back_office_ops · workflow
Deploying Secure, Scalable AI Agents with ADK and Google Cloud in the Enterprise
Moving AI agents from proof-of-concept to enterprise production requires navigating complex networking, authentication, identity propagation, and security requirements that are absent in local demos.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Client sends request
Clients, either end-users via a browser or services and other agents via API calls, interact with the agent logic.
Tools used
ADKgemini-2.5-flashVertex AICloud RunIAPVertex AI Agent EngineGoogle AgentSpaceIAMgoogle_searchOIDCJWThttpx
Outcome
Cloud Run with IAP emerged as the best current trade-off for secure, flexible enterprise agent deployment, supporting Web UI, API, and A2A endpoints from a single instance.
Grounding & classification
Source type: technical build writeup
22 fields verified against source quotes, 3 dropped as unverifiable.
agentic workflowai agentmulti agent workflowknowledge basebuilder submittedsource backedworkflow describedsoftwaretechnical build writeupback office opsagentic task execution