Performance and capacity planning tools for QA, SRE and backend teams

Estimate RPS, concurrent users, throughput, load test volume, infrastructure sizing and observability conversions.

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Who this is for

QA engineers, SREs, backend developers and architects who need quick calculations for load, throughput, concurrency and capacity planning without setup overhead.

What you can calculate here

  • Concurrent users to RPS and RPS to users conversion.
  • Safe and theoretical API throughput from latency and workers.
  • Load test request volume and approximate traffic data size.
  • Instance count needed for expected production traffic.
  • Observability time and throughput unit conversions.
  • Initial scenario templates for JMeter and k6.

Learn more about the project scope

FAQ

What is RPS?

RPS means requests per second. It is a throughput unit often used to estimate API and service load.

How do concurrent users relate to throughput?

Each user creates requests over a cycle that includes response time and think time. Throughput grows with users and requests per flow.

How do I estimate API capacity?

Start with latency and effective concurrent execution slots. Divide total concurrency by latency in seconds for a rough upper bound.

How do I size instances for expected traffic?

Divide expected RPS by per-instance capacity, then add safety margin and optional redundancy to get recommended instance count.

Can I use these tools for JMeter or k6 planning?

Yes. The simulator and scenario generator were designed to bootstrap JMeter and k6 test plans quickly.