Keep the model aligned with the real system as both change.
Drift is the gap that opens when the real system changes but the model does not. Managing drift keeps the model trustworthy, so people keep using it. IOModel closes that gap from both ends: automated detection with the Collector, and editing discipline that ties model updates to the changes that cause them.
Where drift comes from
| Source | Example |
|---|---|
| Renamed components | Code renamed, model still uses old slug |
| New dependencies | A service starts calling another; link missing |
| Removed parts | A component is deleted but remains modeled |
| Behavior change | A workflow no longer matches the real sequence |
Automated drift detection
The IOModel Collector scans your repository and running systems and compares the actual state against the documented model. Where they disagree, Studio reports the drift on the live diagram, so you see exactly which deployed components diverge.
| Capability | What it does |
|---|---|
| Scans | Reads the repository and live systems for actual structure |
| Compares | Diffs reality against the documented model |
| Reports | Shows drift on the diagram in Studio, with actionable detail |
| Runs | On a schedule or in CI, with alerts when drift appears |
Run drift checks in CI
Add the Collector to your pipeline (or schedule it) so drift is caught the moment implementation diverges — not at the next manual review. See CI Validation.
Keeping the model current
Update the model with the change
Treat model edits as part of the change, not a follow-up task.
Review links and workflows
Check that relationships and sequences still reflect reality.
Resolve unresolved references
Unresolved links are an early signal of drift; fix them promptly.
Prune what is gone
Remove objects and links that no longer exist.
Validation catches some drift
Diagnostics like unknown-reference often appear when something was renamed
or removed. Use them as drift signals, not just syntax errors.
Make consistency routine
- Tie model updates to the work that causes them.
- Review the model during architecture changes and reviews.
- Keep specs and workflows linked so a change in one prompts the other.
A model that lags reality erodes trust quickly. Small, frequent updates are far cheaper than periodic large reconciliations.
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