Daily log file names should clearly indicate both content and generation date to maintain chronological organization. Consistent naming conventions use YYYYMMDD or YYYY-MM-DD timestamps for unambiguous daily file differentiation. Including project or component identifiers (like server_ or app_) helps instantly recognize the source without opening files, unlike static filenames needing versioning suffixes or folders.

For example, a web service might generate /logs/webserver_20240115.log, rotating files automatically every midnight. A Hadoop data pipeline could use partitioned paths like /system/logs/ingest/dt=20240115/audit.log, leveraging the date directory structure for scalable storage. Tools like Python’s logging.handlers.TimedRotatingFileHandler or Ruby’s Logger automate this pattern.

Benefits include instant time-based sorting and simplified log aggregation tools like Splunk or AWS CloudWatch Logs. Drawbacks involve timezone ambiguity and sequence gaps if rotations fail. Use UTC dates to mitigate timezone conflicts, and pair with monitoring to detect skipped rotations. While timestamps aid forensic analysis, ensure formats avoid regional ambiguities (like MM/DD vs DD/MM).