API Requests Report
Monitor your API usage, error rates, and response performance to maintain reliable integrations and quickly identify issues.
The API Requests Report provides a complete picture of how your API integrations are performing. It tracks every request made to your system, surfaces validation errors that may indicate integration issues, and monitors response times so you can ensure your API consumers are getting a fast, reliable experience. Use this report to detect problems early, measure integration health, and hold response time standards.
What This Report Includes
This report analyzes all API requests based on the date and time each request was created.
Requests Included:
- All API requests received by the system, regardless of outcome
- Includes both successful requests and those that returned validation errors
- Date range is based on API Created Date (when the API request was received)
Why This Matters: Your API is the backbone of your integrations — whether powering your checkout, managing subscriptions, or syncing with third-party systems. Degraded API performance or rising error rates can directly impact revenue and customer experience.
Report Metrics
Total Requests
The total number of API requests received during the selected period. This is your baseline volume metric, showing how much traffic your API is handling. Sudden spikes or drops in request volume can indicate changes in integration behavior, bot activity, or upstream system issues.
Validation Errors
The number of API requests that had validation errors. These are requests where the submitted data didn't meet the required format or contained missing/invalid parameters.
Validation Error Rate
The percentage of total requests that resulted in a validation error. Calculated as Validation Errors divided by Total Requests. A low Validation Error Rate indicates healthy, well-configured integrations. A rising rate may signal a recent integration change that introduced malformed requests, or a third-party system sending bad data.
Response Time
The average time, in seconds, that the API took to respond to requests during the selected period. This measures end-to-end processing speed from request receipt to response delivery. Fast response times are essential for checkout flows and real-time integrations — slow responses can lead to timeouts, retries, and poor customer experiences.
Available Dimensions
Use these dimensions to slice and filter your API request data for deeper analysis.
| Dimension | Description |
|---|---|
| API Created Date | The date the API request was made |
| API Created Hour | Hour of day when the request was made (0–23) |
| API Created Day Of Week | Day of the week the request was made |
| API Created Week | ISO week number of the request |
| API Created Month | Month and year of the request |
| API Created Year | Year the request was made |
| API ID | The unique identifier for the API request |
| API Method | The API method or endpoint called |
| API User | The API user or key that made the request |
| API Response Code | The response code returned by the API |
| API Validation Code | The validation code returned for the request |
Key Business Insights
1. Integration Health Score Use Validation Error Rate as a proxy for integration quality. Well-maintained integrations should consistently show error rates below 1%. Rates above that threshold warrant investigation into which API consumers are sending invalid requests.
2. Volume Trend Analysis Track Total Requests over time to understand usage patterns. Identify peak traffic periods, correlate request spikes with marketing campaigns or product launches, and ensure your infrastructure can handle the load.
3. Performance Benchmarking Establish a Response Time baseline during normal operations. Compare against this baseline to detect performance degradation. Even small increases in average response time can compound across thousands of requests to significantly impact user experience.
4. Error Spike Detection Monitor Validation Errors for sudden increases. A spike often coincides with a code deployment, integration change, or third-party update. Catching these spikes early allows you to resolve issues before they affect a large number of transactions.
Optimization Strategies
Reduce Validation Errors
- Review the most common validation error reasons and share guidance with integration partners
- Implement client-side validation in your checkout or integration layers to catch errors before they reach the API
- Monitor Validation Error Rate after any integration deployment to catch regressions immediately
Optimize Response Times
- Track Response Time trends and investigate any sustained increases
- Correlate slow response times with Total Request volume to determine if performance degrades under load
- Work with your infrastructure team to identify bottlenecks during peak traffic periods
Monitor Integration Partners
- Set expectations with partners around acceptable Validation Error Rates and provide them with clear integration documentation
- Schedule regular integration health reviews using this report's data
Pro Tips
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Set up regular monitoring cadence. Check this report daily — even a brief glance at Total Requests, Validation Error Rate, and Response Time can surface issues before they escalate.
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Correlate with the Transactions Report. If you notice a drop in successful charges, check the API Requests Report for a corresponding spike in Validation Errors. The root cause may be an integration issue rather than a payment processing problem.
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Use Response Time as an early warning. Gradual increases in response time often precede more visible issues like timeouts and failed transactions. Treat any sustained upward trend as an action item.
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Investigate new error patterns after deployments. Whenever you or an integration partner deploys a change, review this report within 24 hours to confirm that Validation Error Rate hasn't increased.
Frequently Asked Questions
Q: What counts as a "validation error"? A: A validation error occurs when an API request is rejected because the submitted data doesn't meet requirements — for example, missing required fields, invalid data formats, or out-of-range values. These are distinct from processing errors that occur after validation passes.
Q: Why might Total Requests suddenly spike? A: Common causes include integration retries (an upstream system re-sending failed requests), bot or scraping activity, a new integration going live, or a marketing campaign driving increased checkout traffic. Cross-reference with your other reports to determine the cause.
Updated 6 days ago