LogSift Documentation
Privacy & Performance
Traditional log tools require you to upload logs (which often contain sensitive user data or IPs). LogSift uses a "No-Cloud" architecture:
- Worker-Based Sifting: The heavy lifting (regex matching and grouping) happens in a background thread to prevent UI freezing.
- Streaming API: Instead of loading the whole file into RAM, LogSift reads chunks sequentially, allowing you to analyze files much larger than your available memory.
Advanced Parsing Engines
LogSift comes with built-in presets for common stack traces and formats:
- Node.js/Python: Tailored for standard stack trace structures.
- Nginx/Docker: Optimized for time-prefixed container logs.
- Generic: A standard heuristic engine that works on almost any plain-text log format.
Pattern Recognition & Grouping
The core strength of LogSift is its ability to collapse 10,000 errors into 5 "Patterns".
- Fuzzy Matching: Identifies logs that originate from the same source even if they have different UUIDs or timestamps.
- Timeline View: Visualizes when specific patterns spiked, helping you correlate a database failure with an API surge.
- Volume Analysis: Quickly identify which "noise" is filling up your disk space.
Sensitive Data Redaction
Before sharing a report or screenshot, use the Redact Sensitive toggle. It automatically hides:
- Email addresses and phone numbers.
- IPv4 and IPv6 addresses.
- Authorization headers and API keys found in request logs.
Frequently Asked Questions
Is there a file size limit?
Files up to 1GB have been tested successfully on modern machines. For larger files, the only bottleneck is the browser's maximum string length.
Can I export the results?
Yes. You can export a "Root Cause Summary" as a clean text file or a detailed JSON report of all identified patterns.
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