RunLocalTools

Log Analyzer — Find Errors and Patterns in Raw Logs (Free)

Paste or upload raw logs to get level counts, a timeline, recurring-error clustering, and IP extraction — free, unlimited, and 100% client-side.

What it does

Paste raw log output — or upload a .log/.txt file — and get an instant breakdown: how many lines at each severity level, a timeline of activity, the most frequent recurring error patterns, and every IP address mentioned, ranked by how often it shows up. It’s built for the moment you’re handed a few thousand lines of logs and just need to know what’s actually going wrong, fast.

How it works

The analyzer auto-detects a severity level (TRACE through FATAL, including common variants like WARNING and CRITICAL) and a timestamp on each line, recognizing ISO 8601, Apache/nginx combined-log, and syslog timestamp formats without any configuration.

The most useful part is pattern mining: each line is normalized by replacing the parts that change — numbers, IP addresses, UUIDs, hex values, quoted strings, timestamps — with placeholders like <NUM> and <IP>, then lines that reduce to the same template are grouped together and counted. That means three error lines that differ only by which server IP failed to connect show up as one pattern with a count of three, instead of three separate, easy-to-miss entries buried in a scroll of text. Click any pattern to filter the raw line view down to just its occurrences.

A regex filter is available too, with the same backtracking-risk check the rest of this site’s regex tools use, so a runaway pattern won’t lock up your tab.

How to use it

  1. Paste your log text, or drop a log file onto the upload area — it’s kept in your browser so a refresh won’t lose it.
  2. Check the stats bar and timeline for an at-a-glance sense of error rate and when problems clustered.
  3. Switch to the Patterns tab to see recurring errors ranked by frequency, and click one to jump to its matching lines.
  4. Use the level checkboxes, free-text search, or a regex filter to narrow the Lines view.
  5. Export the filtered lines or the whole pattern summary as a file when you’re done.

If you want to test a filter regex on its own before pasting it in here, the regex tester is a good place to work it out first. And once you’ve identified what went wrong, the incident timeline builder can help turn these clusters into a structured postmortem.

Privacy

Your logs never leave your browser — there’s no upload, and nothing is sent anywhere for analysis. That matters here more than most tools, since logs often contain IPs, user identifiers, or internal hostnames you wouldn’t want passing through a third-party server.

FAQ

What timestamp formats are recognized?

ISO 8601 (2024-03-15T10:22:31Z), Apache/nginx combined-log format ([10/Oct/2023:13:55:36 +0000]), and syslog format (Jan 12 03:14:15). Lines without a recognizable timestamp still count toward the totals but are left out of the timeline.

How does the pattern clustering handle lines that are almost, but not quite, identical?

It replaces the parts most likely to vary — numbers, IPs, UUIDs, hex, and quoted strings — before comparing. Two lines that differ only in those spots cluster into one pattern; lines that differ in their actual wording stay separate.

Can it handle really large logs?

Yes — tens of thousands of lines process in well under a second, since it’s all plain JavaScript running locally with no network round-trip.

Does it detect log levels that aren’t the standard six?

It recognizes TRACE, DEBUG, INFO, WARN, ERROR, and FATAL, along with common aliases (WARNING→WARN, CRITICAL/SEVERE→FATAL). Lines with no matching level word still show up in the line and pattern views — they’re just counted separately in the stats.

Will this work on logs from any language or framework?

It works on any plain-text log, regardless of source — the level and timestamp detection are pattern-based, not tied to a specific framework’s output format.