AI App Infrastructure

Deploy a minimal HTTP AI application endpoint with cloud-native compute, logs, secret/config wiring, and least-privilege model invocation permissions.

Step 1 of 1

Choose cloud

Choose an option to continue.

Frequently asked questions

Does this deploy model training or data pipelines?
No. The blueprint only deploys runtime infrastructure for invoking a managed foundation model from an HTTP endpoint.
Where do model identifiers and endpoints come from?
Each starter reads provider-specific Pulumi config. Defaults are safe examples where the provider has a public publisher model; account-specific endpoints stay in config or managed secrets.
Does the Azure variant create an Azure OpenAI account?
No. Azure OpenAI access, quota, and deployments are account-specific, so the starter stores references to an existing endpoint and deployment name in Key Vault and injects them into Azure Functions.
How are logs collected?
The runtime uses native platform logging. Lambda writes to CloudWatch Logs, Azure Functions writes through Application Insights, and Cloud Run writes to Cloud Logging.
How do I clean it up?
Run pulumi destroy from the same stack. Provider-managed log retention or externally supplied model deployments may need separate retention review.