Compute Engine reservations

Related topics

• Compute Engine reservations is part of Compute Engine From the official documentation: “Reservations are a Compute Engine feature.”
• Agent Platform works with Compute Engine reservations From the official documentation: “You can only use Compute Engine reservations that are shared with Agent Platform.”
• Colab Enterprise works with Compute Engine reservations From the official documentation: “Use [Compute Engine reservations](/compute/docs/instances/reservations-overview) to gain a high level of assurance that your Colab Enterprise runtimes have enough virtual machine (VM) resources to run.”
• Compute Engine reservations works with Dataflow From the official documentation: “To ensure that VM resources are available when your Dataflow jobs need them, you can use Compute Engine reservations.”
• Compute Engine reservations works with Google Kubernetes Engine From the official documentation: “Compute Engine capacity reservations let you provision specific hardware configurations in Google Cloud zones, either immediately or at a specified future time. You can then consume this reserved capacity in GKE.”
• Compute Engine reservations works with Model Garden From the official documentation: “You can deploy Model Garden models on VM resources that have been allocated through Compute Engine reservations.”
• 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.”
• 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.”
• 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).”
• 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 Colab Enterprise From the official documentation: “You can use Colab Enterprise from within the Google Cloud console, with features built into both Agent Platform and BigQuery.”
• Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Colab Enterprise depends on Compute Engine From the official documentation: “Colab Enterprise uses Compute Engine quota for GPUs.”
• 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 Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
• Cloud Storage works with Compute Engine From the official documentation: “You can use a web browser, the Google Cloud CLI, or a programming language to transfer files between Cloud Storage and Compute Engine VMs.”
• Compute Engine is an alternative to Google Kubernetes Engine From the official documentation: “You can install MongoDB on a Compute Engine instance or you can deploy MongoDB on Google Kubernetes Engine.”
• Agent Platform works with Cloud Storage From the official documentation: “Load the model's `state_dict` object into Cloud Storage by using a Agent Platform custom job:”
• 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 works with Google Kubernetes Engine From the official documentation: “As an example, if you are using GKE, you can [use Cloud Logging to query](/logging/docs/view/building-queries) for GKE cluster audit logs.”
• Cloud Storage works with Colab Enterprise From the official documentation: “Colab Enterprise stores the results in Cloud Storage for you to review and share with others.”
• 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 Colab Enterprise From the official documentation: “This guide describes how to use CMEK for Colab Enterprise.”
• Customer-managed encryption keys secures Compute Engine 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 Google Kubernetes Engine From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
• 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 you run your pipeline on the Dataflow service, Dataflow creates Compute Engine instances to run your pipeline code.”
• Google Kubernetes Engine depends on BigQuery From the official documentation: “This happens because Google Kubernetes Engine depends on BigQuery and Managed Service for Apache Airflow inherits this dependency from the Kubernetes Engine API.”
• Google Kubernetes Engine depends on Compute Engine From the official documentation: “Other products, such as [Google Kubernetes Engine](/kubernetes-engine) and [Dataflow](/dataflow), use Compute Engine resources and therefore, can be deployed in the same regions or zone.”
• 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 Colab Enterprise From the official documentation: “This page describes how to use VPC Service Controls to set up a Colab Enterprise notebook within a service perimeter.”
• 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).”
• Agent Platform works with BigQuery From the official documentation: “BigQuery and Agent Platform are tightly integrated, letting you access and analyze your data directly within the Agent Platform platform.”
• Agent Platform works with Cloud Logging From the official documentation: “If any containers restart before Agent Platform shuts down the entire job, these containers may produce logs in Cloud Logging.”
• Agent Platform works with VPC Service Controls From the official documentation: “If you use Agent Platform in a VPC-SC environment, you must create an ingress rule in your perimeter to allow ingress from the Reasoning Engine Service Agent (`service-PROJECT_NUMBER@gcp-sa-aiplatform-re.iam.gserviceaccount.com`) into the `storage.googleapis.com` service and…”
• 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 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 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 VPC Service Controls From the official documentation: “This page describes how you can find VPC Service Controls errors using Cloud Logging.”
• Cloud Storage works with Model Garden From the official documentation: “Model Garden lets you deploy [supported models](/gemini-enterprise-agent-platform/models/model-garden/self-deployed-models#supported_models) with custom weights from a Cloud Storage bucket.”
• Compute Engine works with Google Kubernetes 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.”
• Customer-managed encryption keys is part of Agent Platform From the official documentation: “See Agent Engine [Customer-managed encryption keys (CMEK)](/gemini-enterprise-agent-platform/scale/runtime/manage-agent-access#cmek) for more details.”
• 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.”
• Dataflow depends on Identity and Access Management From the official documentation: “Dataflow uses Identity and Access Management (IAM) for authorization.”