Deploying a Google ADK Agent to Vertex AI Agent Engine with Terraform

Most documentation for Vertex AI Agent Engine focuses on the Python SDK ( vertexai.agent_engines.create ). That works fine for one-off deployments, but if you want your agent infrastructure managed declaratively alongside the rest of your GCP resources, Terraform is the right tool. This post walks through a complete Terraform setup for deploying a Google ADK agent to Vertex AI Agent Engine using google_vertex_ai_reasoning_engine . Prerequisites Terraform >= 1.5 google or google-beta provider aiplatform.googleapis.com enabled A Google ADK agent wrapped in AdkApp How Agent Engine Deployment Works The deployment model is straightforward: tar.gz your source code, base64-encode it, and pass it to the API via inline_source . The runtime handles dependency installation, session management, and streaming — you just provide the entrypoint. The Agent Entrypoint The key requirement is an AdkApp instance at the module level. This is what Terraform's entrypoint_object points to. # src/myagent/agent