[Daneel_]

As a person who has worked in and around logging and big data processing for 16 years now, including almost a decade working as a senior in professional services (currently a global security architect) directly for one of the largest big data companies, here is my opinion on logs vs metrics:

A log entry should capture an event in time, for example: a person logging in, a failure, a record of a notable event occurring, etc. These should be written at the time they occur when possible, to minimise chance of loss and to minimise delay for any downstream systems that might consume the logs. Arguments for batching could easily be made for systems generating very high volumes of logs.

Conversely, a metric is a single value, point-in-time capture of the size of something, measured in units or with a dimension. For example: current queue depth, number of records processed per second, data transfer rate in MB/s, cpu consumption percentage, etc. These can/should be written periodically, as mentioned in TFA.