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API Request Estimator

Estimate API traffic, peak load, retries, data transfer, and monthly cost from users and per-user request behavior.

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API load summary

Healthy

Status

Bottleneck check: Rate limit usage 16.7%

Monthly requests

9,504,000

Peak RPS

20

Monthly transfer

181.84 GB

Estimated monthly cost

$68.87

Quick examples

Traffic

Cache and retries

Pricing and limits

Bottleneck check

Rate limit usage16.7%
Origin calls avoided by cache3,326,400
Retry requests29,652

Headroom above peak

100 RPS

Expected final failures

28,664

What-if scenarios

Compare launch traffic, better caching, and retry spikes without changing your current inputs.

ScenarioRequestsPeak RPS

Current

9,504,000

20

Launch x2 users

19,008,000

40

Cache +20pp

9,504,000

20

Retry spike

9,504,000

20

Check before launch

Confirm whether the provider bills gateway calls or origin calls.
Check both steady rate limits and short burst limits.
Cap retries and use exponential backoff during upstream incidents.
Separate cacheable read endpoints from write or payment endpoints.

Why estimate API requests?

API cost and reliability risk are driven by peak rate, cache behavior, and retry policy as much as average monthly volume. This estimator turns product usage assumptions into monthly calls, RPS, transfer volume, billable usage, and practical launch checks.

Usage notes

  • Monthly requests = users x daily requests per user x active days.
  • Peak RPS = average RPS x peak multiplier.
  • Billable requests = monthly requests + retry requests - included requests.
  • Transfer = billable requests x average request and response size.

Frequently asked questions

What peak multiplier should I use?expand_more

Use 3-5x for a first estimate. If traffic is concentrated around launches, alerts, or work hours, test 8x or higher.

How is cache reflected?expand_more

Cache hit rate is shown as avoided origin calls. If your provider bills gateway requests, confirm the actual billing basis.

Why include retries?expand_more

Automatic retries increase request volume. Use backoff and retry caps to prevent spikes during upstream incidents.

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