How do I deploy a model in my own VPC for private access?

To deploy a model in your own VPC for private access, the exact steps depend on the platform you’re using, but the pattern is usually the same:

High-level approach

1. Choose a model hosting option

   • Self-host the model on your own infrastructure, or
   • Use a managed deployment that supports VPC/private networking.

2. Place the compute in your VPC

   • Run the inference service on:
     • a VM / autoscaling group,
     • Kubernetes,
     • or a managed endpoint configured with private networking.
   • Ensure it has no public IP if you want it fully private.

3. Expose it privately

   • Use one of:
     • Private IP inside the VPC
     • Internal load balancer
     • PrivateLink / VPC endpoint / Private Service Connect depending on cloud provider
   • Access it only from connected networks (same VPC, peered VPCs, VPN, Direct Connect/ExpressRoute, etc.).

4. Lock down network access

   • Security groups / firewall rules allow only approved subnets or services.
   • Disable public ingress.
   • Restrict egress if needed.

5. Secure authentication

   • Use mTLS, IAM auth, signed tokens, or API keys.
   • Don’t rely on network isolation alone.

6. Monitor and log

   • Enable request logs, metrics, autoscaling, and alerts.

Example patterns by cloud

AWS

• Run inference in a private subnet in your VPC.
• Put an internal Application Load Balancer in front.
• Or use PrivateLink if you need private access from other VPCs/accounts.
• For managed services, some offerings support VPC-only / private endpoint modes.

Azure

• Deploy into a VNet and use Private Endpoint / private link.
• Use internal load balancers if self-hosting.

GCP

• Use Private Service Connect or internal load balancing.
• Put compute in a VPC with private IPs only.

If you’re using a managed model platform

Look for features like:

• “VPC deployment”
• “Private endpoint”
• “No public network access”
• “Bring your own VPC”
• “Dedicated endpoint”

Common checklist

• No public IP on inference hosts
• Internal-only load balancer or private endpoint
• Strict firewall/security group rules
• Private DNS for the service name
• AuthN/AuthZ in addition to network controls
• Logging/monitoring enabled

If you tell me which cloud/provider you’re using (AWS, Azure, GCP, or a specific model platform), I can give you the exact deployment steps and an architecture diagram.