Systems | Development | Analytics | API | Testing

Software testing at scale comes with unique challenges. Large organizations manage thousands of test cases across multiple projects, often under strict compliance standards and within fast-moving CI/CD pipelines. Until recently, Xray Enterprise existed as an add-on to the main Xray Test Management for Jira app, requiring customers to install and manage both solutions. This created confusion around licensing and setup, and made it harder for teams to understand what they were really getting.

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.

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 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.

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.

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.

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.

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.