batch inference

Related topics

• batch inference works with BigQuery From the official documentation: “This page describes how to get batch inferences using BigQuery.”
• batch inference works with Cloud Storage From the official documentation: “Batch inference for Gemini models accepts one JSON Lines (JSONL) file stored in Cloud Storage as input data.”
• batch inference is part of Gemini Enterprise Agent Platform From the official documentation: “Gemini Enterprise Agent Platform provides two options for projecting future values using your trained forecast model: online inferences and batch inference.”
• batch inference works with Google Cloud Storage From the official documentation: “Batch text prediction with Gemini model using Google Cloud Storage”
• batch inference works with model monitoring From the official documentation: “Optional: [**Model Monitoring**](/gemini-enterprise-agent-platform/machine-learning/model-monitoring/overview) analysis for batch inferences is available in [Preview](https://cloud.google.com/products/#product-launch-stages).”
• batch inference is an alternative to online inference From the official documentation: “Gemini Enterprise Agent Platform provides two options for projecting future values using your trained forecast model: online inferences and batch inference.”
• batch inference is an alternative to Standard PayGo From the official documentation: “For asynchronous jobs such as processing large datasets, batch processing is significantly cheaper (50%) than processing requests sequentially using Standard PayGo.”
• 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 Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• Cloud Logging works with Customer-managed encryption keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• 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”
• 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 works with Gemini Enterprise Agent Platform From the official documentation: “The BigQuery dataset stores all versions for the associated Gemini Enterprise Agent Platform dataset.”
• 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.”
• Cloud Storage works with Customer-managed encryption keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
• Cloud Storage works with Identity and Access Management From the official documentation: “To learn how to use IAM with Cloud Storage, see [Using IAM Permissions](/storage/docs/access-control/using-iam-permissions).”
• 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.”
• 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 Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• 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.”
• 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.”
• Cloud Logging works with Cloud Monitoring From the official documentation: “If a log entry matches the filter of the alerting policy, then Cloud Logging extracts labels and forwards the data to Cloud Monitoring.”
• Cloud Logging works with Cloud Run From the official documentation: “Cloud Logging captures, stores, and analyzes Cloud Run logs.”
• Cloud Logging is an alternative to Google Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs in a Cloud Logging bucket, in a user-created Cloud Storage bucket, or in a Google Cloud-created and user-owned Cloud Storage bucket.”
• Cloud Monitoring works with Cloud Run From the official documentation: “Cloud Monitoring records metrics regarding the execution of Cloud Run.”
• Cloud Run works with Identity and Access Management From the official documentation: “Cloud Run also offers the ability to control access to a service with Identity and Access Management (IAM).”
• 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.”
• Customer-managed encryption keys secures Cloud Logging From the official documentation: “Cloud Logging supports encrypting Log storage with CMEK keys.”
• 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.”
• Identity and Access Management secures Gemini Enterprise Agent Platform From the official documentation: “Agent Platform uses IAM to manage access to resources.”
• Identity and Access Management works with VPC Service Controls From the official documentation: “VPC Service Controls perimeters and Identity and Access Management (IAM) roles work together.”
• 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:”
• 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 VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Cloud Logging is an alternative to Cloud Monitoring From the official documentation: “To see the status of your invalidation request or find a definitive list of recently submitted requests, you can use Cloud Logging or Cloud Monitoring.”
• Cloud Logging is an alternative to Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs either in Cloud Logging or in a user-created Cloud Storage bucket.”
• Cloud Logging works with Gemini Enterprise Agent Platform From the official documentation: “This page provides information about how to use Cloud Logging to view details about a Gemini Enterprise Agent Platform model.”
• Cloud Logging works with Google Cloud Storage From the official documentation: “See [Routing and storage overview](/logging/docs/routing/overview) to route logs from Logging to Cloud Storage, BigQuery, or Pub/Sub.”
• Cloud Logging works with model monitoring From the official documentation: “Model Monitoring automatically notifies you of detected anomalies through email, but you can also set up alerts through Cloud Logging and Cloud Monitoring notification channels.”
• Cloud Logging works with VPC Service Controls From the official documentation: “This page describes how you can find VPC Service Controls errors using Cloud Logging.”
• 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 Google Cloud Storage From the official documentation: “You can configure Cloud Storage client libraries to to generate gRPC related metrics in Cloud Monitoring.”
• Cloud Monitoring depends on Identity and Access Management From the official documentation: “To use Monitoring, you must have the appropriate [Identity and Access Management](/iam/docs/overview) (IAM) permissions.”
• Cloud Monitoring works with model monitoring From the official documentation: “Each time a scheduled monitoring pipeline run fails, Model Monitoring sends a notification to the Cloud Monitoring notification channels you specified when creating the Model Monitoring job.”
• 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 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.”
• Customer-managed encryption keys secures Cloud Run From the official documentation: “If you want to control your encryption keys, then you can use customer-managed encryption keys (CMEKs) in [Cloud KMS](/kms/docs) with CMEK-integrated services including Cloud Run.”
• 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.”
• 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 Google Cloud Storage From the official documentation: “This page describes how to use Gemini Enterprise Agent Platform to export your AutoML tabular model to Cloud Storage, download the model to an on-premises server or a server hosted by another cloud provider, and then use Docker to make the model available for predictions.”