Why this matters
How to reach AI model APIs over private links is a routing and identity problem before it is a model problem. Your SDK still calls a hostname and sends a key. The private link changes the path between your subnet and the provider endpoint: your workload connects to a private IP in your cloud region, not a public address. That keeps prompt data off the public internet. It does not remove TLS, auth or rate limits.
AI API traffic exposes weak setups. Responses stream token by token, so a proxy that buffers hurts time to first token. Batch jobs and chat calls should not share a small proxy pool. Prompts and outputs often hold customer data, and a private endpoint is easier to defend in a security review than a public egress rule with an IP allowlist.
Operations change too. You now care about endpoint subnet capacity, private DNS, route tables and provider approval. A missing DNS rule can send traffic back to the public API, and the app still works, so nobody notices. Treat this as an application change with a network dependency. Confirm support, create the endpoint, fix DNS, pin the SDK, test, then roll out.
Before you start
List every model API you call and how you call it. Include the SDK, base URL, region, auth method, streaming mode, batch endpoints, file uploads and webhooks. A private endpoint for chat completions may not cover embeddings or fine tuning, because providers split services across hostnames. Check the docs for the endpoint service name, supported regions and any access request. If the provider has no private option in your region, pick another region or another path.
Choose where the endpoint lives. A private endpoint in each workload VPC is simple, but it spreads endpoint interfaces and DNS records across accounts. A shared services VPC centralizes the endpoint and lets workloads connect through peering or a transit gateway. That concentrates control and cost, but it creates a shared failure domain. For the first rollout, use the same VPC or account as the first workload.
Reserve subnets for endpoint interfaces. They consume IP addresses and have limits per subnet and per endpoint. Check DNS resolver rules for the VPC. If you use a private hosted zone, decide whether it overrides the public hostname for all VPCs or only selected accounts. Private link gives reachability, not caller identity. Keep keys in a secret store and allow only the endpoint IPs on port 443 from the workload.
How to do it
Work in staging with one model and one hostname. Keep the public path for rollback until the private path passes the checks in the next section. Order matters: change DNS before the endpoint accepts connections and you get an outage. Change the SDK before DNS and it fails to resolve. Create the endpoint, approve it, publish DNS, then move the app.
Use the provider's private endpoint service when one exists. On AWS that means an interface VPC endpoint for a VPC endpoint service. On Azure it means a private endpoint to a private link service. On Google Cloud it means Private Service Connect. The names differ, but the shape is the same: an endpoint in your subnet, provider approval or an endpoint policy, a private DNS name, and a firewall rule. Keep the public hostname in code and use a DNS override if the provider supports it. Do not hard-code IPs. Certificates are issued for names.
- Confirm provider support and region. Find the endpoint service name, supported regions and any access request in the provider docs. Confirm that embeddings, file endpoints and chat calls all work through the private endpoint. Ask support about region pairing if the docs are vague.
- Create the endpoint in the workload VPC. Create an interface VPC endpoint, private endpoint or Private Service Connect attachment in the reserved subnets. Use one subnet per availability zone. Attach a security group that allows port 443 from the app tier only.
- Approve the connection and set a policy. Accept the provider side request if the service requires it. Add an endpoint policy that limits the provider service and accounts allowed. Record the endpoint ID in the runbook.
- Publish private DNS for the API hostname. Create a private hosted zone for the exact API hostname with an alias or CNAME to the endpoint DNS name. Associate it only with VPCs that should use the private path. Test from a host in the subnet first.
- Pin the SDK to the private name. Set the SDK base URL to the private hostname, or use the DNS override if the provider supports it. Keep TLS verification on and use the exact name in the certificate. Remove fallback code that calls the public API on error.
- Tighten egress at the workload. Update security groups, network ACLs and firewall rules to allow only the endpoint addresses on port 443. If you use a shared proxy, allow the proxy to the endpoint, not the whole VPC. Check sidecars and health checks for public DNS use.
- Test and canary one service. Set timeouts and retries before you move traffic. Send small, long and streaming requests through the private path. Move one low-risk service or a small slice of traffic and compare errors, time to first token and latency. Keep a policy-based rollback ready.
How to check it worked
Run checks from a workload host, not your laptop. Use dig or nslookup for the API hostname and confirm the answer is the private endpoint address, not a public IP. Then run openssl s_client with the same hostname and port 443. Check that the certificate matches the hostname. A call that works by IP but fails by name points to DNS or SNI.
Use VPC flow logs, endpoint metrics or provider logs to confirm traffic reaches the endpoint. On AWS, check the endpoint network interface and accepted connections. On Azure, check the private endpoint state and private DNS zone. On Google Cloud, check the Private Service Connect attachment. Check that no NAT or internet gateway egress to the public API host remains for that workload.
Test the app. Send a streaming request and watch time to first token. Send a long prompt and watch for timeouts. Force a 429 or a 5xx with a test key and confirm the client backs off. Check logs for the private hostname and for accidental public hostnames. If you use a proxy, check its logs for buffering and the original host header.
Mistakes to avoid
The first mistake is treating private link as encryption and authentication. It only changes the path. Keep TLS verification, rotate keys and scope tokens to the workload. A private endpoint with a shared admin key is still a wide-open door.
The second is silent fallback. The SDK resolves the public name, the private zone is missing from the test VPC, and traffic goes out the NAT gateway. It works, so nobody checks. Add a firewall deny for the public API host where you can, and monitor DNS answers.
The third is choosing an endpoint in another region because it was easier to create. That adds latency to every token and may break data residency rules. The fourth is ignoring IP and connection limits. Endpoint interfaces consume subnet IPs, and proxies have pools. Size them before a batch job opens many connections. Do not hard-code IPs or turn off certificate checks. Test webhooks, file uploads and batch endpoints, not one chat call. If you want a second opinion, the Expert architecture session from Cloudverg at $450 one-time is one option among others.
Frequently asked questions
Does a private link encrypt AI API traffic?
No. A private link changes the network path and keeps traffic off the public internet. You still need TLS between the client and the API endpoint. You also still need API authentication and authorization at the application layer.
Can I use a private link with any AI model provider?
No. The provider must offer a private endpoint service, private link or private interconnect in your region. Check the provider docs for the exact endpoint service name and any access request. If the provider has no private option, use a private interconnect to a cloud region that does, or keep the public path with strong egress controls.
Do I still need a VPN or dedicated connection?
Only if the client is outside the cloud that hosts the private endpoint. A workload in the same cloud region can use the endpoint directly. On-premises clients need a private path into that cloud first, such as a VPN or dedicated circuit, and then the endpoint.