Log File Analyzer
Parse raw server logs in your browser: count severities, filter and grep lines, and find the messages that repeat most.
Parse raw server logs in your browser: count severities, filter and grep lines, and find the messages that repeat most.
Layerbit’s Log Analyzer doesn’t just colorize text—it acts as a client-side SIEM (Security Information and Event Management) tool. It uses complex Regex mapping to structure raw text into queryable data.
Rapidly isolate critical ERROR and FATAL entries during production outages to identify the root cause, ignoring INFO noise.
Search massive log dumps for specific IP addresses, request IDs, or error codes instantly across filtered or unfiltered views.
Analyze WARN entries to detect high memory usage, slow database queries, or connection pool exhaustion patterns.
Mock forensic scenarios instantly. Click the templates below to load sample logs and watch how the engine categorizes severity and extracts timestamps.
We prioritize zero-trust security architecture. The entire application operates strictly within your browser's DOM. Logs uploaded or pasted are processed locally by JavaScript. Absolutely no data is transmitted over the network, ensuring complete air-gapped security for sensitive production data.
Our complex Regex mapping logic automatically structures raw text from standard Nginx (access/error), Apache, Node.js, Spring Boot, and Docker containers. It targets universal markers for severities like ERROR, FATAL, WARN, INFO, NOTICE, and DEBUG, as well as common ISO/UTC timestamps.
While ELK/Splunk excel at long-term storage and aggregation, Layerbit provides instant, lightweight forensic analysis for immediate IR needs, with zero setup. It renders every line as a DOM row with no virtualization, so it's built for the single log dump you'd actually paste during an incident — comfortably tens of thousands of lines — not a multi-gigabyte archive; split a file that large first (e.g. grep the relevant window) and load that slice instead.
A log file is a chronological record, which is the worst possible ordering for diagnosis. The line that explains an outage is usually one ERROR buried in ten thousand INFO lines, and the useful signal is often not the loudest error but the quiet warning that started forty seconds earlier.
Highlighting by severity changes the reading strategy from sequential to visual: errors and warnings become landmarks you can navigate between, and the density of them over time becomes a shape you can see. That is usually enough to find the window worth reading carefully, which is the actual goal.
Cascading failures produce dramatic downstream errors — connection pool exhausted, circuit breaker open, timeouts everywhere. The first anomaly in the sequence is usually the cause; everything after it is consequence. Work forward from the earliest deviation, not backward from the loudest.
The same warning appearing a thousand times in ten seconds is a different problem from it appearing once an hour, even though the message is identical. Rate matters at least as much as content, and is invisible when you read one line at a time.
Correlating logs across services means their clocks and timezones must agree. Mixed local times, or one service in UTC and another not, will make a cause appear to follow its own effect. Log in UTC with an explicit offset.
When handed a log file and a vague complaint, this order tends to find the answer fastest:
Log files are among the most sensitive artefacts a system produces, and it is worth being conscious of that before pasting one anywhere. In practice they routinely contain bearer tokens in Authorization headers, session identifiers, full request URLs with query parameters, email addresses, internal hostnames and IP addresses, stack traces revealing file paths and library versions, and occasionally a password that ended up in a logged request body.
Which is precisely why this analyzer runs entirely in the page. Your log content is parsed and highlighted by local JavaScript and never transmitted — you can confirm that in your browser's Network tab, or work with the network disconnected entirely. Pasting a production log into a server-side analysis service is, functionally, a data disclosure.