AI-Driven CI/CD Failure Analyzer

A platform that automatically analyzes GitHub Actions CI/CD logs, detects failure causes, maps them to actionable fixes, and provides analytics + automation to improve pipeline reliability and reduce developer debugging time.

Current Features

• GitHub Authentication: Secure user login via a stateless, JWT-based GitHub OAuth2 flow.
• Automated Log Ingestion: Ingests failed GitHub Actions logs automatically via GitHub App webhooks.
• Background Job Processing: Uses a robust queueing system (BullMQ + Redis) to process logs asynchronously, preventing API timeouts and enabling retries.
• Log Analysis (MVP): A foundational service that parses raw logs to detect common error patterns.
• Mock AI Analysis: A placeholder service that mimics an AI call, providing a sample root cause and suggested fix.
• Monorepo Structure: A clean setup with a frontend (React/Vite) and backend (Node.js/Express) in a single repository.
• Modern Database: Utilizes a serverless Postgres database (Neon) with Prisma ORM for type-safe database access.

Architecture

The system is composed of several key components that work together to provide a seamless analysis pipeline.

flowchart TD
  subgraph Client
    FE[React + Vite (5173)]
  end

  subgraph Backend API (3001)
    API[Express app]
    Auth[/auth routes]
    Webhook[/webhooks route]
    Parser[LogParserService]
    AI[AIAnalyzerService]
  end

  subgraph Queue + Worker
    Q[BullMQ Queue]
    Redis[(Redis 6379)]
    Worker[Log Processor]
  end

  subgraph GitHub
    GApp[GitHub App]
    GActions[GitHub Actions]
    GAPI[GitHub REST API]
  end

  subgraph Infrastructure
    Smee[smee.io proxy]
    DB[(Neon Postgres + Prisma)]
  end

  FE -- Login --> Auth
  Auth -- GitHub OAuth2 --> GApp
  GApp --> Auth
  Auth -- JWT --> FE

  FE -- Paste Logs --> API
  API -- AI Analysis --> Parser & AI
  Parser & AI -- Result --> API
  API -- Result --> FE

  GActions -- Workflow Fails --> GApp
  GApp -- Webhook --> Smee
  Smee -- Forwards --> Webhook
  Webhook -- Enqueues Job --> Q
  Q -- Job --> Worker
  Worker -- Fetches Logs --> GAPI
  GAPI -- Log URL --> Worker

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Core Technologies

• Frontend: React, Vite, TypeScript
• Backend: Node.js, Express, TypeScript
• Authentication: JWT, GitHub OAuth
• Database: PostgreSQL (Neon) with Prisma
• Job Queue: BullMQ with Redis
• GitHub Integration: GitHub Apps, Webhooks, Octokit

Setup and Running the Project

1. Prerequisites

• Node.js (v16+)
• npm
• Docker and Docker Compose
• A GitHub account
• A Neon account (for the database)

2. Environment Configuration

Create a .env file in the root of the project and add the following variables. See comments for where to get each value.

# Database URL from your Neon project
DATABASE_URL="postgresql://user:password@host.neon.tech/dbname?sslmode=require"

# GitHub OAuth App credentials (for user login)
# Found in GitHub > Settings > Developer settings > OAuth Apps
GITHUB_CLIENT_ID="your_oauth_app_client_id"
GITHUB_CLIENT_SECRET="your_oauth_app_client_secret"
GITHUB_CALLBACK_URL="http://localhost:3001/auth/github/callback"

# GitHub App credentials (for webhooks and API access)
# Found in GitHub > Settings > Developer settings > GitHub Apps
GITHUB_APP_ID="your_github_app_id"
GITHUB_PRIVATE_KEY="-----BEGIN RSA PRIVATE KEY-----\n...your private key content...\n-----END RSA PRIVATE KEY-----\n"
GITHUB_WEBHOOK_SECRET="your_github_app_webhook_secret"

# JWT & Frontend Configuration
JWT_SECRET="generate_a_strong_random_string"
FRONTEND_URL="http://localhost:5173"

3. Webhook Forwarding with Smee.io

GitHub webhooks require a public URL. For local development, we use smee.io.

1. Go to smee.io and Start a new channel.
2. Copy the generated URL (e.g., https://smee.io/YourRandomString).
3. In your GitHub App settings, set the Webhook URL to your Smee channel URL.
4. In a dedicated terminal, run the Smee client to forward webhooks to your local server:

   npx smee-client -u <YOUR_SMEE_URL> -p 3001 -P /api/webhooks/github

4. Running the Application

Run each of the following commands in a separate terminal from the project root.

1. Start Redis Database:

   docker-compose up -d

2. Install Dependencies:

   npm install

3. Apply Database Migrations:

   npx prisma migrate dev

4. Start the Backend Server:

   npm run start:backend

5. Start the Log Processing Worker:

   npm run start:worker

6. Start the Frontend Server:

   npm run start:frontend

Your application is now running!

• Frontend: http://localhost:5173
• Backend: http://localhost:3001