Systems | Development | Analytics | API | Testing

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.

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.

You know the feeling, you push a new feature, and your tests should catch any issues. But instead, they fail inconsistently, slow down your pipeline, or worse… pass when they shouldn’t. End-to-end testing is always a risk. That's precisely the reason why more teams are turning to end-to-end testing with Playwright. Unlike clunky legacy frameworks, the Playwright testing framework was built for speed, reliability, and cross-browser accuracy all out of the box.

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.

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.

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.

Would you believe me if I say there is a development methodology that considers changing requirements and technical risks as part of the process instead of obstacles to be overcome? Sounds crazy, right? That’s exactly what I thought about the Spiral Model until I took a closer look. I’m not saying it’s perfect for every project or that we should all use it. But for certain types of projects, the messy, uncertain, high-stakes ones, it may be just what you need!

Not every failure is a bug and not every bug is what it seems. Sometimes, a test fails without warning. No code changes, no environment issues, just a red mark where there should be green. You rerun it, and it passes. These are flaky tests. And they do more than create noise. They drain team time, stall releases, and make it harder to trust automation at all. Left unchecked, they quietly become one of the most expensive problems in testing.