Updated May 14, 2026
API performance testing
Validate API latency, throughput, and correctness before releases using engine files and result signals your team can review.
What this workflow should produce
- A scenario that represents a real API journey.
- p95 or p99 latency targets connected to release risk.
- Error and assertion signals that explain correctness, not just speed.
Use case
API performance testing answers a narrow question: can this API handle the expected request shape without unacceptable latency or errors?
How Maxoperf supports it
Maxoperf supports scenario-driven runs with explicit load profiles, managed or private runner locations, and results that can be broken down by label. That helps backend teams see which endpoint or journey changed.
A practical rollout
Start with a small smoke profile. Once the script is stable, turn it into a release-candidate run with thresholds for latency, error rate, and assertions.
FAQ
What is the first API performance test to automate?
Choose one revenue-critical or reliability-critical API path with stable data, clear assertions, and an agreed latency threshold.