My Load Testing Origin Story (And Why I’m Writing This Tutorial)

The first time I was asked to load test a website I had no idea where to start. No ChatGPT to ask. My coworkers were either just as clueless or too busy to walk me through it. So I did what any junior QA does — I Googled my way through it alone.

The site was about as simple as it gets. One page. One PDF to open or download. That’s it. And I still couldn’t pull it off.

The Gatling Disaster

I found Gatling. JMeter existed but I’d read it was hard to set up, so I got intimidated and skipped it. Gatling seemed friendlier — which in hindsight is funny because it used Scala and I only knew Java. But I could work with Scala enough to get started.

Gatling had a recorder that captured my browser flow and generated Scala code automatically. I ran it. Errors everywhere.

And here’s the thing — I had no idea what the errors meant. Was the Scala code not generating load correctly? Was the site actually buckling under pressure? Was my laptop’s CPU and RAM the bottleneck? Was it my wifi? I genuinely could not tell. I had charts and data in front of me and couldn’t interpret any of it. A senior QA looked at the results and offered some insights, but I never felt confident the site had been properly tested. I never even heard whether the launch went well or not.

That was my introduction to load testing. It was a failure and I knew it.

What I Later Figured Out

Years later, working at an ed-tech company, I ran into similar errors using JMeter — error messages I initially mistook for application problems. When I finally read them carefully I realized they were JMeter’s own BindException errors. The load wasn’t even reaching the application. My system was the bottleneck, not the site.

That’s when it clicked. The Gatling disaster probably wasn’t Gatling’s fault. I just didn’t know how to tell the difference between a tool problem and an application problem. Nobody had taught me that. And without knowing what to look for, all those charts and error messages were noise.

The Project That Changed Everything

At the ed-tech company we were preparing for a major course platform launch. A university was opening enrollment and potentially thousands of students would hit the site within minutes to purchase courses and enroll. My job was to load test the checkout and enrollment flow.

This time I had a team. Three of us figured it out together — which made all the difference.

We discovered BlazeMeter’s recorder, which captured the API calls made during the checkout flow cleanly and accurately. That’s when I learned something that reframed everything: what we’re really load testing is backend service performance. Not whether the page looks right. Not whether the button works. Whether the servers can handle the volume of requests hitting them all at once.

We ran tests. Got real results. The data pointed to specific endpoints that were slow under load, the dev team optimized them, and when the launch happened the site held up. Thousands of users, enrollment open, no meltdown.

It wasn’t magic. It was a process we built together through trial and error — and it actually worked.

Why I’m Writing This

Load testing took me years and multiple real projects to feel comfortable with. There was no single tutorial that walked me through it the way I needed. I learned it the hard way, across different tools, different teams, and different levels of chaos.

This tutorial series is what I wish had existed when I was staring at Gatling error messages alone with no idea what they meant.

In the next post I’ll walk you through the exact JMeter workflow we used for that ed-tech launch — from recording your first test with BlazeMeter to running thousands of simulated users and actually understanding what the results are telling you.