To control what a Gemini agent can access in Google Cloud, first choose its runtime identity, then grant that identity only the roles it needs on the specific resources its code uses. Vertex AI Agent Engine documentation describes two patterns: Agent Identity, which uses a distinct agent principal and is marked Preview in the cited setup guide, and service accounts, including a Google-managed default or a custom account. Also manage the agent’s access to backend resources separately from the permissions clients need to call the deployed agent.
Choose the identity the agent will use
The identity attached to the runtime determines which principal Google Cloud evaluates when the agent calls a service or accesses data. The Agent Engine setup guide describes Agent Identity and service accounts as the available patterns in that guidance. Its launch-stage label matters: the guide marks Agent Identity as Preview, so confirm its current status and runtime support before relying on it in a production design. Google’s Agent Engine environment setup guide and Agent Identity overview describe these options.
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Agent Identity: a principal for the agent
With Agent Identity, the agent acts using its primary SPIFFE identity to request Google Cloud access tokens. Administrators grant that identity the roles it needs on the target resources. This gives the agent a distinct principal for resource-level access decisions rather than inheriting permissions from a service account shared with other workloads. See Google’s guidance on an agent’s own authority.
Service account: the account’s permissions apply
An agent running as a service account can access resources that account can access. Agent Engine documentation describes a Google-managed Reasoning Engine Service Agent as the default option and also allows a custom service account. A custom account can make grants more narrowly tailored than using a broadly privileged shared account, but it still needs the roles required by the agent’s code. Review the account’s allow policy and role bindings using Google’s service-account access documentation.
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Decide which pattern fits your deployment
| Consideration | Agent Identity | Service account |
|---|---|---|
| Principal used for backend access | The agent’s primary SPIFFE identity | The selected service account |
| How access is granted | Grant roles to the agent identity on target resources | Grant roles to the service account on target resources |
| Isolation approach | A distinct agent principal | Depends on whether the account is dedicated or shared |
| Setup consideration | Marked Preview in the cited Agent Engine setup guide | Uses the Google-managed default service agent or a custom account |
| Deployment permission noted in the setup guide | Not specified for this identity pattern | A person deploying with a custom service account needs Service Account User on that account |
There is no universal winner: weigh principal isolation, the resources and runtimes your deployment supports, the way your organization manages grants, and the launch-stage constraints. The setup guide’s deployment permission is separate from runtime access: Service Account User lets the deploying person use the custom account, while the account’s own roles govern the agent’s access to resources. The setup guide covers that distinction.
Grant access to the resources the agent actually uses
- Inventory the agent’s calls. Identify the Google Cloud APIs, buckets, and other resources its code needs to reach, and the operations it performs against each.
- Identify the runtime principal. Determine whether those requests will use the agent’s primary SPIFFE identity or a service account.
- Grant roles on the relevant targets. Bind the necessary roles to that principal on the specific resources, rather than assuming that a role granted elsewhere will provide the intended access. The required roles depend on the APIs and data sources involved.
- Check deployment and runtime permissions separately. If using a custom service account, ensure the deploying person has Service Account User on it; then grant the account the runtime roles required by the agent.
- Revisit grants when the agent changes. If its code begins calling a new API or accessing a new data source, assess and add only the permissions needed for that target and operation.
Google’s own-identity instructions include role recommendations for their documented setup scenario; those recommendations should not be treated as a universal permission bundle for every Gemini agent. Use the target service’s requirements and the agent’s actual operations to determine grants. See the own-authority guide and service-account access guidance.
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Keep backend access separate from client access
There are two different access paths to govern. First, the agent’s runtime identity controls its calls to backend services and data. Second, a user or application needs an allowed way to invoke the deployed agent. Granting the agent permission to read a bucket does not, by itself, define which clients may call the agent; conversely, client authentication does not grant the agent access to that bucket.
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Fit IAM and organization-level controls into the design
Google describes Agent Identity as integrated with IAM, Principal Access Boundary, and VPC Service Controls. These controls can be part of an organization’s governance design, but they do not replace deciding which principal should access which resource and which roles are appropriate. Evaluate them against your architecture, data classification, and existing policies. See the Agent Identity overview.
Google’s Agent Registry concepts documentation shows agent principal and principal-set formats, which can help administrators understand how agent identities are represented when applying policy. Review the Agent Registry concepts when working with those identifiers.
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