Systems | Development | Analytics | API | Testing

Some topics are just too trendy to overlook, and AI in testing is definitely one of them. A few weeks ago, we shared a blog post introducing the integration between an MCP server and OctoPerf, highlighting the many benefits it brings. To illustrate this in action, we recently hosted a webinar led by Thomas Pitteman, performance testing expert at Adeo and OctoPerf power user.

The Zen of Python encapsulates the characteristics that led to Python being recognized as one of the most loved programming languages in the world. The principles, written by Tim Peters, are not meant to be absolute rules, but gentle reminders to consider in pursuit of writing beautiful, clean, and efficient code. They are all based on qualities that Python espouses: simplicity, clarity, and beauty.

September brings a powerful wave of innovation across the Katalon Platform, led by the new StudioAssist Agent Mode, AI-driven insights in TestOps, and smarter, more resilient executions in TestCloud. This month’s updates redefine productivity for modern QA teams, helping testers code faster, debug smarter, and execute at scale with confidence.

As AI-powered agents begin to play a more active role in quality engineering, regulated industries especially in BFSI, healthcare, and government face a critical question: How do you scale agentic QA without losing control, visibility, or auditability? This blog explores how to make agent-augmented QA compliant, explainable, and trustworthy, not just in spirit, but in process, tooling, and evidence. We’re not talking about testing AI systems.

Drone technology — also known as unmanned aerial vehicle (UAV) and unmanned aircraft system (UAS) technology — is expanding rapidly across commercial, industrial, and defense sectors. As these systems become more complex, they increasingly rely on sophisticated software for aerial embedded systems.

Replaying traffic is a core tool in your toolbox when you need to reproduce a tricky bug or validate how your app behaves. Traffic replay is especially valuable for testing complex software applications that rely on APIs and microservices, where integration and functionality must be thoroughly validated.

A few years ago I was on call during the Super Bowl. At the time I was working for an observability vendor and one of our customers had an outage caused by a surge in user traffic. But our monitoring system didn’t have enough data to know what went wrong and I sat on a call for 2 hours painfully listening to them spinning up more servers and trying to catch up with the user load.

When the automotive industry introduced the concept of Levels of Autonomy, it gave us a shared language for something profound. It wasn’t just about self-driving cars, it was about how humans and intelligent systems work together as execution gradually shifts from one participant to the other. Level 0 is full human control. Level 5 means the car can handle any situation on its own. And between those two extremes are a series of stages that capture both technological progress and human adaptation.

Our latest research paints a concerning, albeit solvable, situation of blame and misalignment.