Locust
Scalable load tests in plain Python
The Lens
Define user behavior as Python code, point Locust at your endpoint, and scale up to millions of simulated users. The web UI shows real-time results: requests per second, response times, failure rates.
The reason developers love this: it's just Python. No special syntax, no config files, no learning a testing DSL. If you can write a Python function, you can write a load test. Need to test a complex multi-step flow with authentication? It's just Python code.
MIT. Fully free. No paid tier, no cloud service. The homepage links to PyPI, not a commercial product.
The catch: Locust is CPU-bound because of Python's GIL. For high-throughput testing (10K+ requests/sec), you need to run distributed across multiple workers. Tools like k6 (Go-based) handle higher throughput per instance. Also, the web UI is functional but basic. If you want fancy dashboards, you'll need to export metrics to Grafana.
Free vs Self-Hosted vs Paid
fully freeFully open source under MIT. No paid tier, no hosted service, no commercial edition. Install via pip, write Python, run tests.
Your costs are the infrastructure to generate load. A single machine handles moderate tests. For serious load (100K+ concurrent users), you run distributed workers. Budget for the cloud compute to generate that traffic. A swarm of 5 workers on $20/mo VMs costs $100/mo during testing.
Free. Your only cost is the compute to generate load.
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