Caching Strategies

# Cache Architecture

┌─────────────────────────────────────┐
│           Request Flow              │
└─────────────────────────────────────┘
            │
            ▼
┌─────────────────────────────────────┐
│   L1: In-Memory (lru_cache)         │
│   ├── TTL: 60 seconds               │
│   ├── Size: 1000 entries/worker     │
│   ├── Latency: ~0.1ms               │
│   └── Scope: Single process         │
└─────────────────────────────────────┘
            │ miss
            ▼
┌─────────────────────────────────────┐
│   L2: Redis Cluster                 │
│   ├── TTL: 5-60 minutes             │
│   ├── Size: 10GB (3 nodes)          │
│   ├── Latency: ~1ms                 │
│   └── Scope: All instances          │
└─────────────────────────────────────┘
            │ miss
            ▼
┌─────────────────────────────────────┐
│   Origin: PostgreSQL / ML Service   │
│   └── Latency: 10-500ms             │
└─────────────────────────────────────┘

# Redis Cluster Setup

import redis.asyncio as redis
from redis.asyncio.cluster import RedisCluster

# Cluster configuration
redis_cluster = RedisCluster(
    host="redis-cluster.justkalm.internal",
    port=6379,
    password=REDIS_PASSWORD,
    
    # Connection pool
    max_connections=100,
    socket_connect_timeout=5,
    socket_timeout=5,
    
    # Retry configuration
    retry_on_timeout=True,
    health_check_interval=30
)

# Key namespacing
CACHE_PREFIXES = {
    "valuation": "val:",      # val:{product_id}
    "product": "prod:",       # prod:{product_id}
    "user": "usr:",           # usr:{user_id}
    "session": "sess:",       # sess:{session_id}
    "rate_limit": "rl:",      # rl:{api_key}:{endpoint}
    "feature_flag": "ff:",    # ff:{flag_name}
}

# TTL by cache type
CACHE_TTLS = {
    "valuation": 3600,        # 1 hour
    "product": 900,           # 15 minutes
    "user": 300,              # 5 minutes
    "session": 86400,         # 24 hours
    "rate_limit": 60,         # 1 minute
    "feature_flag": 30,       # 30 seconds
}