Need API traffic control and caching

If you want API traffic control and caching, the usual solution is to put an API gateway / reverse proxy in front of your services and configure:

Traffic control

• Rate limiting: requests per second/minute per API key, user, IP, or route
• Burst control: allow short spikes while enforcing an average limit
• Quotas: daily/monthly usage caps
• Concurrency limits: cap simultaneous in-flight requests
• Timeouts / circuit breaking: protect backend services from overload
• Request throttling by route: stricter limits on expensive endpoints

Caching

• Response caching for GET/HEAD endpoints
• Edge caching / CDN caching for public data
• Cache keys based on path, query params, headers, auth scope
• TTL controls: short TTL for dynamic data, longer TTL for static/reference data
• Cache invalidation:
  • TTL-based expiry
  • event/webhook-based purge
  • versioned URLs or cache tags

Common implementation options

• API Gateway: Kong, Apigee, AWS API Gateway, Azure API Management, NGINX, Envoy
• CDN: Cloudflare, Fastly, Akamai
• App-level cache: Redis, Memcached
• Database/query cache: for expensive repeated reads

Typical setup

1. Gateway enforces auth + rate limits
2. CDN/cache layer serves cacheable GET responses
3. Backend app uses Redis for hot data and computed results
4. Monitoring/alerts track:
   • requests/sec
   • 429 responses
   • cache hit ratio
   • backend latency
   • error rate

Best practices

• Don’t cache personalized or sensitive responses unless carefully scoped
• Use Cache-Control, ETag, Last-Modified
• Return 429 Too Many Requests with Retry-After
• Make limits hierarchical: global → tenant → user → endpoint
• Protect heavy endpoints more aggressively than cheap ones

If you want, I can also give you:

1. a recommended architecture,
2. NGINX/Kong/Cloudflare config examples, or
3. a Redis-based caching + rate limiting design.