Workload Manager

Related topics

• Compute Engine works with Workload Manager From the official documentation: “Required to view shared rule findings on the Compute Engine Overview page or in Workload Manager.”
• Workload Manager depends on service account From the official documentation: “Workload Manager uses this service account to call other APIs and services for creating resources required for the deployment.”
• BigQuery works with Workload Manager From the official documentation: “Workload Manager does not support exporting evaluation results to multi-regional BigQuery datasets. You can export evaluation results to regional BigQuery datasets.”
• Identity and Access Management secures Workload Manager From the official documentation: “Workload Manager uses Identity and Access Management (IAM) for authorization.”
• VPC Service Controls works with Workload Manager From the official documentation: “This page describes how to configure ingress and egress rules to run Workload Manager evaluations in projects that are protected with VPC Service Controls.”
• 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 Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
• Cloud SQL works with Cloud Storage From the official documentation: “Exports data from a Cloud SQL instance to a Cloud Storage bucket as a SQL dump or CSV file.”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• Compute Engine works with service account From the official documentation: “A common method is to attach a service account to a resource like a Compute Engine instance.”
• 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.”
• Cloud Run works with Cloud SQL From the official documentation: “Connecting from Cloud Run (fully managed) to Cloud SQL”
• Cloud SQL works with Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
• 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 depends on service account From the official documentation: “The Cloud Run function needs a service account with permissions to write to GCS bucket and be invoked by Pub/Sub.”
• Cloud Run works with Google Cloud Storage From the official documentation: “The Cloud Run function needs a service account with permissions to write to GCS bucket.”
• Cloud Storage works with Compute Engine From the official documentation: “For example, you can create a service account that your Compute Engine instances use to access objects stored in Cloud Storage buckets.”
• VPC Service Controls secures Gemini Enterprise Agent Platform From the official documentation: “[VPC Service Controls](/vpc-service-controls/docs/overview) can help you mitigate the risk of data exfiltration from Gemini Enterprise Agent Platform.”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
• Cloud Run works with Cloud Storage From the official documentation: “Receive events from Cloud Storage in a Cloud Run service”
• Cloud Run works with Identity and Access Management From the official documentation: “For example, a remote backend deployed on Cloud Run can use Identity and Access Management (IAM) to:”
• 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.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• service account is part of Identity and Access Management From the official documentation: “Service accounts function as both principals and resources within IAM.”
• 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 works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• Cloud Storage works with service account From the official documentation: “The service account can manage objects in the Cloud Storage bucket.”
• Compute Engine works with Google Cloud Storage From the official documentation: “The usage export bucket is a Google Cloud Storage bucket where Compute Engine usage reports are stored.”
• 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 Compute Engine From the official documentation: “When Dataflow runs a pipeline, the processing is distributed across multiple Compute Engine virtual machines (VMs), also known as workers.”
• Dataflow works with Google Cloud Storage From the official documentation: “When you run a pipeline using Dataflow, your results are stored in a Cloud Storage bucket.”
• Identity and Access Management secures Compute Engine From the official documentation: “Compute Engine uses Identity and Access Management (IAM) for authorization.”
• 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 Compute Engine From the official documentation: “To further protect your Compute Engine resources, you can protect them using [VPC Service Controls](/vpc-service-controls/docs/overview).”
• 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 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 Compute Engine From the official documentation: “Compute Engine integrates with Google Cloud technologies such as Cloud Storage, Google Kubernetes Engine, and BigQuery, to extend beyond the basic computational capability to create more complex and sophisticated applications.”
• 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.”
• 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 Compute Engine From the official documentation: “This lets Cloud Run clients use this backend service route to send requests directly to Compute Engine instances.”
• Cloud Run works with service account From the official documentation: “Map a custom Service Account to a Cloud Run service”
• Cloud SQL depends on Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”
• Cloud SQL depends on Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
• Cloud SQL works with Dataflow From the official documentation: “Use Datastream to replicate changes from your MySQL instance to either BigQuery or Cloud Storage, and then use Dataflow or Managed Service for Apache Spark to bring the data into your Cloud SQL instance.”
• Cloud SQL works with Identity and Access Management From the official documentation: “This page describes how Cloud SQL is integrated with IAM .”
• Cloud SQL works with VPC Service Controls From the official documentation: “Make sure that you configure VPC Service Controls so that the project that hosts the CA Service CA pool and CA<br>and the project that hosts Cloud SQL belong to the same service perimeter.”
• 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).”
• Compute Engine works with Gemini Enterprise Agent Platform From the official documentation: “Google Compute Engine provides a runtime environment for all features provided by Managed Service for Apache Spark and Gemini Enterprise Agent Platform.”
• Compute Engine depends on service account From the official documentation: “The Service Account is used by Compute Engine to access other Google APIs.”
• 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 depends on Identity and Access Management From the official documentation: “Dataflow uses Identity and Access Management (IAM) for authorization.”
• Dataflow works with service account From the official documentation: “If you use query engines such as Managed Service for Apache Spark or Dataflow to read table data, grant this role to the service account that you use to run jobs in that engine.”
• 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 depends on Identity and Access Management From the official documentation: “Agent Platform uses IAM to manage access to resources.”
• Gemini Enterprise Agent Platform works with Identity and Access Management From the official documentation: “Learn more about [Gemini Enterprise Agent Platform access control with IAM](/gemini-enterprise-agent-platform/machine-learning/general/access-control).”
• Identity and Access Management secures BigQuery From the official documentation: “Security in BigQuery is intrinsically linked to [Identity and Access Management (IAM)](/iam/docs/overview) in Google Cloud.”