Authenticating Batch Jobs and Services to an AI Governance Proxy with Workload Identity

From static key to verified workload identity

The proxy should then bind the verified identity to policy decisions and audit records. The sequence below shows how a credential moves from the platform to the audit log.

1. IssueThe platform mints a short-lived credential for a specific workload and audience.
2. ValidateThe proxy checks issuer, signature, audience, expiry, and claims.
3. AuthorizeVerified identity maps to model, tool, and rate-limit policy.
4. RecordEach decision is logged with the identity that produced it.

Why static keys fail at the proxy

A shared API key is a long-lived secret that does not describe which workload is calling. Short-lived credentials issued by the platform each workload runs on replace it, so the proxy receives an identity that can be verified on every request.

What the proxy validates on every request

• Issuer
• Signature
• Audience
• Expiry
• Workload claims

Mechanisms compared

Two approaches cover most environments. The right choice depends on where the callers run and how many platforms need a common identity model.

Mapping identity to policy

Once the proxy has verified a caller, the identity becomes the key for authorization. Verified identity maps to model, tool, and rate-limit policy, and each decision is logged with the identity that produced it.

Audit evidence to record for each request

• Verified subject and issuer, plus the credential type used
• Audience presented and the token expiry time
• Workload registration or policy version that matched
• Requested model or tool, and the allow, deny, or approval outcome
• Rate-limit state and the reason for any rejection
• Request timestamp and a correlation ID that links to downstream calls