Approach summary (Cloud Engineer perspective)
I’d protect the platform with layered controls: edge policing, per-tenant quotas, adaptive queueing, circuit breakers, and clear fallbacks so customers get best-effort UX under load.
Token-bucket rate limiting
- Implement at API Gateway/load balancer (AWS API Gateway or Envoy) using a token-bucket to allow burstiness while enforcing steady-state throughput.
- Store counters in a fast store (Redis or DynamoDB DAX) with local leak threads to minimize latency.
- Example: bucket capacity 200, refill 50/sec per endpoint.
Per-customer quotas & fairness
- Track per-customer/tenant buckets and global pool. Enforce hard caps + soft caps with throttling callbacks (HTTP 429 + Retry-After).
- Implement tiered quotas (free vs paid) and emergency reserve to prevent noisy neighbors.
Queueing / backpressure
- Push non-real-time work into durable queues (SQS, Pub/Sub). Use tokenized admission for synchronous paths to SQS write limits.
- Apply consumer autoscaling with concurrency limits (Lambda reserved concurrency or K8s HPA) to protect downstream DB connection caps.
Circuit breakers & health-aware routing
- Add circuit breakers at service-client boundaries (Hystrix-style or Envoy circuit breaking). Open when error rate/latency crosses threshold, fall back to cached data or degraded feature.
- Use health checks + traffic-shaping to route away from hot/failed zones.
Priority lanes & QoS
- Implement priority queues: high-priority (interactive), medium (batch), low (analytics). Enforce preemption for interactive requests. Use weighted fair-queueing in API Gateway/edge proxies.
User-facing fallbacks & observability
- Return graceful responses: cached results, stale-while-revalidate, reduced feature set, or estimated progress; always include Retry-After and user-friendly error codes.
- Monitor limits (CloudWatch/Stackdriver), emit alerts, and auto-scale conservative resources. Add dashboards for per-tenant throttles and SLA violations.
Trade-offs & rationale
- Conservative defaults protect DB/third-party costs at expense of some latency/feature degradation. Durable queues and circuit breakers favor availability. Token-bucket + per-tenant quotas balance fairness and burst handling.
