The error graph on the “Your Usage” page shows how often API requests fail and the reasons for those failures. It helps surface patterns over time and makes it easier to identify the root cause of failed requests.
What the Error Graph Shows #
Each colored line represents a class of errors based on HTTP status codes. A flat line at zero indicates that no errors of that type occurred on that day. A spike indicates a noticeable increase in failed requests.
Filtering and Exporting API Requests #
The graph can be filtered by product, API key, and date range. Once filters are applied, the graph displays daily error counts for the selected period.
The raw error data can be downloaded by clicking “Export to CSV”. The export includes the date, error type, and count, making it easier to investigate further or share with an engineering team.
Error Types and What They Mean #
- Validation Error (400): Indicates that the request format did not match what the API expects. This typically occurs when a required field is missing or an input value does not meet the rules defined in the API documentation.
- Not Authorized Error (401 or 403): Indicates an authentication or permission issue. This may occur if an API key is missing, incorrect, expired, or not permitted to access the requested resource.
- Not Found Error (404): Means that the endpoint or resource does not exist. This commonly happens when the URL or path is incorrect or when a versioned endpoint has changed.
- Too Many Requests Error (429): Occurs when the request volume exceeds rate limits. The graph helps identify when this happens so throttling or backoff logic can be adjusted accordingly.
- Server Error (5xx): Means that the request reached Trestle’s infrastructure but a server-side failure occurred. These errors are typically temporary. If they appear frequently or in large numbers, please contact support@trestleiq.com.
Using Error Tracking to Maintain Integration Health #
The error graph can be used to monitor trends, catch issues early, and correlate error spikes with releases or traffic changes. Monitoring errors over time helps keep integrations reliable and healthy.