Load Testing
Every "Artillery vs k6 vs JMeter" comparison online has the same "resource usage: Moderate/Low/High" row and no numbers behind it. We got tired of repeating that without evidence, so we built a fixed target server, ran all three tools against it with matched load
Load Testing
A load test that only hits one endpoint tells you how fast that endpoint is. It doesn't tell you how your system behaves when users log in, search for products, add items to a cart, and check out — all at the same time, with realistic delays between actions.
Load Testing
Out of the box, Artillery gives you latency percentiles and status code counts. That's a starting point, but for serious load testing you need custom assertions, metrics that go to your observability stack, and hooks to run custom logic during tests. Artillery's plugin system covers all
Load Testing
Artillery is a load testing tool built for developers. You write YAML, you run a command, you get results. No GUI to learn, no Java heap to tune, no XML to wrestle. If you can write a curl command, you can write an Artillery test. This post covers installation, the
Load Testing
Running load tests manually before releases is better than not running them. Running them automatically on every pull request is better still. Blocking a merge when performance regresses is the goal. This post covers integrating Artillery into GitHub Actions and GitLab CI, setting thresholds that actually gate deployments, and strategies
Testing
Artillery covers the basics well — YAML config, HTTP scenarios, simple ramp patterns. The advanced features are where it earns its place for complex load testing: custom JavaScript processors, stateful sessions, WebSocket testing, multi-environment configs, and plugin integration. This guide covers them all. Custom Processors Custom processors let you write
WebSocket
HTTP load testing is well understood. WebSocket load testing is not. Most teams either skip it entirely or discover their WebSocket server collapses at 500 concurrent connections only after a major feature launch. This guide covers the tools, metrics, and test scenarios that matter for WebSocket performance. Why WebSocket Load
Shift-Left Testing
Performance problems discovered in production are the most expensive kind. By the time a performance regression surfaces in user complaints or SLO violations, it's been deployed, it's affecting real traffic, and the engineers who introduced it have moved on to other features. Shift-left performance testing