Systems | Development | Analytics | API | Testing

Recently I had the joy of talking to Daniel Knott, a well-known YouTuber and QA leader in the Healthcare testing space. He shares a lot of his knowledge and experience on his channel as well as his blog called Adventures in QA. In this interview, we talked about how Daniel found himself in the QA world, how he applies automation testing in his day-to-day work, and the implications of AI for Healthcare testing. Here are some takeaways from the discussion for you.

Amazon API Gateway and AWS Lambda are widely used for deploying and running scalable APIs or applications in the cloud. While they offer powerful capabilities for deploying and scaling APIs, designing the API or maintaining visibility into performance and reliability can be challenging without the right tools in place.

Automating API documentation can save time, reduce errors, and improve efficiency in enterprise systems. Here's why it matters and how it works: Why It’s Important: APIs are crucial for enterprise operations, but manual documentation often lags behind code updates, leading to errors, delays, and increased support costs. Challenges of Manual Documentation: It’s time-consuming, prone to human error, and pulls developers away from critical tasks.

If you have spent some time developing Flask applications, you have probably encountered terms like request, session, current_app, and g. You might even use them daily. But have you ever stopped to think about how Flask makes these seemingly global objects available exactly when you need them, especially in a multi-threaded web server environment? Well, the magic lies in Flask's context system. In this article, you will learn what contexts are in Flask and how to use them with practical examples.

You’ve just wrapped a long sprint. Deadlines are tight, and QA is struggling with flaky test runs. Your team debates the age-old question should we stick with Selenium or finally migrate to Playwright? It’s not just about speed anymore; it’s about control, visibility, and smarter automation. The truth is, both Playwright and Selenium have their strengths but only one fits your product, pace, and team DNA.

It has never been more critical to establish a solid foundation for regulatory compliance. Regulations govern a wide range of functions. Some of them are obvious, such as health and human services, patient data, medical devices, and credit payments. Some of them are less obvious, especially with the ever-changing definition of what constitutes private and identifiable data. This article provides an overview of regulatory compliance challenges and the hidden risks organizations face beneath the surface.

NeoLoad has long been at the forefront of modern performance testing, trusted by enterprises around the world to help them test earlier, test faster, and scale performance across even the most complex environments. Its intuitive design and powerful automation have made it the go-to solution for teams seeking speed, reliability, and breadth of capabilities. Today, expectations for software teams continue to grow.

Ever wondered why some software projects soar while others stall out? It’s not just the tech stack, it’s the game plan behind it. With the global software development market projected to hit $570 billion in 2025 and growing at 12.9% CAGR, picking the right development model isn’t just smart-it’s survival.

Since GDPR rolled out in 2018, enforcement has intensified. In 2023 alone, EU regulators levied roughly €2.1 billion in fines for non-compliance. That includes a jaw-dropping €1.2 billion strike against Meta for unlawful data transfers between the EU and the U.S., marking it the most significant GDPR penalty. Let’s be real. Data is serious business, and building software without GDPR compliance is like launching a bank without a vault.

We're excited to announce the general availability of Konnect Debugger, formerly known as Active Tracing during its tech preview phase. This powerful debugging and observability solution in Kong Konnect has evolved from a focused tracing tool into a comprehensive debugging platform.