Performance and load testing guides — measure, benchmark, and optimize your app before it hits production.
WebAssembly
WebAssembly is fast — often within 10–20% of native performance — but "fast" is relative. Whether your Wasm module is fast enough depends on the baseline, the workload, and the runtime. Benchmarking Wasm requires measuring both the Wasm execution and comparing it against native, and tracking performance over time
Game Testing
Performance is the most common reason games get negative reviews on mobile and PC. "Unplayable on my device," "terrible framerate," "game crashes after 20 minutes." Most of these issues are detectable before release with systematic performance testing. Frame Rate Testing Defining Performance Targets Before
Testing Tools
Load testing tools have different philosophies about how you define tests, what protocols they support, and how results are presented. k6, JMeter, and Locust are the three most widely used open-source options. Each has legitimate reasons to exist. This guide cuts through the marketing to help you pick the right
5G
5G promises sub-millisecond latency for URLLC (Ultra-Reliable Low Latency Communications) use cases — remote surgery, autonomous vehicles, industrial automation. Testing applications that depend on these guarantees requires different tools and strategies than traditional web performance testing. This guide covers how to validate low-latency requirements, simulate 5G network conditions, and build tests
Testing Strategy
Netflix's infrastructure team had a problem in 2010: they couldn't be sure their systems would survive an AWS outage. Their solution — a tool that randomly terminates production instances — became Chaos Monkey, and the discipline around it became chaos engineering. The core idea: instead of hoping your
Testing Tools
Gremlin is a commercial chaos engineering platform that simplifies running controlled failure experiments at scale. Where open-source tools like Chaos Mesh require Kubernetes expertise to operate, Gremlin provides a web UI, pre-built attack scenarios, and team collaboration features. This tutorial covers setup, running your first experiments, and building a chaos
Performance Testing
k6 is known as a load testing tool. What's less known is that it's also effective for chaos testing — simulating fault conditions, injecting failures at the application layer, and validating resilience under degraded conditions. This guide covers k6's chaos capabilities: the k6 Disruptor extension,
Testing
Your app works fine with five users. You've tested it manually, the happy paths are green, and everything looks good. Then traffic spikes — a Product Hunt launch, a newsletter hit, a mention on Hacker News — and your API starts returning 503s. Response times climb from 200ms to 8
Testing
You can write load tests in Python with Locust — no XML, no GUI needed. Just a plain Python file describing what your virtual users do, then a command to run it. That's the entire model. If you've wrestled with JMeter's thread groups and XML
Testing
Load testing is not optional. If you have not verified that your system holds up under real traffic, you are shipping blind. The question is not whether to load test — it is which tool fits your stack, your team, and your CI pipeline. Five tools dominate the field: k6, Artillery,
Testing
Apache JMeter has been the go-to load testing tool in enterprise QA shops for over two decades. It is open source, Java-based, and capable of simulating thousands of concurrent users against HTTP endpoints, databases, message queues, and more. If your team has existing .jmx files or your QA process requires
Testing
Your Node.js API handles 10 concurrent users without breaking a sweat. Your staging environment runs clean. Then you ship, traffic picks up, and at 300 simultaneous users the response times double, the queue backs up, and your database starts dropping connections. Nobody saw it coming because nobody tested it