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Log Explorer — Parse, Filter & Analyze Log Files, JSON Logs & Structured Logs Online Free

Analyze, search, decode, and visualize JSON, Node, Kubernetes, and CloudWatch logs. 100% client-side.

100% in-browserNo signupFree forever
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What Is a Log Explorer?

A log explorer is a browser-based tool for parsing, filtering, and making sense of application log output — without sending your logs to a third-party service. Paste raw log content and the tool renders each entry as a structured, searchable row.

Structured vs unstructured logs: Structured logs (JSON, NDJSON) carry named fields like level, timestamp, and traceId that can be filtered precisely. Unstructured logs (Apache Common Log, Nginx, plain text) use fixed-position or regex-parsed fields. Log Explorer auto-detects both forms and normalises entries into a consistent view for filtering, searching, and exporting — making log analysis fast even when the format varies.

How it works

Explore Logs in Seconds

01

Paste or upload logs

Drop in raw log text — multi-line JSON, NDJSON, Apache, Nginx, CSV, or unstructured plain text.

02

Auto-detect format

The tool identifies the log format automatically and parses every entry into structured fields.

03

Filter & search

Filter by log level (ERROR, WARN, INFO), search by keyword or regex, and narrow by time range.

04

Export results

Copy filtered entries or export matching rows as JSON or CSV for sharing or further analysis.

Supported Log Formats

FormatDescription
JSONSingle JSON object per entry — common in Node.js, Python, and Go services
NDJSON / JSON LinesOne JSON object per line — default format for Docker, Kubernetes, and Datadog
Apache Common LogFixed-format access logs from Apache HTTP Server
NginxAccess and error logs from Nginx — combined and error formats
CSVComma-separated log exports from CloudWatch, Splunk, or custom pipelines
Plain textFree-form lines — level and timestamp extracted via heuristics
Use cases

When Developers Use Log Explorer

🐛

Debug Production Errors

Paste a log dump, filter to ERROR level, and find the root cause without spinning up a log aggregator.

🌐

Analyze Access Logs

Parse Nginx or Apache access logs to see traffic patterns, status code distribution, and slow requests.

🔍

Find Anomalies

Search for unexpected patterns, spike in warnings, or repeated stack traces across large log files.

⚡

Performance Profiling

Filter by service name or trace ID and sort by duration to identify slow operations in structured logs.

📋

Audit Trails

Inspect user action logs or access audit logs without uploading sensitive data to an external service.

🚨

Incident Response

During an outage, quickly triage logs by time range and error level to narrow down the blast radius.

FAQ

Frequently Asked Questions

1Do my logs get uploaded to any server?
No. Log Explorer runs entirely in your browser using JavaScript. Your log data never leaves your machine — no upload, no server-side processing. Safe for sensitive production logs and PII-containing entries.
2Why can I not filter my logs by service name or trace ID in the explorer?
Field-level filtering only works when logs have named fields — i.e., JSON objects with keys like service, traceId, or requestId. Plain text logs use positional fields without names, so only keyword and regex search apply. If your logs lack structure, consider migrating to JSON logging. Log Explorer parses whatever named fields are available.
3How do I filter logs by severity or keyword?
Use the level dropdown to show only ERROR, WARN, INFO, or DEBUG entries. The keyword search bar matches against any field in the parsed entry. For advanced matching, prefix your query with / to use a regex pattern.
4Why can't I search my logs reliably and how do I fix it?
Plain text logs break keyword search as soon as message formats change and cannot be filtered by field without regex. Switching to structured logging (JSON with consistent fields like level, message, traceId) makes logs queryable and easy to aggregate. Log Explorer handles both formats — paste your logs to filter by level or keyword regardless of format.
5Can I use regex to filter log entries?
Yes. Type a forward slash followed by your regex pattern (e.g. /database.*timeout) in the search bar to match entries with full regex support — useful for matching variable error messages, UUIDs, or IP address ranges.
6How do I view Kubernetes or Docker logs in a browser?
Run kubectl logs <pod-name> or docker logs <container-name>, copy the output, and paste it here. The tool auto-detects NDJSON (JSON Lines) format and renders each entry as a structured, filterable row.
7Why do my Docker or Kubernetes logs look like one long escaped string and how do I read them?
Docker and Kubernetes emit logs in NDJSON format — one JSON object per line. When copied from a terminal they may appear as escaped strings. Paste them into Log Explorer: it auto-detects NDJSON, parses each line into structured fields, and renders them as filterable rows so you can search by level, message, or trace ID.
8How do I parse Apache or Nginx access logs?
Paste your access log lines — the tool recognizes Apache Common Log Format and Nginx access logs automatically and parses each line into IP, timestamp, HTTP method, URL, status code, and user agent fields.
9How do I export filtered log results?
After applying your filters, click Export to download matching entries as JSON or CSV. Useful for sharing specific error windows with teammates or attaching to incident reports.
10What log levels are standard?
Standard levels in order: TRACE < DEBUG < INFO < WARN < ERROR < FATAL. Monitor ERROR and FATAL actively, watch WARN trends, and treat INFO as operational context. DEBUG/TRACE are typically disabled in production.
11How do I analyze CloudWatch logs without the AWS console?
Export CloudWatch logs via the console (Actions → Download) or with aws logs get-log-events. Paste the JSON output here for filtering, search, and timeline analysis without staying in the AWS console.
12How do I find the root cause of an error when my logs are mixed formats and scattered across services?
Paste all your log output — JSON, NDJSON, Apache, Nginx, or plain text — into Log Explorer at once. The tool auto-detects and normalizes the formats into a consistent view. Filter to ERROR level first, then use keyword or regex search to match the error message, and narrow by trace ID for distributed systems. Export the matching entries as JSON or CSV for your incident report.
Learn more

Developer Guides

📖Top 10 JSON Log Errors📖Debugging API Logs📖Structured Logging Guide📖Fix JSON in Log Lines

Last updated: May 2026

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