Sending custom metrics from AWS Lambda could impact the function in what way?

Sending custom metrics from AWS Lambda can indeed impact the duration of the function. When custom metrics are being sent, the function has to perform additional tasks beyond executing its main purpose. This additional work requires time, which can lead to an increase in the overall duration of the function's execution.

When a Lambda function is invoked, it runs for a limited amount of time, and any extra processing for tasks such as logging custom metrics consumes part of that execution window. As a result, if the function has to handle sending metrics, it may not only take more time to complete its existing operations but also the overhead of facilitating communication with the metrics system. This can lead to longer execution times and potential implications on costs associated with Lambda, as AWS charges based on the duration of the function.

The other choices do not accurately capture the implications of sending custom metrics. For example, while sending metrics can lead to increased memory usage, it is not guaranteed to always cause an increase. In some scenarios, the effect may be negligible. Statements regarding optimization and no effects on duration do not align with the reality that any added workload typically requires additional processing time.