Essence - free native log viewer for Mac
A flexible & privacy-focused analytics solution for NGINX.
Server-side Query Fan-Out Session monitoring & reporting for LLM user-bot traffic
A visualization tool that can extract information from any server log (i.e. HTTP server/Django/Auth/etc), reverse-search the data, and visualize the origination of the authentication attempts.
Another parser for server logs to find potential vulnerabilities
Self-hosted server log analytics for AI bot detection, AI agent monitoring, and AI visibility. Classifies GPTBot, ClaudeBot, ChatGPT-User, Perplexity & more from edge JSONL — no JS tag, no SaaS. Open-source alternative to Cloudflare AI Crawl Control.
Turn raw server/CDN access logs into verified-crawler analytics: parse many log formats, verify Googlebot/Bingbot by IP (not user-agent), enrich with DuckDB, and analyze crawl budget, crawl waste, and crawl traps with SQL.
LogWerk is a lightweight, offline-first server log analyzer dashboard that runs entirely in your web browser.
Free, private, 100% client-side log file analyzer: GPTBot vs OAI-SearchBot cost split, crawl budget, Cloudflare/Fastly/AWS edge rules + robots.txt generator. Training vs search-index vs user-triggered AI split (2026).
Introduction to server logging for web apps
Local-first AWK-powered log parser for Apache and Nginx logs.
巨大サーバーログ・圧縮.gzログから正規表現マッチ行を高速抽出するGUIツール（Windows専用・完全オフライン）
Record which AI crawlers read your pages. Forwards GPTBot, ClaudeBot, PerplexityBot and friends to rankveo, and nothing else.
Ruby CLI for streaming server log analysis with gzip input, thresholds, trend buckets, comparison mode, config, and export support.
Analyze server access logs locally in your browser: real page views, visits, purchases, and the gap to Google Analytics. No upload.
A full-stack logging dashboard that captures both client-side and server-side logs with visual analytics, filtering, and CSV export - built using Next.js and Material UI.
Sparkling Water is a scalable system for detecting, merging, and clustering similar server processes based on interaction logs. Using Apache Spark, MinHash, LSH, and time-series hashing (SSH, BSeSH), it efficiently identifies behavior patterns in large server infrastructures for performance optimization, anomaly detection, and system analysis.
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