Why Shopify Integrations Drift (And How to Reconcile)

Every integration drifts. It is not a question of if, but when and by how much. Understanding why drift happens - and how to reconcile it - is the difference between reactive firefighting and proactive reliability engineering.

What is Integration Drift?

Drift occurs when data in two integrated systems no longer matches, despite being intended to stay synchronized. Your Shopify store shows 10 units in stock. Your ERP shows 8. One order exists in Shopify but not in your fulfillment system. A product price is $49.99 in one database and $54.99 in another.

Drift is not always visible. It accumulates silently until it causes user-facing problems: overselling inventory, missing fulfillments, incorrect pricing, or customers seeing stale data. By the time you discover drift, you are debugging backwards trying to find when and why synchronization broke.

Root Cause 1: Missed Webhooks

Webhooks are reliable - until they are not. Networks experience transient failures. Your server might be down during a deployment. Shopify retries webhooks several times, but if all retries fail, the event is lost forever.

Real-world scenario: During a 5-minute deployment window, your webhook endpoint returns 503 errors. Shopify retries twice and then gives up. Three inventory adjustments and one order creation never reach your system. Shopify and your database are now out of sync, and you have no record that these events happened.

Root Cause 2: Eventual Consistency Windows

Distributed systems achieve consistency eventually, not immediately. When you update inventory in Shopify, it might take milliseconds to propagate through Shopify internal systems before webhooks fire. If you query the API during that window, you see stale data.

Root Cause 3: Partial Failures

Integrations involve multi-step processes. Each step can fail independently. You might successfully write to Shopify but fail to update your analytics database. Or succeed in updating inventory but fail to send the notification email. Partial failures leave systems in inconsistent states.

Root Cause 4: Schema Changes

APIs evolve. Shopify adds new fields, deprecates old ones, or changes validation rules. Your integration code was written against yesterday schema. Today schema breaks assumptions, and your sync logic silently fails or skips data it does not recognize.

How Reconciliation Works

Since drift is inevitable, the solution is not perfect sync - it is continuous reconciliation. Reconciliation means periodically comparing system states and correcting discrepancies.

1. Periodic Full-Sync Checks

Schedule jobs that compare critical data across systems. For inventory: fetch all SKUs from Shopify and your ERP, compare quantities, flag differences beyond tolerance (±2 units is noise, ±10 is real drift).

2. Delta Detection

Do not re-sync everything. Detect what changed since the last reconciliation. Use timestamps, version numbers, or checksums to identify entities that need correction. Only sync the delta.

3. Safe Correction

When reconciliation finds drift, correction must be safe. Do not blindly overwrite - you might overwrite a recent change with stale data.

4. Alerting and Monitoring

Reconciliation is not just a batch job - it is a monitoring tool. Track discrepancy counts and alert when they spike - this indicates a systemic issue.

Conclusion

Drift is not a bug - it is a property of distributed systems. Perfect synchronization is impossible. The engineering solution is not preventing drift but detecting and correcting it faster than it causes problems.