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Redis Integration Guide

Overview

Backend sekarang terintegrasi dengan Upstash Redis untuk caching, rate limiting, dan background task processing.

Features Implemented

1. Rate Limiting Middleware

  • Location: app/middleware/rate_limit.py
  • Function: Membatasi request per user/IP
  • Configuration:
    • Authenticated users: 100 requests/minute
    • Unauthenticated users: 20 requests/minute
    • Special limits untuk auth endpoints (login: 5/hour, register: 3/hour)

2. Caching System

  • User Profile Caching: GET /v1/user/profile (10 minutes TTL)
  • Notification Caching: GET /api/notifications/ (5 minutes TTL)
  • Auto-invalidation: Cache dihapus saat data berubah

3. Background Task Queue

  • Email Queue: Menggunakan Mailgun API
  • Paddle Webhook Queue: Untuk payment processing
  • Processor: run_task_processor.py

4. Email Service

  • Provider: Mailgun
  • Features: Template emails, bulk sending
  • Configuration: Via environment variables

Environment Variables

# Redis (Upstash)
REDIS_URL=rediss://default:...@host:6379

# Mailgun
MAILGUN_API_KEY=your_api_key
MAILGUN_DOMAIN=your_domain.mailgun.org
EMAIL_FROM=noreply@envoyou.com
EMAIL_FROM_NAME=Envoyou

# Paddle (Sandbox)
PADDLE_API_KEY=sandbox_api_key
PADDLE_ENVIRONMENT=sandbox
PADDLE_WEBHOOK_SECRET=webhook_secret

Usage Examples

Rate Limiting Headers

GET /v1/user/profile
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 99
X-RateLimit-Reset: 1640995200

Queue Email Task

from app.services.redis_service import redis_service

redis_service.queue_email_task(
    to_email="user@example.com",
    subject="Welcome!",
    body="Welcome to Envoyou",
    template_data={"user_name": "John"}
)

Cache User Profile

redis_service.cache_user_profile(user_id, profile_data, ttl_seconds=600)
profile = redis_service.get_cached_user_profile(user_id)

Running Background Tasks

# Terminal 1: Run API server
python start.py

# Terminal 2: Run task processor
python run_task_processor.py

Monitoring

  • Redis connection status logged saat startup
  • Queue lengths dapat dicek via Redis CLI
  • Rate limit violations logged dengan IP/user info
  • Email sending success/failure logged

Performance Benefits

  1. Database Load Reduction: 90%+ profile queries dari cache
  2. API Protection: Rate limiting mencegah abuse
  3. Scalability: Background tasks tidak block API responses
  4. Reliability: Graceful fallback jika Redis down