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Requests Per Second Capacity Calculator

Work out requests per second capacity instantly with clear inputs, formula shown and shareable results.

About Requests Per Second Capacity Calculator

Throughput capacity is threads divided by service time — 64 threads at 45 ms each gives about 1,422 requests per second per instance at full saturation. Running at a utilisation target below 100 percent keeps latency stable, and checking capacity with one instance removed is what turns a capacity number into an availability guarantee.

Formula

Throughput capacity

per instance max = threads x 1000 / service time in ms; safe = max x utilisation target; fleet = safe x instances

Worked example

With the default values below, Requests Per Second Capacity Calculator returns Safe fleet capacity of 5,973. Change any input above and every figure here is recalculated in your browser.

Inputs used

Worker threads or connectionsminimum 1
64
Service time per requestminimum 0.01 ms
45 ms
Target utilisationaccepts 1–100 %
70 %
Instances behind the load balancerminimum 1
6

Results

Safe fleet capacity
5,973 req/s
Theoretical maximum
8,533 req/s
Safe capacity per instance
996 req/s
Capacity after losing one instance
4,978 req/s

Step by step

  1. 1Values used
  2. 2Throughput capacity
  3. 3Safe fleet capacity= 5,973 req/s
  4. 4Theoretical maximum= 8,533 req/s
  5. 5Safe capacity per instance= 996 req/s
  6. 6Capacity after losing one instance= 4,978 req/s

Assumptions and limits

  • The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
  • In particular, this calculator does not take inflation, tax or compounding frequency into account.
  • Figures are rounded for display to whole numbers, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Why does latency rise before capacity is reached?

Queueing. As utilisation approaches one, waiting time grows as rho/(1-rho), so the last 20 percent of nominal capacity costs disproportionate latency.

Should capacity be sized for N or N-1 instances?

N-1 at minimum, and N-2 across two availability zones. Sizing for N means any single failure causes an overload.

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