Updated May 14, 2026
Cloud load testing
Run repeatable load tests on managed runner capacity without rebuilding runner infrastructure for every release.
What this workflow should produce
- A repeatable scenario, load profile, and location plan.
- Shared run results with latency, error, log, and runner-health context.
- A release decision attached to the run instead of scattered notes.
Use case
Cloud load testing helps teams move beyond laptop scripts and one-off runner hosts. The goal is to make capacity, setup, and results repeatable enough that a release decision can depend on them.
How Maxoperf supports it
Create or upload the test, choose a load profile, place managed runners in the right locations, and inspect results in the console. The same workflow can later add private locations when the target requires a different network boundary.
A practical rollout
- Start with a stable API or user journey.
- Run a baseline at low pressure.
- Increase load only after the script and target are healthy.
- Save notes and tags on the run so the next comparison has context.
FAQ
What makes cloud load testing repeatable?
The scenario files, load profile, execution locations, and result review process are kept together so the team can rerun the same test later.