Incident-Driven Retraining and Postmortems

Every anomaly becomes a labeled learning example: the postmortem produces corrected labels and a retraining mandate, so the fleet gets safer after each event.

Turning events into improvements

When a model misbehaves, a monitor fires, or an unexpected machine event occurs, the response is not only to roll back but to learn. Kronos runs a structured postmortem on every incident that produces a permanent record, corrected labels for the pulses involved, and an explicit retraining mandate for the affected models. The loop from incident to improved model is closed and tracked.

The postmortem is data-first. Using lineage, it reconstructs the exact model that held authority, the inputs it saw, and why it acted as it did. It determines whether the root cause was stale data, mislabeled examples, an unmodeled regime, or a genuine model defect, and each root cause implies a different fix — recurate, relabel, extend the envelope, or redesign.

Postmortem outputs

• Timeline reconstructed from the immutable audit trail
• Root-cause classification (data / label / regime / model)
• Corrected labels for involved pulses (see label provenance)
• Retraining mandate with priority and scope
• Regression test added so the failure cannot silently recur

def postmortem(incident):
    ctx  = lineage.reconstruct(incident)     # model, inputs, decision
    root = classify_root_cause(ctx)
    fixes = {'label':relabel, 'regime':extend_envelope,
             'data':recurate, 'model':redesign}[root](ctx)
    add_regression_test(incident.states)     # lock in the lesson
    return RetrainMandate(models=ctx.affected, priority='high',
                          fixes=fixes)

Every incident also adds a regression test to the frozen benchmark used in CI/CD, so no future model can regress on that exact situation without the pipeline catching it. As breeder units progress FOAK to NOAK to BOAK, lessons from one unit propagate to all through the fleet propagation process, so an incident anywhere strengthens every machine.