How do I parse log files online?

Visit unblockdevs.com/log-explorer and paste your log content directly into the input area. The tool auto-detects the format (JSON, NDJSON, Apache, Nginx, CSV, or plain text) and renders each entry as a structured, filterable row. No file upload required — all processing happens in your browser.

How do I filter logs to find specific errors?

Use the level filter to show only ERROR or WARN entries, then use the keyword search to narrow down by message, service name, or trace ID. The tool also supports regex patterns for advanced filtering across any log field.

What is structured logging and why does it matter?

Structured logging means writing each log entry as a machine-parseable format (typically JSON) with consistent field names. This makes logs queryable, alertable, and easier to aggregate in tools like Datadog, CloudWatch, or ELK Stack. Unstructured plain text logs require regex parsing and break when message formats change.

How do I search logs by regex?

In the search bar, prefix your query with / to switch to regex mode: for example, /timeout|connection refused will match any log entry containing "timeout" or "connection refused". Regex search works across all parsed fields including message, service, and trace ID — useful for matching variable error messages, UUIDs, or IP addresses.

What is NDJSON and how is it different from JSON?

NDJSON (Newline Delimited JSON), also called JSON Lines, is a format where each line is a valid JSON object. Unlike standard JSON (which wraps everything in an array), NDJSON is streamable and append-friendly — each log entry is written as a complete JSON object on its own line. It is the default log format for Docker, Kubernetes, Datadog, and many logging libraries.

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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.

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Paste logs

JSON lines, plain text, stack traces. Docker, Kubernetes, CloudWatch — one entry per line.

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Structured log analysis

Tools and techniques for parsing and analyzing logs.

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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

Paste or upload logs

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

Auto-detect format

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

Filter & search

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

Export results

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

Supported Log Formats

Format	Description
JSON	Single JSON object per entry — common in Node.js, Python, and Go services
NDJSON / JSON Lines	One JSON object per line — default format for Docker, Kubernetes, and Datadog
Apache Common Log	Fixed-format access logs from Apache HTTP Server
Nginx	Access and error logs from Nginx — combined and error formats
CSV	Comma-separated log exports from CloudWatch, Splunk, or custom pipelines
Plain text	Free-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.

2What is the difference between JSON logs and plain text logs?

JSON logs store each entry as a structured object with named fields (level, message, timestamp, traceId). Plain text logs (Apache, Nginx, custom formats) use positional or regex-parsed fields. Structured JSON is strongly preferred for production because it is machine-queryable and does not break when message text changes.

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.

4What are log levels and which ones should I monitor?

Standard log levels in order of severity: DEBUG < INFO < WARN < ERROR < FATAL. In production, monitor ERROR and FATAL actively (they require action), investigate WARN trends, and treat DEBUG/INFO as diagnostic noise. Filter to ERROR first when triaging incidents.

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.

7What is NDJSON (JSON Lines)?

NDJSON is a format where each line is a valid JSON object. It is streamable and append-friendly — perfect for logging. Docker, Kubernetes, Datadog, and most logging libraries use NDJSON as the default log format.

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.

12What is the difference between structured and unstructured logs?

Structured logs are machine-readable JSON records with defined fields (timestamp, level, message). Unstructured logs are free-form text lines requiring regex to parse. Log Explorer handles both — it parses JSON and NDJSON automatically and extracts fields from common formats like Apache Combined Log and syslog via heuristics.

Learn more

Developer Guides

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

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

Paste logs

Never paste production secrets into unknown tools

Learn more

Structured log analysis

What Is a Log Explorer?

Explore Logs in Seconds

Paste or upload logs

Auto-detect format

Filter & search

Export results

Supported Log Formats

When Developers Use Log Explorer

Frequently Asked Questions

Tools You Might Also Need

Developer Guides

Feedback for log_explorer

Stay Updated

Get in touch