I'm building a public API and need quotas, logs, and throttling

For a public API, it helps to separate three concerns:

1. Quotas — how much a client is allowed to use over time
2. Throttling / rate limiting — how fast they can send requests right now
3. Logs / observability — how you detect abuse, debug issues, and prove usage

1) Quotas

Use quotas for longer-term limits, such as:

• Requests per day / month
• Requests per minute per API key
• Data transferred
• Number of active resources
• Concurrent jobs
• Feature-specific limits

Common patterns:

• Per API key / tenant
• Per user
• Per organization
• Per endpoint
• Per plan tier: free, pro, enterprise

Example:

• Free: 10,000 requests/month, 5 req/sec burst
• Pro: 1,000,000 requests/month, 50 req/sec burst
• Enterprise: custom

2) Throttling

Use throttling to protect your service from sudden spikes and abuse.

Typical algorithms:

• Token bucket: allows bursts, good for APIs
• Leaky bucket: smooths traffic
• Fixed window: simple, but can be unfair at boundaries
• Sliding window: more accurate, slightly more complex

A practical setup:

• Per-second/minute rate limit
• Burst allowance
• Concurrency limit for expensive operations
• Per-IP fallback limit for anonymous traffic

Example:

• 10 req/sec sustained
• Burst to 30
• 3 concurrent export jobs

3) Logs

Log at multiple levels:

Request logs

Capture:

• Timestamp
• Request ID / correlation ID
• API key or tenant ID
• Endpoint
• Method
• Status code
• Latency
• Payload size
• Rate-limit decision
• Quota remaining

Security/audit logs

Capture:

• Authentication failures
• Permission denials
• Key creation/revocation
• Quota changes
• Admin actions
• Suspicious patterns

Error logs

Capture:

• Stack traces
• Upstream failures
• Timeouts
• Retry counts

Metrics

In addition to logs, track:

• Requests per minute
• 4xx / 5xx rates
• Latency percentiles
• Throttled requests
• Quota exhaustion events

Response headers to expose limits

If this is a public API, return clear limit information:

• X-RateLimit-Limit
• X-RateLimit-Remaining
• X-RateLimit-Reset
• Retry-After when throttled

Example 429 response:

HTTP/1.1 429 Too Many Requests
Retry-After: 60
Content-Type: application/json

{
  "error": "rate_limited",
  "message": "Too many requests. Try again in 60 seconds."
}

Recommended architecture

A common design:

• API gateway / edge proxy handles basic throttling
• Auth service identifies tenant/API key
• Quota service tracks monthly/daily usage
• Centralized logging/metrics for observability
• Async audit pipeline for immutable security logs

For scale, store counters in:

• Redis for real-time rate limiting
• Database / warehouse for durable quota accounting
• Log pipeline like ELK, OpenSearch, Datadog, Splunk, or Cloud Logging

Best practices

• Use multi-dimensional limits: per key, per user, per IP, per endpoint
• Differentiate 429 from 403:
  • 429 = too many requests
  • 403 = not allowed / plan restriction
• Make limits predictable and documented
• Support idempotency keys for retried writes
• Exempt or separately limit webhooks/internal health checks
• Protect expensive endpoints more aggressively
• Keep logs PII-minimized and retention-bounded

A simple policy example

• Anonymous: 60 req/min per IP
• Registered free user: 100 req/min, 10k/day
• Paid user: 1000 req/min, 1M/month
• Export endpoint: 1 concurrent job, 10/hour
• All clients: burst up to 2x sustained rate

If you want, I can also help you design:

• a quota schema
• a rate-limiting algorithm
• a database/Redis implementation
• or an OpenAPI/HTTP header standard for your API.