Shared VPC

Related topics

• service project is part of Shared VPC From the official documentation: “When you use Shared VPC, you designate a project as a *Shared VPC host project* and attach one or more *service projects* to it.”
• Shared VPC is an alternative to VPC Network Peering From the official documentation: “We recommend using Shared VPC over using VPC Network Peering because Shared VPC is easier to configure and scale.”
• Shared VPC works with VPC Service Controls From the official documentation: “If you use both Shared VPC and VPC Service Controls, the host project that contains the network and the service project that contains the Managed Lustre instance must both be inside the same perimeter.”
• host project is part of Shared VPC From the official documentation: “When you use Shared VPC, you designate a project as a *Shared VPC host project* and attach one or more *service projects* to it.”
• Cloud Service Mesh works with Shared VPC From the official documentation: “For a detailed explanation of how Shared VPC is supported with Cloud Service Mesh, see [Limitations](/service-mesh/v1.25/docs/service-routing/limitations).”
• Cloud Run works with Shared VPC From the official documentation: “To see which Cloud Run resources are using the Shared VPC network, run the following command:”
• Cloud Workstations works with Shared VPC From the official documentation: “To enable Cloud Workstations to use your Shared VPC network and subnetwork, grant the Cloud Workstations Service Agent for your project the [Compute Engine Network User role](/compute/docs/access/iam#compute.networkUser) (`roles/compute.networkUser`) on the Shared VPC subnet.”
• Dataflow works with Shared VPC From the official documentation: “The following error occurs when you run a Dataflow job on a Shared VPC network:”
• Shared VPC depends on host project From the official documentation: “Each Shared VPC network is defined and owned by a centralized *host project*, and can be used by one or more *service projects*.”
• Shared VPC works with VPC Network Peering From the official documentation: “You can use Shared VPC with clusters based on VPC Network Peering.”
• App Engine works with Shared VPC From the official documentation: “For requests from a Shared VPC, traffic is only considered internal if the App Engine app is deployed in the Shared VPC host project.”
• GKE works with Shared VPC From the official documentation: “For networking, GKE clusters are deployed in a Shared VPC that's created as part of the enterprise foundation blueprint.”
• Private Service Connect works with Shared VPC From the official documentation: “Private Service Connect resources can be deployed in standalone VPC networks or Shared VPC networks.”
• Shared VPC is part of host project From the official documentation: “The Shared VPC host project is the project which contains the Shared VPC network.”
• Shared VPC depends on service project From the official documentation: “Shared VPC requires that you designate a *host project* to which networks and subnetworks belong and a *service project*, which is attached to the host project.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• 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”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• Identity and Access Management secures Cloud Service Mesh From the official documentation: “Access to Cloud Service Mesh in the Google Cloud console is controlled by [Identity and Access Management (IAM)](/iam/docs/overview).”
• Cloud Logging works with GKE From the official documentation: “Enable Cloud Logging on GKE Clusters”
• Compute Engine is an alternative to GKE From the official documentation: “To use TPU7x, you can use Google Kubernetes Engine (GKE) or Compute Engine.”
• Cloud Logging works with Cloud Service Mesh From the official documentation: “Cloud Service Mesh stores the dry-run results to Cloud Logging in the following labels:”
• Cloud Monitoring works with Cloud Service Mesh From the official documentation: “Mesh telemetry is no longer automatically ingested into Cloud Monitoring.”
• Cloud Monitoring works with GKE From the official documentation: “Enable Cloud Monitoring on GKE Clusters”
• Cloud Run works with Cloud Service Mesh From the official documentation: “This section shows you how to troubleshoot common errors with Cloud Service Mesh and Cloud Run.”
• Cloud Service Mesh works with VPC Service Controls From the official documentation: “You can now use VPC Service Controls with Cloud Service Mesh.”
• Cloud Run is an alternative to GKE From the official documentation: “The app uses Cloud SQL, Vertex AI, and either Google Kubernetes Engine (GKE) or Cloud Run.”
• App Engine is an alternative to Cloud Run From the official documentation: “App Engine and Cloud Run are Google Cloud platforms for hosting apps and services.”
• Cloud Service Mesh works with VPC Network Peering From the official documentation: “Cloud Service Mesh supports [VPC Network Peering](/vpc/docs/vpc-peering) with the [service routing APIs](/service-mesh/docs/service-routing/service-routing-overview).”
• Artifact Registry works with Cloud Run From the official documentation: “Cloud Run recommends using Artifact Registry.”
• Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
• Cloud Service Mesh depends on GKE From the official documentation: “Provision managed Cloud Service Mesh on a GKE cluster.”
• Cloud Service Mesh works with GKE From the official documentation: “# Set up a proxyless gRPC service mesh on GKE”
• Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
• Artifact Registry works with Compute Engine From the official documentation: “Compute Engine can pull containers directly from Artifact Registry repositories.”
• Artifact Registry works with GKE From the official documentation: “In the next tutorial, you deploy those images from the Artifact Registry repository to a GKE cluster:”
• 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 Service Mesh works with Compute Engine From the official documentation: “You can run applications on the following platforms and adopt them into a global service mesh that Cloud Service Mesh configures. | Feature | Supported | | --- | --- | | Compute Engine virtual machine (VM) instances | ✔ |”
• Cloud Service Mesh works with Identity and Access Management From the official documentation: “For information about how and which permissions are evaluated for each method, see the Identity and Access Management documentation for Cloud Service Mesh.”
• Cloud Workstations depends on Private Service Connect From the official documentation: “Your workstations connect to the control plane through Private Service Connect.”
• GKE depends on Compute Engine From the official documentation: “For example, GKE deploys clusters on Compute Engine VMs.”
• Private Service Connect works with VPC Service Controls From the official documentation: “VPC Service Controls that use Private Service Connect”
• VPC Service Controls secures Artifact Registry From the official documentation: “If your VPC Service Controls settings are blocking access to Artifact Registry, you must add the Artifact Registry service to the service perimeter of your VPC Service Controls.”
• App Engine works with Artifact Registry From the official documentation: “Store dependencies for your App Engine applications in Artifact Registry.”
• App Engine works with Cloud Logging From the official documentation: “App Engine automatically sends both the request logs and app logs to the [Cloud Logging](/logging/docs/overview) agent.”
• App Engine works with Cloud Monitoring From the official documentation: “This tutorial shows how to set up an uptime alert for the [Python Hello World app](/python/getting-started/hello-world) running on App Engine flexible environment using [Cloud Monitoring](/monitoring/docs).”
• App Engine works with Compute Engine From the official documentation: “Your App Engine app can communicate with services hosted on Compute Engine within the same project without going through the public internet.”
• Artifact Registry works with Cloud Workstations From the official documentation: “To host custom container images, we recommend and support Artifact Registry. If you use GitHub or any other public or private repository, Cloud Workstations might not work as expected.”
• 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 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 Monitoring works with Cloud Run From the official documentation: “Cloud Monitoring records metrics regarding the execution of Cloud Run.”
• Cloud Monitoring works with Compute Engine From the official documentation: “Many Google services like Compute Engine send telemetry to Cloud Monitoring.”
• Cloud Run works with GKE From the official documentation: “Leverage Google Kubernetes Engine (GKE) and Cloud Run to deploy applications to the Google Cloud, optimizing costs, performance, and management overhead.”
• 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 Service Mesh depends on Cloud Monitoring From the official documentation: “Cloud Service Mesh uses Cloud Monitoring to provide automatic telemetry and logs.”