Private Access to AI Services in Google Cloud with VPNTunnel
PythonIf you're looking to set up private access to AI services in Google Cloud using a VPN tunnel, you'll need a few different resources:
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VpnGateway: This resource represents a VPN Gateway which runs VPN tunnels. It's the endpoint on the Google Cloud side of the VPN connection.
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VpnTunnel: The VPN tunnel resource establishes the connection between your Google Cloud network and another network, such as your on-premises network.
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Router: Routers are involved in dynamic routing for your VPN tunnel and they advertise the appropriate routes between the two networks.
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Servicenetworking Connection: To enable private services access, a private connection between your VPC network and the Google services network is needed.
I will provide you with a complete Pulumi Python program that demonstrates how you can use these resources to achieve private access to AI services in Google Cloud:
import pulumi import pulumi_gcp as gcp # Replace these variables with appropriate values for your setup. project = 'my-gcp-project' region = 'us-central1' network_name = 'my-vpc-network' subnet_name = 'my-subnet' # A VPC network is required for setting up a VPN. vpc_network = gcp.compute.Network( "vpc-network", project=project, name=network_name, auto_create_subnetworks=False, description="Custom VPC Network" ) # Subnet to be used by the VPN Gateway and Tunnels. subnet = gcp.compute.Subnetwork( "subnet", project=project, name=subnet_name, region=region, network=vpc_network.id, ip_cidr_range="10.1.2.0/24" ) # VPN Gateway which will run VPN Tunnels. vpn_gateway = gcp.compute.VPNGateway( "vpn-gateway", project=project, region=region, network=vpc_network.id ) # VPN tunnel for connecting to Google services privately. vpn_tunnel = gcp.compute.VPNTunnel( "vpn-tunnel", project=project, region=region, peer_ip="15.0.0.120", # IP address of the peer VPN gateway. shared_secret="a-strong-shared-secret", vpn_gateway=vpn_gateway.id ) # Router to advertise allowed IPs. router = gcp.compute.Router( "router", project=project, region=region, network=vpc_network.id ) # Configure service networking to use private services. service_networking_connection = gcp.servicenetworking.Connection( "service-networking-connection", network=vpc_network.id, service="servicenetworking.googleapis.com", # Google service to connect to. reserved_peering_ranges=[subnet.ip_cidr_range] ) # Export the VPN Gateway's name so you can reference it easily. pulumi.export("vpn_gateway_name", vpn_gateway.name) # Export the VPN Tunnel's name for easy reference. pulumi.export("vpn_tunnel_name", vpn_tunnel.name) # Export the router's name for troubleshooting purposes. pulumi.export("router_name", router.name) # Export the service networking connection's name for reference. pulumi.export("service_networking_connection_name", service_networking_connection.name)
Each resource in this script represents a piece of the overall setup:
- The
vpc-network
defines your private cloud network. - The
subnet
represents a segment of IP addresses where your resources, such as the VPN gateway, will live. - The
vpn-gateway
is the endpoint for the VPN connection within Google Cloud. - The
vpn-tunnel
is responsible for establishing the secure connection over which your private Google Cloud services can be accessed. - The
router
handles dynamic routing for the VPN tunnel. - The
service-networking-connection
creates a private connection to Google services.
This code is a starting point. You’ll need to replace the
peer_ip
and other placeholders with valid values that match your on-premises or peer network settings. Thereserved_peering_ranges
should be a list of the ranges that you would like to connect privately to the services.Make sure you have the necessary permissions and VPN setup, including the correct peer IP on the non-Google side of the connection. Once this code is executed using the Pulumi CLI, it will create all the necessary resources to establish a private connection to Google Cloud AI services through a VPN tunnel.
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