Locust vs Artillery
Feature checklists rarely decide anything. What decides it is the pricing metric, who has to write the tests, and which limitation you can live with.
Entry price
Free and open source
Open sourceFree and open source
Open sourceWhat drives the bill
The metric that actually scales your invoice.
Free and open source. You pay in engineering time and CI minutes.
Open source and free, including distributed runs on your own AWS account. You pay AWS, not Artillery.
Free tier
Everything, self-hosted
Everything, self-hosted
Open source
MIT
MPL-2.0
Self-hostable
No-code authoring
Languages
Platforms
Fits teams
Adoption
Widely used
OSS community · since 2011
Widely used
Artillery Software · since 2015
Strengths
- Test scenarios are plain Python, so any logic is expressible without workarounds.
- Distributed mode is conceptually simple and works well on Kubernetes.
- Live web UI is useful during an exploratory ramp-up.
- Distributed load on your own AWS account, so no per-virtual-user vendor pricing at all.
- Reuses Playwright scripts for browser-level load without rewriting journeys.
- YAML for simple scenarios, JavaScript when you need real logic.
Limitations
- Python's per-user overhead is higher than k6 or Gatling; big loads need more machines.
- Reporting is basic — plan on exporting to Grafana.
- HTTP-centric; other protocols require writing your own client.
- Serverless distribution requires AWS knowledge and IAM setup.
- Reporting is basic without exporting to an observability platform.
- Smaller community than k6 or JMeter.
Best for
Python teams who want load scenarios expressed in their own language.
AWS-native teams that want large-scale load tests without vendor VU pricing.
All of these integrate with: GitHub Actions.
Pricing last reviewed August 2026 and is indicative only — confirm on each vendor’s own page.