What Is JSON Log Viewing?
JSON log viewing is the practice of parsing structured log entries — typically in newline-delimited JSON (NDJSON) format — into a readable table so you can quickly scan timestamps, severity levels, messages, and metadata. Modern cloud-native applications emit logs as JSON objects, one per line, making machine parsing easy but human reading difficult.
This is used for:
- Debugging Production Issues: Scan hundreds of log lines in a structured view to spot error patterns.
- Log Analysis: Extract and examine specific fields like
level,message,service, ortraceIdacross many entries. - Incident Response: Quickly filter by error-level logs during an outage without scrolling through raw JSON.
How to Use the JSON Log Viewer Online
- Paste your NDJSON logs: Copy one or more JSON log lines (one object per line) into the editor.
- Click Parse Logs: The tool reads each line, extracts common fields, and renders them in a sortable table.
- Analyze the output: Identify errors, warnings, and info entries at a glance, then copy individual entries as needed.
Frequently Asked Questions
What log formats are supported?
The viewer works with any NDJSON input where each line is a valid JSON object. It intelligently detects fields like timestamp, level, severity, message, msg, service, and logger regardless of naming variation.
Is this tool safe?
Yes. All processing happens 100% client-side in your browser. Nothing is uploaded to any server.
Is this tool free?
Yes, completely free with no usage limits or registration required.
Real-World Examples
A DevOps engineer debugging a Kubernetes pod crash can copy the container's JSON-formatted logs from kubectl logs and paste them into this viewer. The structured table immediately surfaces the error-level entries and their timestamps, cutting investigation time significantly.
Related Tools
- JSON to Table — Convert any JSON data into an HTML table for visualization.
- JSON to CSV — Export JSON log data as a CSV file for spreadsheet analysis.
- JSON Filter — Filter JSON data by field values to narrow down log entries.