feat(rate-limiting): add per-bucket limits and startup validation

- Add per-bucket rate limit config (ban, unban, import, config, jail, filter, action)
- Add process-local warning at startup for multi-worker deployments
- Document Redis migration path for shared state across workers
- Remove Issue #42 from Tasks.md (resolved)

Docs/Deployment.md

@@ -113,6 +113,56 @@ If fail2ban goes offline but the backend always returns 200, Docker treats the c
 ---
 
 
+## Rate Limiting
+
+Rate limiting is enforced at two levels:
+
+1. **Global middleware** — Per-IP request rate limit across all endpoints (default: 200 requests/minute per IP)
+2. **Per-bucket limits** — Stricter limits on specific operations:
+
+   | Bucket | Limit | Window | Purpose |
+   |--------|-------|--------|---------|
+   | `bans:ban` | 100/min | 60s | Ban operations |
+   | `bans:unban` | 100/min | 60s | Unban operations |
+   | `blocklist:import` | 10/hour | 3600s | Import operations |
+   | `config:update` | 50/min | 60s | Config write operations |
+   | `jail:*` | 100/min | 60s | Jail management |
+   | `filter:*` | 50/min | 60s | Filter management |
+   | `action:*` | 50/min | 60s | Action management |
+
+### Process-Local Scope
+
+**Current implementation is process-local.** Each worker maintains independent in-memory counters. In a multi-worker deployment (N workers), an attacker can send up to N × limit requests before any single worker triggers a block — effectively multiplying the allowed request rate by the number of workers.
+
+**Short-term mitigation:** The scheduler lock enforces single-worker mode. The startup warning log (`rate_limiting_process_local_only`) documents this constraint. Deploy with one worker.
+
+**Long-term solution:** Replace the in-process GlobalRateLimiter with a Redis-backed adapter. The `check_allowed()` and `check_allowed_for_bucket()` interfaces are designed for a drop-in replacement using atomic `INCR` + `EXPIRE` semantics — no changes needed in middleware or router code.
+
+### Redis Migration (Future)
+
+When migrating to Redis, replace the in-memory deque store with:
+
+```python
+# Atomic increment with expiry (pseudo-code)
+count = redis.incr(f"rl:{ip}")
+if count == 1:  # First request, set expiry
+    redis.expire(f"rl:{ip}", window_seconds)
+if count > max_requests:
+    return False, window_seconds - redis.ttl(f"rl:{ip}")
+return True, 0
+```
+
+The bucket variants use `INCR` + `EXPIRE` on `rl:{bucket}:{ip}` keys. This preserves the sliding-window semantics while providing shared state across all workers.
+
+### Monitoring
+
+Check logs for these events:
+- `global_rate_limit_exceeded` — Global middleware blocked a request (WARNING)
+- `rate_limiting_process_local_only` — Startup warning about multi-worker limitation (WARNING)
+- `rate_limiter_cleanup` — Periodic cleanup of expired entries (DEBUG)
+
+---
+
 ## CORS Configuration
 
 Cross-Origin Resource Sharing (CORS) must be explicitly configured when the frontend and backend are served from different origins.