18. System Design Case Study 2: Distributed Rate Limiter & Web Application Firewall • High-Level System Design (HLD): Distributed Systems at Scale • Rishabh Ki Kaksha

*   **Requirements:** Million QPS scale, sub-millisecond overhead (< 2ms), multi-region active-active synchronization.
*   **Core Engine:** Redis Cluster with Lua Scripts (Atomic Execution without race conditions).

```
[ Client ] ➔ [ API Gateway / Envoy Proxy (Filter Plugin) ]
                     ⬇ (Async Check < 1ms)
             [ Distributed Redis Cluster (Lua Script Token Bucket) ]
               ├── Allowed? ➔ Route to Backend Microservices
               └── Exceeded? ➔ Return HTTP 429 Too Many Requests
```

---

### 2. Atomic Redis Lua Script Implementation

```lua
local key = KEYS[1]
local capacity = tonumber(ARGV[1])
local refill_rate = tonumber(ARGV[2])
local now = tonumber(ARGV[3])
local requested = tonumber(ARGV[4])

-- Fetch current state from Hash:
local data = redis.call('HMGET', key, 'tokens', 'last_refreshed')
local tokens = tonumber(data[1]) or capacity
local last_refreshed = tonumber(data[2]) or now

-- Calculate refilled tokens:
local elapsed = math.max(0, now - last_refreshed)
tokens = math.min(capacity, tokens + (elapsed * refill_rate))

if tokens >= requested then
    tokens = tokens - requested
    redis.call('HMSET', key, 'tokens', tokens, 'last_refreshed', now)
    redis.call('EXPIRE', key, 3600)
    return 1 -- Allowed
else
    return 0 -- Rejected (429)
end
```

---

### 3. Interview Ke 3 Sawal Is Topic Se

1. **Multi-region Redis sync lag me rate limit bypass kaise rokte hain?** -> Local Token Bucket + Global Asynchronous Synchronizer (Local rate limiters 80% budget locally satisfy karte hain).
2. **Shadow Rate Limiting kya hoti hai?** -> Naye rate limit rules ko production me pehle dry-run mode me chala kar metrics track karna bina actual requests ko drop kiye.
3. **DDoS mitigation me WAF (Web Application Firewall) rate limiter se pehle kyu lagti hai?** -> Malicious bot IP signatures, TLS fingerprints aur volumetric L3/L4 floods ko Edge network par hi drop karne ke liye.

---
**Next Topic:** 19. System Design Case Study 3: Real-Time Chat & Notification System (WhatsApp / Slack)

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Rishabh Gehlot

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