A development team is monitoring a serverless function that handles data processing tasks triggered by a NoSQL database stream. They are encountering issues with failed executions and need a way to quantify these incidents due to client-related mistakes. Which approach would BEST assist them in identifying and quantifying these specific issues over time for the purpose of application fine-tuning?
Expand log entries to include detailed error messages for each execution and periodically review for client errors
Increase the function's monitoring level to capture all execution paths and errors
Implement a custom metric recorded directly from the function whenever a client error is encountered during the data processing
Incorporate a distributed tracing system to tag and review instances of client errors in function executions