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rootcoz

Automatically diagnose CI/CD test failures with AI and get actionable root cause analysis in seconds

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Getting Started

  • Quickstart

    Install rootcoz via Docker Compose, configure your AI provider and CI system, register your first user, and run your first failure analysis in under five minutes

  • Setting Up the CLI

    Install the rootcoz CLI tool, configure server connections in config.toml, authenticate with API keys, and run your first analysis from the command line

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User Guides

  • Analyzing Test Failures

    Submit Jenkins jobs, JUnit XML files, or raw failure lists for AI-powered root cause analysis via the web UI, API, or CLI

  • Reviewing Analysis Results

    Navigate the report page, understand AI classifications (Product Bug, Test Bug, Infra Bug), review failures, override classifications, and track review progress

  • Chatting with AI About Failures

    Use the interactive chat feature to ask follow-up questions about analyzed jobs, explore root causes deeper, and get code fix suggestions

  • Creating Bug Reports from Analysis

    Preview and create GitHub issues or Jira bugs directly from failure analysis results, with AI-generated titles, descriptions, and duplicate detection

  • Configuring Integrations

    Set up Jenkins, Jira, GitHub, and Report Portal integrations including authentication, SSL settings, and per-request overrides

  • Using Multi-AI Peer Analysis

    Configure multiple AI providers to debate and reach consensus on failure classifications, improving accuracy through peer review rounds

  • Managing Users and Roles

    Register users, assign roles (viewer, reviewer, operator, admin), approve pending registrations, configure allow lists, and rotate API keys

  • Tracking Failure History and Reports

    Use the failure history page to find recurring test failures, view per-test timelines, and generate analytics reports on classification trends and team metrics

  • Integrating with pytest

    Add the --analyze-with-ai flag to your pytest runs to automatically enrich JUnit XML reports with AI root cause analysis

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Recipes

  • Deployment Recipes

    Common deployment patterns including Docker Compose production setup, OpenShift deployment, reverse proxy with trusted headers, and dev mode with hot reload

  • CLI Recipes

    Copy-paste CLI commands for common workflows: batch analysis, bulk classification overrides, filtered dashboards, exporting reports, and admin operations

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Reference

  • REST API Reference

    Complete reference for all API endpoints including analysis submission, results retrieval, comments, classifications, chat, admin operations, and SSE streams

  • CLI Command Reference

    Full reference for all rootcoz CLI commands and subcommands: analyze, results, history, comments, classifications, chat, reports, config, auth, and admin

  • Environment Variables and Configuration

    Complete list of all environment variables organized by category: Jenkins, AI providers, Jira, GitHub, Report Portal, authentication, server settings, and Web Push

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