How to inspect Cloud Vision API errors?

[raulvadillo]

As I can see, I have 10% errors of the calls made to "google.cloud.vision.v1.ImageAnnotator.BatchAnnotateImages". But I don't know how to inspect why this errors are raising. I tried using the Reg Explorer but I only can see rows with INFO severity. I tried with periods of time which I know that errors were raised, for the record.

[priyalkaur]

Inspecting errors in the Google Cloud Vision API can be essential for troubleshooting and improving the reliability of your applications. To investigate the errors you're encountering when using the "google.cloud.vision.v1.ImageAnnotator.BatchAnnotateImages" API, you can follow these steps:

1. Check the Response: Whenever you make a request to the Cloud Vision API, it returns a response. The response often includes specific error messages and details about what went wrong. Inspect the response object in your code to extract error information.

2. Error Handling in Code: Ensure that your code includes proper error-handling mechanisms to capture and log any exceptions or errors that occur during API calls. Depending on the programming language you're using, this might involve try-catch blocks, error handlers, or exception logging.

3. Logging and Debugging: Implement extensive logging in your application. Log relevant information, including the input data sent to the API, timestamps, and response details. This will help you trace the source of errors and identify patterns.

4. Google Cloud Console: Go to the Google Cloud Console and navigate to the specific project associated with your Cloud Vision API usage. Look for error logs and monitoring information related to the API calls. Google Cloud offers comprehensive logging and monitoring tools.

5. Error Codes and Messages: Refer to the Google Cloud Vision API documentation for a list of error codes and messages specific to the API. These codes can provide insights into the nature of the errors.

6. Rate Limiting and Quotas: Ensure that you are not exceeding the rate limits or quotas for the Cloud Vision API. If you exceed these limits, it can result in errors. Check the Google Cloud Console, navigate to the API usage section, and monitor your usage.

7. Community and Support: Reach out to the Google Cloud community or support for assistance if you encounter persistent issues that you cannot resolve on your own. They can provide guidance on specific problems.

8. Network and Connectivity: Sometimes, errors may be related to network issues. Ensure that your network connection is stable and that you can reach the Cloud Vision API endpoints.

hope these tips help.