Teams know by observing gateway traffic, not by relying on repository search alone. Runtime telemetry can show volume, owning team, and workload context for each model call, which lets operators separate a forgotten low-volume dependency from a business-critical path that needs a coordinated migration plan.
Runtime telemetry, not source code archaeology
Teams usually learn a retiring model is still in use by watching the traffic that actually reaches it. Gateway logs and runtime telemetry reveal whether calls are still arriving, how often they occur, and which workloads or teams are generating them. That is more reliable than repository search alone, because stale references in code do not prove live dependency.
A practical inventory needs to distinguish an abandoned reference from an active path. If a model is still receiving requests, the question is no longer “does anything mention it?” but “who depends on it, and what business function breaks if it disappears?”
What telemetry should tell you before you retire the model
The useful signals are volume, caller identity, and execution context. Volume shows whether usage is sporadic or sustained, caller identity shows which service or team owns the dependency, and context shows whether the model sits on a critical request path, a batch workflow, or an edge case that can be migrated later. Those three signals together support a defensible retirement decision.
Telemetry is also what lets teams separate real use from accidental noise. A model that sees one request a month may still matter if it backs a compliance workflow or a human escalation path, while a model with high volume but low business criticality may be easier to replace. The operational question is therefore not just “is it used?” but “how material is the use?”
- Confirm the request source, not just the endpoint name.
- Map each caller to an owning team or product.
- Check whether the traffic is synchronous user-facing demand or background processing.
- Look for dependency chains that would fail if the model stopped responding.
Migration decisions should follow observed dependency, not assumptions
Once runtime data shows the model is still active, teams can decide whether to migrate, shim, or decommission. The right choice depends on whether the traffic is a business-critical path, a low-volume fallback, or a forgotten integration that can be redirected with minimal risk. That makes telemetry a planning tool, not just a discovery tool.
In practice, the strongest retirement plans include a cutoff date, a named owner for each observed caller, and a rollback path if hidden usage appears late in the process. Without that discipline, model retirement often turns into an outage caused by incomplete visibility rather than a deliberate shutdown.
Risk and Threat Considerations
Retiring a model based only on code search creates blind spots. Hidden runtime dependencies, especially across gateways, scheduled jobs, and shared services, can keep a supposedly retired model alive long after the owning team thinks it is safe to remove.
Failure mechanism: Repository references go stale, but live traffic continues through indirect paths that were never captured in source control, so the retirement decision is made on incomplete evidence.
Impact: Teams can break production workflows, miss a critical dependency, or leave an old model exposed longer than intended because nobody had the full usage picture.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
OWASP API Security Top 10 addresses the attack and risk surface, while NIST SP 800-53 Rev 5 and NIST CSF 2.0 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| OWASP API Security Top 10 | API9 — Improper Inventory Management | Live model endpoints need accurate inventory and dependency visibility. |
| Recommendation — Inventory runtime callers and retire only after observed traffic drops to zero. | ||
| NIST SP 800-53 Rev 5 | AU-2 — Event Logging | Telemetry is the evidence source for determining whether the model is still used. |
| Recommendation — Log model gateway events with caller and context details to prove remaining use. | ||
| NIST CSF 2.0 | DE.CM-01 — Networks and network services are monitored to find potential cybersecurity events | Gateway monitoring is how teams detect continued model consumption before decommissioning. |
| Recommendation — Monitor model gateways continuously and alert on unexpected post-retirement traffic. | ||
Practitioner Guidance
What to prioritize: Start with gateway and application telemetry for the exact model endpoint, then trace each caller back to an accountable team. That gives you an evidence-based retirement queue instead of a generic cleanup list.
What to verify: Verify whether the observed calls are truly production traffic, whether they recur over time, and whether any caller still depends on the model for a customer-facing or regulated workflow. A single low-volume caller can be more important than a noisy noncritical one.
Decision rule: If runtime telemetry shows any live caller, treat the model as active until the owner signs off on migration or removal. If telemetry is absent, do not declare victory until you have confirmed the relevant gateways, proxies, and background jobs were actually instrumented.
Practitioner takeaway: Retirement is a dependency-management exercise, not a codebase search exercise, and the safest cutoff is the one backed by observed traffic and a named migration owner.