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The core idea
Different endpoints consume different resources. A cheap catalog lookup and a costly document analysis should not automatically share the same policy. Consider authenticated identity, operation cost and shared infrastructure. IP-based limits can be useful, but many legitimate users may share one network address.
A practical approach
Step 1
Identify what you are protecting: compute, model usage, database capacity or abuse-sensitive actions. Choose limits that reflect the operation’s cost.
Step 2
Return a consistent rate-limit response with safe retry guidance where available. Avoid clients immediately retrying in a tight loop.
Step 3
Monitor which users and actions are affected. Review whether the policy blocks ordinary workflows such as a classroom joining from one network.
Worked example
A training portal may allow frequent lesson reads but limit repeated expensive document-processing requests per account. A school with many learners behind one connection should not be treated exactly like one account flooding the analysis endpoint.
A mistake to avoid
A front-end disabled button does not enforce a rate limit. Enforcement belongs on the service boundary. Also account for retries and background workers so they do not amplify an overload.
Try it yourself
Estimate the requests produced by one normal user journey and one burst of concurrent users. Compare those patterns with your proposed limits before enabling them broadly.
Your implementation checklist
- Limits reflect operation cost.
- Enforcement happens on the server.
- Clients receive a recovery signal.
- Shared-network users are considered.
Share or cite this guide
Innovate with Ajay Editorial (2026-10-04). Design Rate Limits around Resources and User Experience. https://innovatewithajay.com/blogs/design-rate-limits-for-real-users