Website Log Analyzer

What Can a Website Log Analyzer Do?

A website log analyzer is a free online tool for parsing server access logs and analyzing request activity. It summarizes total requests, HTTP status codes, request methods, popular URLs, source IP addresses, referrers, browsers, device information, and response traffic. Use it to understand website traffic and investigate 4xx/5xx errors, repeated requests, and potentially suspicious scanning activity. Log parsing and analysis run locally in your browser, so the original logs do not need to be uploaded to a server.

Supported Log Formats

The tool provides parsing options for Nginx Combined, Apache Combined, Nginx Common, Apache Common, automatic format detection, and custom regular expressions. Custom regex patterns can extract fields through named groups, including ip, time, method, url, protocol, status, bytes, referer, and ua. You can import .log, .txt, and .gz files or paste log text directly. Whether a CDN log can be parsed directly depends on whether its field structure is compatible with the available formats. If it is not compatible, try a custom regular expression. Parsing results depend on the log format, field layout, and whether the expression matches the input.

Key Features

• Request and status code statistics: Summarize request counts, HTTP status code distribution, request methods, popular URLs, and response bytes.
• Traffic source analysis: Review source IP addresses, referrers, browsers, devices, and suspected crawler activity identified from User-Agent strings.
• HTTP error investigation: Examine 4xx and 5xx responses and related request paths to help identify missing resources, access restrictions, and server errors.
• Suspicious request analysis: Identify high-frequency traffic, potentially suspicious scans, and unusual requests based on request frequency, status codes, and URL paths.
• Raw log filtering: Filter log records by time, IP address, URL, status code, request method, and crawler type, then export the filtered results to CSV.
• Custom format parsing: Use custom regular expressions to match non-standard log formats and extract supported named fields.

Log Privacy and Data Security

Log parsing and analysis run locally in your browser. Original logs do not need to be uploaded to a server, and no account registration is required. Access logs may contain IP addresses, request paths, referring pages, and User-Agent strings. Before analyzing them, make sure you are authorized to process the data, and avoid leaving sensitive log content on shared devices.

Frequently Asked Questions

Which servers does the website log analyzer support?

The tool is designed primarily for Nginx, Apache, and access logs with compatible field layouts. Whether a CDN log can be parsed directly depends on its field structure. If the default formats do not match, try a custom regular expression.

Why do some log entries fail to parse?

Common causes include a mismatch between the selected format and the actual log format, a different timestamp format, missing fields, incomplete log lines, or a custom regex that does not match. Check a sample of the original logs, then select a suitable format or adjust the named groups in your expression.

How do I parse logs with a custom regular expression?

Select the custom regex format and write a pattern that matches your log lines. Use the named groups supported by the tool for fields you want to extract, such as ip, time, method, url, status, and ua. Make sure the expression accounts for field order, delimiters, and optional fields, and test it against a small sample before processing a larger file.

Why might status code or response traffic statistics be inaccurate?

Statistics depend on whether the log format matches correctly and whether fields such as status codes and response byte counts are extracted successfully. Missing fields, incompatible formats, or an incorrect custom regex may prevent some records from being included as expected. Check the original logs and parsing format, and compare a sample of raw records with the resulting statistics.

Can the tool confirm that a request came from a genuine search engine crawler?

No. A User-Agent string alone cannot verify a crawler's identity. The crawler type identified by the tool is only an initial indication. To verify official crawlers such as Googlebot or Bingbot, check the source IP address and follow the relevant search engine's official verification procedures.

Is the number of unique IP addresses equal to the number of website visitors?

No. Multiple users may share a NAT or proxy IP address, while one user may use multiple IP addresses. Request count, unique IP count, and actual visitor count are different metrics and should be interpreted according to their respective definitions.

Are there limits on large log files?

Performance and the amount of data that can be processed depend on file size, record count, log line length, browser memory, and device performance. For very large files, split the logs by time range or file size and analyze them in batches to reduce memory usage and make issues easier to investigate.