Agent Platform endpoint

Related topics

• endpoint configures Agent Platform endpoint From the official documentation: “* `ENDPOINT`: a `STRING` value that specifies the Agent Platform endpoint to use for the model.”
• Agent Platform endpoint works with Cloud resource connection From the official documentation: “BigQuery uses a [Cloud resource connection](/bigquery/docs/create-cloud-resource-connection) to interact with the Gemini Enterprise Agent Platform endpoint.”
• Agent Platform endpoint works with model From the official documentation: “If the model was previously undeployed, setting this option to `TRUE` redeploys the model to an Agent Platform endpoint.”
• BigQuery configures Agent Platform endpoint From the official documentation: “If you specify a short endpoint name that omits the region, such as `gemini-3.5-flash`, then BigQuery selects an endpoint according to the following rules:”
• 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”
• customer-managed encryption keys secures Cloud Storage From the official documentation: “CMEKs encrypt data at rest in Cloud SQL, Cloud Storage, and within GKE clusters.”
• 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 Spanner From the official documentation: “Federated analytics seamlessly combine data from Spanner and other sources in BigQuery.”
• 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 Storage works with customer-managed encryption keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
• customer-managed encryption keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
• Cloud resource connection works with Cloud Storage From the official documentation: “Cloud resource connection lets BigQuery access Cloud Storage object data and metadata using its own service account.”
• Cloud resource connection works with Gemini Enterprise Agent Platform From the official documentation: “BigQuery uses a [Cloud resource connection](/bigquery/docs/create-cloud-resource-connection) to interact with the Gemini Enterprise Agent Platform endpoint.”
• Cloud Storage works with Gemini Enterprise Agent Platform From the official documentation: “When you perform custom training, Agent Platform usually loads your data from Cloud Storage.”
• customer-managed encryption keys secures Gemini Enterprise Agent Platform From the official documentation: “Enable customer-managed encryption keys (CMEK) for the Gemini Enterprise Agent Platform to gain more control over data encryption and key management.”
• BigQuery works with Cloud resource connection From the official documentation: “After you create the training dataset, you establish a connection to link BigQuery and external sources.”
• Cloud resource connection is part of BigQuery From the official documentation: “A Cloud resource connection in BigQuery lets you connect BigQuery to other Google Cloud services and external storage by using a dedicated service account with delegated access.”
• Cloud resource connection depends on service account From the official documentation: “A Cloud resource connection in BigQuery lets you connect BigQuery to other Google Cloud services and external storage by using a dedicated service account with delegated access.”
• Cloud resource connection works with service account From the official documentation: “When you create a connection resource, BigQuery creates a unique system service account and associates it with the connection.”
• Cloud resource connection works with Spanner From the official documentation: “A Cloud resource connection associated with a service account is used to connect to the Spanner.”
• Cloud Storage works with service account From the official documentation: “The service account can manage objects in the Cloud Storage bucket.”
• customer-managed encryption keys depends on Cloud Storage From the official documentation: “If used for storing Customer-managed Encryption Keys (CMEK): Cloud Storage (See [Cloud Storage pricing](/storage/pricing).)”
• endpoint works with model From the official documentation: “Deploy the model resource to a serving Endpoint resource.”
• Google Cloud Storage works with Spanner From the official documentation: “- Export any Spanner database into a Cloud Storage bucket using either Avro or CSV file formats.”
• service account is part of Cloud resource connection From the official documentation: “When you create a connection resource, BigQuery creates a unique system service account and associates it with the connection.”
• BigQuery depends on Cloud resource connection From the official documentation: “BigQuery uses a [Cloud resource connection](/bigquery/docs/create-cloud-resource-connection) to interact with the Cloud AI service.”
• 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 service account From the official documentation: “The service account can be used by services, such as Cloud Run, to read and modify data in the BigQuery dataset.”
• Cloud resource connection depends on Cloud Storage From the official documentation: “- `CONNECTION_ID`: A `STRING` value that contains a [Cloud resource connection](/bigquery/docs/create-cloud-resource-connection) that the service can use to access the objects in Cloud Storage, in the format `location.connection_id`.”
• Cloud resource connection secures Google Cloud Storage From the official documentation: “This connection acts as a secure, delegated identity that BigQuery uses to manage and read your Iceberg files. This helps ensure that individual users never have direct access to your Cloud Storage bucket.”
• Cloud Storage works with Spanner From the official documentation: “Move Spanner databases to and from Avro or CSV files stored in Cloud Storage.”
• customer-managed encryption keys is part of BigQuery From the official documentation: “If you require more control over encryption keys, BigQuery supports [customer-managed encryption keys](/bigquery/docs/customer-managed-encryption) in the [Cloud Key Management Service](/kms/docs).”
• customer-managed encryption keys is part of Cloud Storage From the official documentation: “[Cloud Storage](/storage/docs/introduction) provides features such as customer-managed encryption, lifecycle management, and aging and retention policies.”
• customer-managed encryption keys secures endpoint From the official documentation: “For **endpoints**, all model files used for the model deployment under the endpoint are CMEK-encrypted.”
• customer-managed encryption keys secures Google Cloud Storage From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
• customer-managed encryption keys secures model From the official documentation: “For **models**, the models stored in the storage system (for example, disk) are CMEK-encrypted.”
• customer-managed encryption keys works with Spanner From the official documentation: “`SPANNER_PROJECT` - A Google Cloud project that contains a Spanner instance which uses the customer-managed encryption keys (CMEKs) that reside in `KEY_PROJECT`.”
• customer-managed encryption keys secures Spanner From the official documentation: “To learn how to use manually-created CMEKs to protect your Spanner resources, see [Secure a database with CMEK](/spanner/docs/use-cmek).”
• Gemini Enterprise Agent Platform depends on Cloud Storage From the official documentation: “Certain tasks in Agent Platform require that you use additional Google Cloud products besides Agent Platform. For example, in most cases, you must use Cloud Storage and Artifact Registry when you create a custom training pipeline.”
• Gemini Enterprise Agent Platform works with Spanner From the official documentation: “MODEL DDL statements and ML functions in Spanner invoke Gemini Enterprise Agent Platform endpoints and can fail due to various reasons:”
• model depends on endpoint From the official documentation: “You must deploy the model to an endpoint before the model can be used to serve online inferences.”
• model is part of Gemini Enterprise Agent Platform From the official documentation: “`Model`, this resource is available in Gemini Enterprise Agent Platform.”
• service account depends on BigQuery From the official documentation: “Each feature view uses a service account to access the source data in BigQuery during sync.”
• service account depends on Google Cloud Storage From the official documentation: “Google SecOps uses a unique service account to read data from your GCS bucket. You must grant this service account access to your bucket.”
• service account works with Spanner From the official documentation: “The service account has access to the Spanner instance.”