Model Decommissioning Record

Captures the specific business, technical, or regulatory reason for retirement. This is a mandatory, structured field—not free-text—to enable automated compliance reporting.

• Performance Degradation: Model drift exceeded a predefined threshold (e.g., F1 score dropped below 0.85).
• Regulatory Mandate: A conformity assessment failed under the EU AI Act, requiring immediate withdrawal.
• Business Obsolescence: The underlying product or decision process was discontinued.
• Security Vulnerability: A critical adversarial robustness flaw was discovered, necessitating emergency decommissioning.

The exact moment of decommissioning is bound to the record using a Trusted Timestamp Authority (TSA) per RFC 3161. This proves the model was not used after a specific cut-off date.

• The record hash is submitted to a TSA, which returns a signed timestamp token.
• This provides cryptographic non-repudiation, preventing any party from backdating or denying the retirement event.
• Often combined with Merkle Tree Hashing to anchor the record in a public blockchain for universal verifiability.

A complete, deterministic artifact bundle that allows for exact reconstruction of the model's final state. This is not just a backup; it's a forensic artifact.

• Model Weights & Architecture: The final serialized parameters and graph definition.
• Environment Fingerprint: A hash of all software dependencies, container images, and hardware drivers.
• Deterministic Serialization: All artifacts are packaged using a canonical format (e.g., Canonical JSON) to ensure a bit-for-bit identical replay is possible years later.
• Content-Addressable Storage: The snapshot is stored and retrieved by its SHA-256 hash, guaranteeing integrity.

The decommissioning record is the final link in the model's Data Lineage Graph. It formally transfers custody of the model artifact from the production environment to a secure, immutable archive.

• Logs the identity of the authorizing party (human or system) who executed the decommissioning.
• Records the Human-in-the-Loop Override if a manual intervention triggered the retirement.
• Updates the Model Card Logging system to mark the version as 'decommissioned', preventing accidental redeployment.

Once written, the decommissioning record must be physically impossible to alter or delete. This is achieved through Write-Once-Read-Many (WORM) storage technologies.

• Software WORM: Policy-based immutability locks in cloud object storage (e.g., S3 Object Lock in Compliance mode).
• Hardware WORM: Data written to specialized non-erasable media.
• Distributed Ledger Technology (DLT): The record's hash is anchored in a tamper-proof distributed ledger, providing a decentralized proof of existence that survives any single infrastructure failure.

The decommissioning process is triggered and validated automatically by Policy-as-Code rules, not manual checklists. This ensures consistent, auditable execution.

• A rule engine (e.g., Open Policy Agent) verifies that all preconditions are met before allowing the retirement command.
• Idempotent Logging ensures the decommissioning event is recorded exactly once, even if the command is retried.
• The enforcement decision itself is logged, creating a GitOps Audit Trail that links the decommissioning action back to a specific policy commit.