Authored by Gary Nicholls
This post follows on from our AWS Nova log benchmarking article, where we explored how smaller LLMs perform on log analysis tasks. That earlier post highlighted that LLMs are surprisingly good at parsing logs. While that work focused on understanding logs, this post tackles an earlier step: automatically structuring logs using AI.
Logging Origins
Logs are one of the oldest — and still most valuable — forms of observability. Mainframes and early Unix systems were already using logs to record system activity, with tools like syslog dating back to the early 1980s.
Even as systems have become more distributed and complex, logs remain foundational, especially for investigating issues when things go wrong. Logs are typically written to local files before being shipped to modern observability platforms using agents like OpenTelemetry or Fluent Bit.
