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About Bugban

Bugban is a self-hosted platform for monitoring errors, performance issues and slow database queries across PHP, JavaScript and mobile applications. It captures stack traces, request context, DOM snapshots and mobile screenshots, grouping errors by fingerprint with metadata such as first occurrence, frequency and status. Each error is analyzed by AI to produce a root cause explanation and a concrete fix, which is automatically opened as a pull request on GitHub when the project is connected. Slow queries are flagged with their EXPLAIN plan, highlighting full scans, index usage and unfixable patterns like leading-wildcard LIKE clauses. Performance metrics include Web Vitals for browsers and app start, screen load and jank for mobile, with thresholds and separate AI prompts tailored to each context. The system supports multiple languages for AI output and integrates with notification channels such as in-app, email, Slack and Telegram, including emergency phone calls via Telegram for critical spikes. Alerts can also trigger webhooks to external systems like Jira or Trello.

Key features

  • Error and exception tracking with fingerprint grouping
  • AI root cause analysis and fix generation
  • Slow query monitoring with EXPLAIN plans
  • GitHub pull request creation for fixes
  • DOM snapshots and mobile screenshots capture
  • Performance metrics for web and mobile
  • Multi-channel alerts and escalation
  • Webhook integration for external systems

Use cases

  • Debugging production errors with full context
  • Identifying and fixing slow database queries
  • Monitoring performance regressions across releases

Pros

  • Self-hosted deployment with full data control
  • AI-generated fixes automatically opened as GitHub pull requests
  • Supports PHP, JavaScript and mobile apps with official SDKs
  • Detailed error context including DOM snapshots and mobile screenshots
  • Multi-language AI analysis and notifications

Cons

  • No free tier beyond a 7-day trial
  • Requires GitHub integration for automatic fixes
  • Limited to supported SDKs and frameworks
  • No cloud-hosted option

Frequently asked questions about Bugban

What is Bugban and what does it do?

Bugban is a self-hosted platform for monitoring errors, performance issues, and slow database queries across PHP, JavaScript, and mobile applications. It captures detailed error context, analyzes issues with AI to provide root cause explanations and fixes, and can automatically open pull requests on GitHub with suggested fixes.

Who is Bugban suitable for?

Bugban is suitable for developers and teams working with PHP, JavaScript, or mobile applications who need self-hosted error tracking with AI-driven fixes and performance monitoring. It is ideal for those who prioritize data privacy and want automated error resolution workflows.

How does Bugban integrate with GitHub?

Bugban integrates with GitHub by automatically opening pull requests with AI-generated fixes when errors occur. The GitHub App reads only the relevant files from the stack trace, writes changes to a dedicated branch, and creates a pull request for review without requiring stored tokens.

What kind of alerts and notifications does Bugban support?

Bugban supports multiple notification channels, including in-app, email, Slack, and Telegram. For critical issues, it can place emergency phone calls via Telegram to alert team members, alongside optional WhatsApp messages and webhook integrations for external systems like Jira or Trello.

Does Bugban support multiple programming languages for AI output?

Yes, Bugban supports AI analysis and explanations in multiple languages, including Azerbaijani, English, Russian, and Turkish, allowing teams to receive error insights in their preferred language.

How does Bugban handle slow database queries?

Bugban flags slow queries with their EXPLAIN plan, highlighting issues like full table scans, index usage, and unfixable patterns such as leading-wildcard LIKE clauses. It allows one-click re-measurement of queries executed safely on the user's server without exposing data.

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