6 Warning Signs Your Integrations Are Silently Breaking

The most dangerous integration failure is the one that does not announce itself. A loud crash—an HTTP 500 error, a workflow that halts mid-execution—gets noticed and fixed within hours. But a silent breakdown, where data drifts, records quietly go missing, or fields slowly degrade, can run undetected for weeks. By the time someone notices, you are reconciling hundreds of mismatched records across your QuickBooks, shipping, and inventory systems.

Here are six warning signs that your integrations are failing without telling you, and what to do about each one.

1. Record Counts No Longer Match Between Systems

This is the earliest and most reliable signal. If your e-commerce platform shows 847 orders this week but QuickBooks only has 839 invoices, eight orders vanished somewhere in the pipeline. The discrepancy might be small enough that nobody notices during normal operations, but it compounds daily.

The fix is straightforward: build a nightly reconciliation job that compares record counts across every connected system. A simple script that queries order counts from Shopify, invoice counts from QuickBooks, and shipment counts from ShipStation, then alerts when the delta exceeds zero. This costs almost nothing to implement and catches 80% of silent failures within 24 hours.

2. Timestamps Show Increasing Latency

When an integration is healthy, the time between an order being placed and appearing in your fulfillment system stays consistent. If that gap grows from 2 minutes to 15 minutes to 45 minutes over the course of a month, something is degrading. Common culprits include API rate throttling, growing database query times, or a webhook queue that is filling faster than it drains.

Track the median processing latency weekly. Any sustained upward trend is a red flag, even if all records are still arriving eventually. Today's 45-minute delay becomes tomorrow's timeout error.

Figure 1 — How integrations degrade from healthy to broken over time without proper monitoring

3. Fields Are Arriving Empty or Null

An API provider updates their response schema, deprecates a field, or nests it one level deeper. Your integration still runs without errors because the HTTP response is still 200 OK. But the customer phone number, shipping method, or tax amount now arrives as null. The workflow continues processing as though nothing happened, creating records with missing critical data.

Build field-level validation into every integration step. If a required field comes back empty, the workflow should flag it, not silently proceed. In data entry automation, null-field detection is a first-class concern, not an afterthought.

4. Error Logs Show Intermittent 4xx Responses

Occasional HTTP 401 (unauthorized) or 403 (forbidden) responses that resolve on retry often signal an expiring API token or a rate limit approaching its ceiling. Many teams ignore these because the retry succeeds. But the frequency tells a story: going from one retry per day to ten retries per day means the underlying issue is worsening.

Log every non-200 response, even if the retry succeeds. Chart the frequency weekly. A sustained increase in 401 errors typically means your OAuth token refresh is becoming unreliable. A spike in 429 errors means you are approaching the API's rate limit and need to implement request throttling or batch processing.

5. Webhook Delivery Reports Show Declining Success Rates

Most platforms provide webhook delivery logs. Shopify, WooCommerce, and ShipStation all expose delivery success/failure rates. If your webhook success rate drops from 99.8% to 96%, that 3.8% gap represents real orders that your automation never received. The platform sent them; your endpoint did not acknowledge them.

Common causes include server cold starts on serverless endpoints, SSL certificate expirations on your webhook receiver, or DNS propagation issues after infrastructure changes. Check your webhook delivery logs weekly. Anything below 99.5% warrants immediate investigation.

6. Manual Workarounds Are Increasing

This is the most insidious signal because it is human, not technical. When your operations team starts manually entering orders that "didn't come through," manually correcting addresses that "came in wrong," or manually reconciling invoices that "don't match," they are compensating for a broken integration. They may not even realize it.

Survey your team monthly: "How many records did you manually correct or re-enter this week?" If that number is anything above zero and it is trending upward, your integration is silently failing and humans are absorbing the cost. This hidden labor often exceeds the cost of fixing the actual integration issue.

Figure 2 — Combine automated and human monitoring to catch all six warning signs

Building a Monitoring Layer

The solution to silent integration failures is proactive monitoring, not reactive firefighting. Every integration in your stack should have three monitoring layers: a heartbeat check that confirms the connection is alive, a data validation check that confirms the content is correct, and a volume check that confirms the expected quantity is flowing through.

On platforms like Make.com, you can build a dedicated monitoring scenario that runs hourly, queries each connected system, and sends a Slack alert if any metric falls outside its expected range. The cost is minimal: a few API calls per hour. The alternative—discovering a three-week data gap during a customer escalation—is not.

"If you are not monitoring your integrations, you are trusting them. Trust without verification is how businesses lose data, revenue, and customers."

Do not wait for the symptoms to become obvious. By the time a customer complains about a missing order, the integration has likely been failing for days. Set up your monitoring today, and let the machines watch the machines while you focus on growing the business.