Academic

Mind the Boundary: Stabilizing Gemini Enterprise A2A via a Cloud Run Hub Across Projects and Accounts

arXiv:2602.17675v1 Announce Type: cross Abstract: Enterprise conversational UIs increasingly need to orchestrate heterogeneous backend agents and tools across project and account boundaries in a secure and reproducible way. Starting from Gemini Enterprise Agent-to-Agent (A2A) invocation, we implement an A2A Hub orchestrator on Cloud Run that routes queries to four paths: a public A2A agent deployed in a different project, an IAM-protected Cloud Run A2A agent in a different account, a retrieval-augmented generation path combining Discovery Engine and Vertex AI Search with direct retrieval of source text from Google Cloud Storage, and a general question answering path via Vertex AI. We show that practical interoperability is governed not only by protocol compliance but also by Gemini Enterprise UI constraints and boundary-dependent authentication. Real UI requests arrive as text-only inputs and include empty accepted output mode lists, so mixing structured data into JSON-RPC responses c

T
Takao Morita
· · 1 min read · 18 views

arXiv:2602.17675v1 Announce Type: cross Abstract: Enterprise conversational UIs increasingly need to orchestrate heterogeneous backend agents and tools across project and account boundaries in a secure and reproducible way. Starting from Gemini Enterprise Agent-to-Agent (A2A) invocation, we implement an A2A Hub orchestrator on Cloud Run that routes queries to four paths: a public A2A agent deployed in a different project, an IAM-protected Cloud Run A2A agent in a different account, a retrieval-augmented generation path combining Discovery Engine and Vertex AI Search with direct retrieval of source text from Google Cloud Storage, and a general question answering path via Vertex AI. We show that practical interoperability is governed not only by protocol compliance but also by Gemini Enterprise UI constraints and boundary-dependent authentication. Real UI requests arrive as text-only inputs and include empty accepted output mode lists, so mixing structured data into JSON-RPC responses can trigger UI errors. To address this, we enforce a text-only compatibility mode on the JSON-RPC endpoint while separating structured outputs and debugging signals into a REST tool API. On a four-query benchmark spanning expense policy, project management assistance, general knowledge, and incident response deadline extraction, we confirm deterministic routing and stable UI responses. For the retrieval path, granting storage object read permissions enables evidence-backed extraction of the fifteen minute deadline. All experiments are reproducible using the repository snapshot tagged a2a-hub-gemini-ui-stable-paper.

Executive Summary

The article presents a novel approach to stabilizing Gemini Enterprise A2A via a Cloud Run Hub, enabling secure and reproducible orchestration of heterogeneous backend agents and tools across project and account boundaries. The authors implement an A2A Hub orchestrator on Cloud Run, routing queries to various paths, including public and IAM-protected agents, retrieval-augmented generation, and general question answering. The results demonstrate deterministic routing and stable UI responses, with the ability to extract evidence-backed information. The approach addresses key challenges in enterprise conversational UIs, including protocol compliance, boundary-dependent authentication, and UI constraints.

Key Points

  • Implementation of A2A Hub orchestrator on Cloud Run
  • Routing queries to multiple paths
  • Addressing UI constraints and boundary-dependent authentication

Merits

Scalability and Flexibility

The proposed approach allows for easy integration of new agents and tools, enabling scalability and flexibility in enterprise conversational UIs

Demerits

Complexity and Overhead

The implementation of the A2A Hub orchestrator and the various routing paths may introduce additional complexity and overhead, potentially impacting performance

Expert Commentary

The article presents a significant contribution to the field of conversational AI and UI, particularly in enterprise settings. The authors' approach to stabilizing Gemini Enterprise A2A via a Cloud Run Hub addresses key challenges in the field, including protocol compliance, boundary-dependent authentication, and UI constraints. The results demonstrate the effectiveness of the approach in enabling deterministic routing and stable UI responses. However, further research is needed to fully explore the potential implications and applications of this approach, particularly in terms of scalability, flexibility, and performance.

Recommendations

  • Further research is needed to explore the scalability and flexibility of the proposed approach
  • The development of more sophisticated UI constraints and boundary-dependent authentication mechanisms is recommended to further improve the stability and security of enterprise conversational UIs

Sources