Log File Analyzer
Parse Apache & Nginx access logs — top IPs, status codes, paths, methods & errors. 100% in your browser.
Total Requests
12
Unique Visitors (IPs)
6
Bandwidth Transferred
39.83 KB
Error Rate (4xx/5xx)
4 (33.3%)
HTTP Response Status Breakdown
Top IP Addresses
Top Requested Endpoints
Status Codes
HTTP Methods
Top User Agents
How the log file analyzer works
Paste raw access-log lines from Apache or Nginx and this tool parses the Common Log Format and Combined Log Format entirely in your browser — your server logs are never uploaded. It extracts the client IP, request method, path, response status, and bytes transferred from each line, then aggregates the totals: traffic volume, unique visitors, status-code breakdown, the busiest endpoints, and which clients (and bots) hit you hardest.
The 4xx/5xx error tally surfaces broken links and failing endpoints at a glance, and the top-IP + top-user-agent tables make it easy to spot crawlers and abusive clients (e.g. repeated /wp-login.php probes). Paths are grouped without their query string so endpoints aggregate cleanly. For decoding individual codes, see the HTTP Status Codes reference; to format request URLs, try the URL Parser.
Built and maintained by Meet Shah · Last updated
What this tool is used for
- Summarising an access log by status code, path and address.
- Finding which paths generate the most errors.
- Identifying a single address responsible for a traffic spike.
- Checking a log for a pattern before writing a query.
- Analysing a log you should not upload anywhere.
Frequently Asked Questions
- What should I look at first in a log?
- The error rate over time rather than individual lines. A spike locates the moment something changed, which narrows the search far faster than reading forward from the beginning.
- Why are structured logs worth the effort?
- Because JSON lines can be filtered and aggregated without regex. Free-text logs need a parser per format, and that parser breaks the first time someone rewords a message.
- What is a correlation ID?
- An identifier attached to every log line from one request, so a single operation can be followed across services. Without one, distributed logs are a pile of unrelated lines with similar timestamps.
- Should logs contain personal data?
- As little as possible. Logs are copied, shipped to third-party services and retained far longer than anyone intends — which makes them a common source of breaches involving data nobody realised was there.
- What timezone should log timestamps use?
- UTC, with an explicit offset in the format. Local timestamps make correlating servers in different regions painful and become ambiguous for an hour every autumn.
Common errors and gotchas
- Reading bot traffic as user traffic, which for most sites is a large share of requests.
- Assuming the client address is the real one, when a proxy or a CDN sits in front.
- Analysing a rotated fragment and treating it as a full period.
- Reading a 404 count without checking whether the paths are scans rather than broken links.
- Loading a very large log into a browser tab, which can exhaust memory.