Ray on Gemini Enterprise Agent Platform

Related topics

• BigQuery works with Ray on Gemini Enterprise Agent Platform From the official documentation: “# Use Ray on Agent Platform with BigQuery”
• Dataflow works with Ray on Gemini Enterprise Agent Platform From the official documentation: “Use Ray for distributed data preprocessing with [Dataflow](/dataflow/docs/overview) or [Managed Service for Apache Spark](/dataproc/docs/concepts/overview), accelerated model training, scalable hyperparameter tuning, reinforcement learning, and parallelized batch prediction.”
• Managed Service for Apache Spark works with Ray on Gemini Enterprise Agent Platform From the official documentation: “Use Ray for distributed data preprocessing with [Dataflow](/dataflow/docs/overview) or [Managed Service for Apache Spark](/dataproc/docs/concepts/overview), accelerated model training, scalable hyperparameter tuning, reinforcement learning, and parallelized batch prediction.”
• Ray on Gemini Enterprise Agent Platform is part of Gemini Enterprise Agent Platform From the official documentation: “If you're connected to your Ray cluster on Gemini Enterprise Agent Platform, restart your kernel and run the following code.”
• 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”
• 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 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.”
• 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”
• 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.”
• BigQuery works with Managed Service for Apache Spark From the official documentation: “This means you can quickly read and write BigQuery data to and from Managed Service for Apache Spark.”
• 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.”
• 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.”
• BigQuery is an alternative to Managed Service for Apache Spark From the official documentation: “Run queries against your federated data using BigQuery or Managed Service for Apache Spark.”
• Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
• Cloud Storage works with Managed Service for Apache Spark From the official documentation: “Managed Service for Apache Spark accesses these files on Cloud Storage.”
• Dataflow is an alternative to Managed Service for Apache Spark From the official documentation: “For more complex data loads into your Cloud SQL for PostgreSQL database, consider using Dataflow or Managed Service for Apache Spark, which involves creating an ETL process.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Managed Service for Apache Spark depends on Cloud Storage From the official documentation: “Managed Service for Apache Spark uses Cloud Storage as its default distributed file system.”
• 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.”
• 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 Dataflow From the official documentation: “Information stored in [Cloud Logging](/logging/docs/region-support) is primarily generated by the code in your Dataflow program.”
• 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 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.”
• Customer-managed encryption keys secures Managed Service for Apache Spark From the official documentation: “For data encryption at rest, use the [Cloud Key Management Service](/kms/docs/key-management-service) (KMS) or [Customer Managed Encryption Keys](/managed-spark/docs/concepts/configuring-clusters/customer-managed-encryption) (CMEK).”
• 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.”
• 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 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 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 Managed Service for Apache Spark From the official documentation: “Use [Cloud Logging](/logging) to view logs from the Managed Service for Apache Spark Autoscaler.”
• 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 works with Managed Service for Apache Spark From the official documentation: “Monitoring uses workload metadata and metrics to provide insights into the health and performance of Managed Service for Apache Spark workloads.”
• 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:”
• Customer-managed encryption keys works with Dataflow From the official documentation: “This sample shows how to use encryption keys managed by the customer, with a Dataflow pipeline.”
• Customer-managed encryption keys secures Dataflow From the official documentation: “You can either create CMEKs manually to protect your Dataflow resources or use Cloud KMS Autokey.”
• 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.”
• Dataflow works with VPC Service Controls From the official documentation: “To customize DNS resolution when using Dataflow with VPC Service Controls, use Cloud DNS [private zones](/dns/docs/overview#dns-private-zones) instead of using custom BIND servers.”
• 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.”
• Gemini Enterprise Agent Platform works with VPC Service Controls From the official documentation: “For information on using Gemini Enterprise Agent Platform VPC Service Controls, see [VPC Service Controls with Gemini Enterprise Agent Platform](/gemini-enterprise-agent-platform/machine-learning/general/vpc-service-controls).”