Systems | Development | Analytics | API | Testing

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.

Your teams don’t buy features; they buy outcomes. Speed to insight, trusted AI, lower TCO. That’s the lens for our Qlik Product Recap, a curated view of what’s new across Qlik and why it matters. We loved meeting many of you at Qlik Connect, and you’ll see several features we highlighted there plus everything we’ve shipped since, organized by the outcomes they enable. While Qlik Connect is a great moment to showcase innovation, it’s only one waypoint.

As we pass through the years, the electric vehicle (EV) industry has become all about driving smarter, faster, and more connected than ever before. With the rapid adoption of EVs, expanding charging networks, and evolving consumer expectations, the need for advanced digital ecosystems has become critical. From charging station locators to battery analytics, fleet management, and EV-sharing platforms, every interaction now relies on intelligent, data-driven technology.

The global retail landscape has undergone a massive digital revolution. With online shopping now accounting for a growing share of global sales, the e-commerce market is expected to surpass $8 trillion by 2027. From small retailers to global enterprises, every brand is racing to deliver seamless, secure, and personalized digital shopping experiences, and eCommerce apps are at the center of this transformation.

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.

Imagine your Node.js app is like a super-fast sports car. The "loader" is its transmission — that crucial part that gets the engine's power to the wheels, making everything run smoothly. If that transmission starts acting up, your speedy app will just sputter and stop. So, it's simple: a good loader means your app flies, a bad one means it's stuck in neutral. In this post, we'll explore how to improve your Node.js app's performance with its loader. But first, what exactly is this loader thing?

The age of agentic AI introduces unprecedented risks. In the rapidly evolving landscape of artificial intelligence, agentic AI is emerging as a transformative force, capable of autonomous decision-making, learning, and interaction. These sophisticated AI systems are poised to revolutionize industries and daily life. Conversely, these same capabilities can be exploited by attackers to launch highly effective and scalable cyberattacks. The advancement of AI brings a critical imperative.

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.

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.

Spend less time waiting and more time doing the work you love! One of the defining moments of my software career was learning the motto “if it hurts, do it more.” What the heck? This concept feels totally counterintuitive. But give it a moment’s thought, and you soon realize that as developers we are instructed to lean into the bad parts of our process so that we fix them and make them stop hurting.