Log Fingerprints

During ingestion, the Kf-Parse stage of the parsing pipeline computes a fingerprint for every log line by replacing its variable segments with placeholders. Given:

the fingerprint is:

and the auto-extracted facets are ts, caller, method, result, and took — see Facets for how facet extraction works more generally. Storing the template once and the variable values separately, rather than re-indexing the full text of every line, is what keeps Kloudfuse’s highly repetitive log traffic both fully searchable and storage-efficient.

The Fingerprints tab (alongside Logs, Timeseries, Table, and the other views — see View tabs) clusters your current search’s results by fingerprint instead of listing them one at a time. Group by a field — source, for example — to see, per group, each distinct fingerprint’s pattern, its occurrence count over the selected time range, and a trend sparkline.

This turns "this source is noisy" into "this source produces these four kinds of lines, and this one just spiked" in one screen, without hunting for a distinguishing substring to search for first. Filter by severity (level=error, for example) before switching to Fingerprints to see, at a glance, every kind of error a system is producing — rather than scrolling through every individual occurrence to notice the same few messages repeating.

A log’s fingerprint is also shown on its own detail pane — so you can pivot from "one interesting line" to "every line that shares its pattern" by copying its fingerprint into a search, or the reverse: start from the Fingerprints view and open one of the underlying lines for full context.

Fingerprinting and facet extraction are heuristic — accurate for most log formats, but not guaranteed for all of them. When a format needs precise extraction, define a custom grammar (dissect or grok pattern) instead of relying on the automatic heuristic; see Grammar for the configuration reference.