a597873885/webfunny_monitor

【免费社区版】【企业版】Webfunny是一款集全链路监控和用户行为分析(埋点)系统于一体的大数据分析系统,我们致力于解决线上的疑难杂症和精细化分析业务数据;监控系统面向技术、埋点系统面向业务,两者配合使用,相得益彰。

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Summary Information

Updated 17 minutes ago
Added to GitGenius on September 12th, 2026
Created on July 4th, 2018
Open Issues & Pull Requests: 111 (+0)
GitHub issues: Enabled
Number of forks: 883
Total Stargazers: 5,301 (+0)
Total Subscribers: 87 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 0.4 hours
Mean response time: 4.4 hours
90th percentile: 21.0 hours
Tracked items: 5

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Open issues: 3
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 298 days
Stale 30+ days: 2
Stale 90+ days: 2

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Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Detailed Description

Webfunny is a full-stack monitoring and analytics platform that combines frontend monitoring, backend APM, and user behavior tracking in a single system.

The tool addresses the challenge of diagnosing production issues and analyzing business metrics across the entire application stack. It works by injecting a probe that automatically collects errors, performance data, and user behavior without requiring changes to business logic. The frontend monitoring system captures real-time traffic metrics, user sessions with behavior replay, code errors with source map support, API and page performance data, remote debugging capabilities, and session recordings. The backend APM component monitors service performance and infrastructure. A separate event tracking system allows business teams to instrument custom analytics. These three subsystems work together to provide visibility from the user's browser through backend services to databases.

Teams should adopt this tool if they need comprehensive observability across frontend and backend without extensive code instrumentation, prefer to keep data within their own infrastructure, or want to avoid vendor lock-in. It suits organizations that can deploy and maintain their own infrastructure, as it supports private deployment via Docker with only Node.js as a requirement. The tool is positioned as an alternative to cloud-based monitoring services, offering the ability to handle high-traffic scenarios through cluster deployment while maintaining complete data ownership.

The project maintains active development with regular commits and ongoing issue resolution. The codebase is written in JavaScript and includes both community and enterprise editions, with source code available for purchase to enable custom modifications. Documentation covers deployment procedures and usage patterns across the monitoring and analytics features.