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• Cloud Storage works with Pub/Sub From the official documentation: “| **Google Cloud** | Cloud Storage | Pub/Sub |”
• BigQuery is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• 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).”
• Model Armor secures Vertex AI From the official documentation: “The following example enables Model Armor on a Vertex AI endpoint.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• Cloud Monitoring works with Knowledge Catalog From the official documentation: “Knowledge Catalog is integrated with Monitoring, which collects metrics, events, and metadata from Knowledge Catalog services.”
• Cloud Monitoring works with Model Armor From the official documentation: “This graph uses the metrics that Model Armor publishes to Cloud Monitoring.”
• Cloud Monitoring works with Pub/Sub From the official documentation: “Use Cloud Monitoring and Pub/Sub to set up custom monitoring and alerting policies for exported logs.”
• Cloud Storage works with Knowledge Catalog From the official documentation: “Knowledge Catalog is an intelligent governance solution for data and AI assets in Google Cloud. It provides a centralized inventory where you can discover, manage, and govern your data across Google Cloud data sources like BigQuery, Cloud Storage, Pub/Sub, and Spanner.”
• Knowledge Catalog works with Pub/Sub From the official documentation: “When an entry or aspect is created, updated, or deleted, Knowledge Catalog publishes a notification message to a Pub/Sub topic that you specify.”
• Knowledge Catalog works with Sensitive Data Protection From the official documentation: “This page describes how to automatically add Knowledge Catalog aspects to your data after Sensitive Data Protection profiles your resources.”
• Sensitive Data Protection works with VPC Service Controls From the official documentation: “For information about VPC Service Controls support for Sensitive Data Protection, see the [Supported products](/vpc-service-controls/docs/supported-products#table_dlp) table in the VPC Service Controls documentation.”
• VPC Service Controls secures Knowledge Catalog From the official documentation: “It explains how to use VPC Service Controls to create service perimeters that protect your Knowledge Catalog resources and mitigate data exfiltration risks.”
• 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 works with Model Armor From the official documentation: “If you need to log the data that goes through the Model Armor template, you can reroute logs to a secure storage like BigQuery, which offers stricter access controls.”
• 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 Monitoring works with Sensitive Data Protection From the official documentation: “Sensitive Data Protection sends detailed telemetry about your Sensitive Data Protection usage to Monitoring.”
• Cloud Monitoring works with VPC Service Controls From the official documentation: “Cloud Monitoring performs the VPC perimeter check when a project is *added* to a metrics scope:”
• Cloud Storage works with Vertex AI From the official documentation: “Access Cloud Storage content through your current project's Vertex AI service agent.”
• Knowledge Catalog works with VPC Service Controls From the official documentation: “The integration between Looker (Google Cloud core) and Knowledge Catalog supports VPC Service Controls.”
• VPC Service Controls secures Cloud Monitoring From the official documentation: “VPC Service Controls provides additional security for Cloud Monitoring to help mitigate the risk of data exfiltration.”
• VPC Service Controls secures Pub/Sub From the official documentation: “If you use [VPC Service Controls](/vpc-service-controls/docs/overview) and your Pub/Sub topic is part of a project inside a service perimeter, you must grant access to projects in order to create notifications.”
• VPC Service Controls secures Sensitive Data Protection From the official documentation: “VPC Service Controls enables you to define a security perimeter around your projects and resources, including Sensitive Data Protection resources.”