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LogSift Documentation

LogSift is a high-performance log analysis tool designed to find the "needle in the haystack" across massive datasets. It identifies repeating patterns, groups related errors, and helps isolate root causes—all without ever uploading your logs to a server. Open LogSift.

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".

  1. Fuzzy Matching: Identifies logs that originate from the same source even if they have different UUIDs or timestamps.
  2. Timeline View: Visualizes when specific patterns spiked, helping you correlate a database failure with an API surge.
  3. 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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