loglensai-rule-discovery-and-hybrid-tracking

Feed representative log samples into the rule discovery workflow, which groups similar messages into templates using token-based clustering. The resulting rules can then be applied to parse future log entries consistently.

Hybrid tracking combines discovered parsing rules with continuous log ingestion so known patterns are matched by rules while unmatched entries are flagged for new rule discovery. This keeps coverage current as log formats evolve.

Yes, the workflow is designed for high-velocity log ingestion backed by DuckDB storage and Drain3 template mining. Rule-based matching keeps per-line processing cheap once templates are established.

Discovery can miss patterns when sample data is too small, log formats vary widely, or messages contain high-cardinality variables. Increasing sample diversity and tuning clustering thresholds improves coverage.

Use manual rules for stable, well-documented log formats where precision matters, such as security audit trails. Automatic discovery is better for exploratory analysis of unfamiliar or rapidly changing log sources.