Systems | Development | Analytics | API | Testing

Smartphone users worldwide are expected to reach 7.7 billion by 2028. With such an enormous and growing user base, non-functional requirements like performance, security, reliability, and usability can make or break businesses.

Performance testing is essential for ensuring that web applications can handle real-world user loads. A critical part of setting up a reliable test is configuring the ramp-up period correctly in JMeter. Whether you’re a business owner, product owner, developer, or DevOps professional, understanding and configuring this parameter can mean the difference between a test that reflects true performance and one that misses crucial performance problems.

In today’s dynamic digital environment, performance testing stands as a critical pillar in ensuring seamless and efficient applications. JMeter, a widely used open-source load testing tool, offers powerful parameterization features that can transform your testing strategy.

Agile software development is all about moving fast. Quick iterations, faster releases, constant feedback: it’s a model designed for speed and flexibility. Teams love it because it lets them ship features faster and respond to changes without getting bogged down. But here’s the catch: every time you move fast, there’s a risk you’ll break something. That’s where regression testing comes in.

Increasing the test coverage of a backend application is key to ensuring its reliability, functionality, and robustness. Thanks to its intuitive API and agnostic approach to assertions, Mocha has emerged as one of the most popular choices for unit testing in Node.js. In this guide, you'll learn what Mocha is, understand how it works, explore its features, and see it in action with a complete example. Time to become a Mocha unit testing expert!

In the fast-paced world of software development and quality assurance, time is always a critical factor. Teams need tools that streamline processes, enhance collaboration, and minimize manual overhead. That’s where Tricentis Testim comes in, and we’re excited to share some powerful new features that will boost the efficiency of your testing workflows. We’ve listened to your requests and acted on your feedback.

Within the realms of microservices and distributed systems, gRPC has emerged as a cornerstone technology. Its adoption by tech giants like Google, Netflix, and Square underscores its capability to facilitate high-performance, scalable inter-service communication. Built as a modern take on the traditional Remote Procedure Call (RPC) paradigm, gRPC enables services, potentially written in different languages, to communicate efficiently and reliably across networks.

AI-powered development is moving faster than ever. Tools like Cursor, Windsurf, and GitHub Copilot, and models like ChatGPT-4, Claude, and Gemini transform how software is built. These tools can generate code, solve problems, and deliver full applications in a single day, far quicker than traditional methods. But with this rapid development comes a major challenge: testing. While code is generated in hours, traditional testing tools and methods lag.

When you’re gearing up for a big launch—be it a product update, marketing campaign, or just steady growth—you want to know how many people can hammer on your app or website at once before things start to break. That’s where calculating concurrent users comes in. Whether you’re a non‑technical business owner, a student learning the ropes, or a seasoned DevOps engineer, this guide will walk you from the basics to advanced tips in a friendly, jargon‑free way.