Google Cloud's Gemini Enterprise offers custom agents with organizational context and governance features. However, a key detail for enterprise AI engineers is that agents registered via the A2A (agent-to-anywhere) path bypass the standard Agent Gateway policies. This means security controls like Model Armor must be configured directly within the agent application itself, rather than relying solely on the Gemini Enterprise console settings. A practical approach involves mapping the entire request path and testing specific controls to ensure actual traffic is protected, rather than assuming coverage based on configuration. AI
IMPACT Highlights a critical security configuration detail for Gemini Enterprise agents, impacting how organizations implement governance for custom AI integrations.
RANK_REASON Article provides a practical guide for configuring security for a specific product feature (Gemini Enterprise A2A agents), rather than announcing a new product or major research.
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