Kusho Record Replay Service

A Flask-based service for collecting, analyzing, and generating test cases for API traffic patterns.

Prerequisites

• Docker and Docker Compose
• Python 3.x (for local development)
• MySQL 8.0
• OpenAI API key (for test generation features)

Quick Start

1. Clone the repository:

   git clone [email protected]:kusho-co/record-replay.git
   cd record-replay

2. Configure the services in docker-compose.yml:

   services:
     collector:
       environment:
         - MYSQL_HOST=mysql
         - MYSQL_PORT=3306
         - MYSQL_USER=kusho
         - MYSQL_PASSWORD=kusho_password
         - MYSQL_DATABASE=kusho_traffic
         - OPENAI_ORGID=your_org_id
         - OPENAI_API_KEY=your_api_key
   
     mysql:
       environment:
         - MYSQL_ROOT_PASSWORD=root_password
         - MYSQL_DATABASE=kusho_traffic
         - MYSQL_USER=kusho
         - MYSQL_PASSWORD=kusho_password

3. Start the services:

   docker-compose up -d

The service will be available at http://localhost:7071.

---

API Endpoints

Event Collection

Collect Events

POST /api/v1/events

• Description: Collect and store traffic events.
• Request Body:

  {
    "events": [
      {
        "id": "event1",
        "timestamp": "2024-12-29T12:00:00Z",
        "data": "event_data"
      }
    ]
  }

• Response:

  {
    "status": "success",
    "message": "Stored <number> events"
  }

---

Traffic Analysis

Get Anomalies

GET /api/v1/analysis/anomalies

• Description: Retrieve traffic anomalies.
• Query Parameters:
  • hours (optional, default: 24): Number of past hours to analyze.
  • min_score (optional, default: 0.0): Minimum anomaly score.
• Response:

  {
    "anomalies": [],
    "count": 0
  }

Analyze Traffic

POST /api/v1/analysis/analyze

• Description: Analyze recent traffic data.
• Request Body:

  {
    "hours": 24
  }

• Response:

  {
    "status": "success",
    "message": "Analyzed traffic for past 24 hours"
  }

Start Analysis Job

POST /api/v1/analysis/start-job

• Description: Start a background job for analyzing traffic and generating tests.
• Request Body:

  {
    "hours": 24
  }

• Response:

  {
    "status": "success",
    "job_id": "<job_id>",
    "message": "Started analysis job for past 24 hours"
  }

Get Job Status

GET /api/v1/analysis/job-status

• Description: Get the status of an analysis job.
• Query Parameters:
  • job_id (required): The ID of the job.
• Response:

  {
    "job_id": "<job_id>",
    "job_status": "completed",
    "result": {},
    "error": null
  }

---

OpenAPI Export

Export OpenAPI

GET /api/v1/export/openapi

• Description: Export the test suite in OpenAPI-compatible JSON.
• Query Parameters:
  • base_url (required): Base URL for the API.
• Response:

  {
    "openapi": "3.0.0",
    "paths": {}
  }

Export OpenAPI for an Endpoint

GET /api/v1/export/openapi/endpoint

• Description: Export OpenAPI-compatible data for a specific endpoint.
• Query Parameters:
  • base_url (required): Base URL for the API.
  • url (required): Endpoint URL.
  • http_method (required): HTTP method (e.g., GET, POST).
• Response:

  {
    "summary": "Endpoint description",
    "parameters": [],
    "responses": {}
  }

---

Miscellaneous

List Available Endpoints

GET /api/v1/endpoints

• Description: List all available API endpoints.
• Response:

  {
    "status": "success",
    "endpoints": ["/api/v1/events", "/api/v1/analysis/anomalies"]
  }

---

Development Setup

1. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # Linux/Mac
   # or
   .\venv\Scripts\activate  # Windows

2. Install dependencies:

   pip install -r requirements.txt

3. Run migrations:

   flask db upgrade

4. Start the development server:

   python -m flask run --port 7071

Docker Configuration

The service uses two main containers:

• collector: The Flask application service
• mysql: MySQL 8.0 database server

Volumes:

• mysql_data: Persistent storage for MySQL data
• migrations: Database migration scripts
• custom.cnf: Custom MySQL configuration