Sync Drift
When data in source and target systems diverge after syncs or partial failures.
Sync drift is divergence between source and target systems after syncs—caused by missed events, partial failures, or schema changes. It erodes data trust.
It shows up between CRMs, ERPs, warehouses, and product databases when webhooks drop, retries duplicate, or fields change silently.
Handling drift means detecting mismatches and reconciling. Use checksums, sampled comparisons, and targeted backfills to realign and prevent bad decisions from stale data.
Frequently Asked Questions
How do I detect sync drift?
Use counts, checksums, and sampled record comparisons. Monitor webhook failures, DLQs, and reconciliation deltas.
What causes drift?
Dropped events, retries without idempotency, schema changes, manual edits in targets, and bi-directional conflicts.
How do I fix drift safely?
Run reconciliations/backfills with idempotent writes and checkpoints. Validate before overwriting and log changes.
How often should I reconcile?
Based on risk—daily/weekly for critical data. Increase frequency after incidents or schema changes.
How do I prevent drift?
Use reliable ingestion (webhooks/CDC), idempotent writes, and monitoring. Limit manual target edits or sync them back.
Does bi-directional sync increase drift?
Yes—set clear source-of-truth rules and conflict resolution. Avoid freeform edits on both sides.
How do schema changes impact drift?
Unmapped fields or type changes cause gaps. Version schemas and coordinate changes across systems.
What metrics indicate drift risk?
Rising mismatch counts, DLQ growth, and increased reconciliation effort. Track per-connector error rates.
Can I automate drift repairs?
Yes—automate reconciliations for known patterns and alert on anomalies. Keep humans for high-risk corrections.
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